Patent Publication Number: US-10778644-B2

Title: Determining security features for external quantum-level computing processing

Description:
CROSS-REFERENCE TO RELATED APPLICATION 
     This application is a continuation of and claims priority from allowed, co-pending U.S. patent application Ser. No. 15/437,904, filed on Feb. 21, 2017 and entitled “Determining Security Features for External Quantum-level Computing Processing”. 
    
    
     FIELD OF THE INVENTION 
     The present invention related to data security and, more specifically, determining security features for a data set that requires external quantum-level processing. 
     BACKGROUND 
     Quantum computing involves theoretical computation systems that make direct use of quantum-mechanical phenomena, such as superposition and entanglement, to perform operations on data. Whereas common digital computing requires that the data be encoded into binary digits (i.e., bits), each of which is always in one of two definite states (0 or 1), quantum computation uses quantum bits, which can be in superpositions of states. 
     While quantum computing is a burgeoning technology, its use is foreseen to grow in the near future as a means of solving complex problems more efficiently. However, technical challenges exist in building large-scale quantum computers and, as such, quantum-capabilities are limited. Thus, in the event that an entity, such as an enterprise, corporation, university or the like has a need or will have a need in the future to implement quantum-level computing, the entity is likely to rely on third-party entities (i.e., entities external from the enterprise, corporation, university or the like) to conduct such processing of data. 
     However, in today&#39;s computing environment in which data is entrusted in other entities, data breaches occur at an alarming rate. A data breach is a security incident in which data, typically sensitive, protected confidential data is copied, viewed, misappropriated or otherwise used by individuals/entities other than those authorized to do so. The breaching of data may be part of multiple entities acting together (e.g., collusion or conspiracy) or implicate governments or the like (e.g., espionage). Such data breaches may be intentional (i.e., perpetuated by wrongdoers) or unintentional, but in either instance, once the data has been comprised, the harm to the data owner is unavoidable. In this regard, when an entity provides data to a third-party/external entity, the entity runs the risk that the data may be breached. 
     Therefore, a need exists on the behalf of entities who desire to have third party/external entities perform quantum-level processing of the entity&#39;s data to limit the risk related to the possibility of the data being breached/comprised. In this regard, the desired systems, methods, and the like should lessen, if not eliminate, the risk to the data owner in the event that the data is breached/comprised by the third party/external entity. Moreover, desired systems, methods and the like should apply requisite security features to the data sets that require external quantum-level processing that are consistent with the confidentiality of the data set and take into account time constraints associated with the processing of the data. 
     SUMMARY 
     The following presents a simplified summary of one or more embodiments in order to provide a basic understanding of such embodiments. This summary is not an extensive overview of all contemplated embodiments, and is intended to neither identify key or critical elements of all embodiments, nor delineate the scope of any or all embodiments. Its sole purpose is to present some concepts of one or more embodiments in a simplified form as a prelude to the more detailed description that is presented later. 
     Embodiments of the present invention address the above needs and/or achieve other advantages by providing apparatus, systems, computer program products, for applying security measures to data sets requiring external/third-party quantum-level processing. By providing such security measures to the data sets prior to communicating/transferring the data to the external/third-party data processors, the present invention limits the risk associated with the data being breached/comprised, either intentionally or unintentionally, by the external/third-party entity. 
     In specific embodiments of the invention, the data set is segmented into discrete data blocks and each individual data block is communicated/transferred to a different external/third-party entity for subsequent quantum-level data processing. As a result, none of the external/third-party entities have access to the entire data set and, as such, in the event that the data possessed by an external/third-party entity is breached/comprised, the risk posed to the data owner is minimized because the breached/comprised data is only a segment/portion of the entire data set and, as such, may be have limited value in the hands of a wrongdoer. 
     In other embodiments of the invention, the data set and/or the data blocks are obfuscated, such that asymmetrical cryptography or the like is implemented to re-arrange, shift or the like the data elements in the data set and/or data blocks prior to communicating the data sets/segments to the external/third-party entities for quantum-level processing. Once the data set/data blocks have been quantum-level processed and returned to the data owner, the obfuscation is removed/reversed from the data set/data block. 
     In still further embodiments of the invention, the data set and/or data blocks may be injected with “dummy” data (i.e., benign information that does not contain any useful data, but serves to reserve space where real data is nominally present). Insertion of dummy data further prevents breached data from being read/used by a wrongdoer. In specific embodiments of the invention the “dummy” data may be logically programmed (i.e., so-called smart “dummy” data) so that the data owner can forensically discern whether the dummy data has been accessed, read or otherwise manipulated. 
     In additional embodiments of the invention, the various functions of the system are segregated in individual trusted zones, such that processing may occur in a trusted zone absent knowledge of rules that being applied to the processing and/or upstream/downstream processing parameters. For example, data set segmentation, data set re-formation, the rules associated with data segmentation and re-formation and, in some embodiments, the communication/transfer of data sets are segregated in separate trusted zones. In this regard the trusted zones allow for segmentation and reformation rules to be applied without the corresponding segmentation and reformation algorithm being aware of which segmentation/reformation rules are being applied. Additionally, in those embodiments in which the communication/transfer occurs within a separate trusted zone, the data segmentation and re-formation may occur absent knowledge as to which external/third-party entity processed a data segment. 
     A system for determining security measures for a data set requiring quantum-level computing defines first embodiments of the invention. The system includes a distributed computing network configured to communicate data amongst a plurality of computing devices and one or more external entities, each entity controlling one or more of the plurality of computing devices configured for quantum level-computing processing. The system additionally includes a computer platform including a memory and one or more processors in communication with the memory. In addition, the system includes a data set security measure determining module stored in the memory, executable by the one or more processors and configured to receive the data set determined to require quantum-level computing and determine one or more security measures to apply to the data set based at least on a level of confidentiality associated with data in the data set and timing requirements associated with processing the data set. Additionally, the system includes a plurality of security measure modules stored in the memory, executable by the one or more processors and configured to apply security measures to the data set as determined by the data set security measure determining module. In addition, the system includes a data communication module stored in the memory executable by the processor and configured to initiate communication of at least a portion of the data set to one or more external quantum-level processing entities. The external entities are configured to process the data block via the corresponding one or more of the computing devices configured for quantum-level computing processing. Moreover, the system includes a security measure removal module stored in the memory, executable by the one or more processors and configured to, in response to receiving the quantum-level processed data from the one or more external quantum-level processing entities, remove the one or more security measures from the data set. 
     In specific embodiments of the system, the data communication module further comprises an external entity selection sub-module configured to select one of the external entities for quantum-level computing processing of the data set based on predetermined external entity selection rules, wherein the predetermined external entity selection rules are based on one or more of type of data in the data block, external entity quantum-level computing processing capabilities and external entity security capabilities. 
     In still further specific embodiments the system includes a data processing level-determining module stored in the memory, executable by the processor and configured to determine that the data set requires quantum-level computing. 
     In additional specific embodiments of the system, the plurality of security measure modules include a data segmentation module configured to segment the data set into a plurality of data blocks based on predetermined data segmentation rules. In specific embodiments of the system, the data segmentation module is further configured to segment the data set into the plurality of data blocks by at least one of randomly determining which data elements to include in the data blocks and systematically determining which data elements to include in the data blocks based on predetermined tiering criteria. In such embodiments of the system, the data segmentation rules are further configured to determine at least one of a size of each data block, and a sequence for the plurality of data blocks and/or tiering criteria. In further related embodiments of the system, the data communication module further comprises an external entity selection sub-module configured to select, for each data block, one of the external entities for quantum-level computing processing. In other related embodiments of the system, the a security measure removal module is further configured to receive the quantum-level computing processed data blocks from the different external entities and combine the quantum-level computing processed data blocks to re-form the data set be applying re-formation rules. In still related specific embodiments of the system, the data segmentation rules and data re-formation rules are stored in a first trusted computing zone, the data segmentation module is stored in a second trusted computing zone and the security measure removal module is stored in a third trusted computing zone. 
     In other specific embodiments of the system, the plurality of security measure modules include a data obfuscation module configured to perform at least one of rearranging or shifting data elements in the data set. 
     While in still further specific embodiments of the system, the plurality of security measure modules include a dummy data module configured to generate dummy data and insert the dummy data into the data set. In related embodiments of the system, the dummy data module is further configured to generate the dummy data as logically programmed dummy data configured to record information associated with accessing the dummy data or attempting to access the dummy data. 
     In other specific embodiments the system includes a forensic analysis module stored in the memory, executable by the processor and configured to analyze the received quantum-level computing processed data blocks to determine whether the data blocks have been accessed or read in an unauthorized manner. 
     A method for external processing of a data set requiring quantum-level computing defines second embodiments of the invention. The method includes receiving the data set requiring quantum-level computing processing and determining one or more security measures to apply to the data set based at least on a level of confidentiality associated with data in the data set and timing requirements associated with processing the data set. The method further includes applying, by a computing device processor, the one or more security measures to the data set and, in response to applying the one or more security measures to the data set, electronically communicating at least a portion of the data set to one or more external quantum-level processing entities. In addition, the method includes, in response to receiving the quantum-level processed data from the one or more external quantum-level processing entities, removing the one or more security measures from the data set. 
     In specific embodiments of the method, determining one or more security measures further includes determining a segmentation scheme for segmenting the data set into a plurality of data blocks. The segmentation scheme comprises size of data blocks and sequencing of data blocks. In related embodiments the method may further include determining an external entity capable of quantum-level computing processing for each of the data blocks. The determination is based at least one or more of type of data in the data block, external entity quantum-level computing processing capabilities and external entity security capabilities. 
     In other specific embodiments of the method, determining one or more security measures further includes determining, based on obfuscation rules, an obfuscation scheme for rearranging or shifting the data in the data set. 
     In still further specific embodiments of the method, determining one or more security measures further includes determining a dummy data insertion scheme for inserting dummy data into the data set. 
     A computer program product including a non-transitory computer-readable medium defines third embodiments of the invention. The computer-readable medium includes a first set of codes for causing a computer to receive a data set requiring quantum-level computing processing and a second set of codes for causing a computer to determine one or more security measures to apply to the data set based at least on a level of confidentiality associated with data in the data set and timing requirements associated with processing the data set. The computer-readable medium additionally includes a third set of codes for causing a computer to apply the one or more security measures to the data set and a fourth set of codes for causing a computer to, in response to applying the one or more security measures to the data set, electronically communicate at least a portion of the data set to one or more external quantum-level processing entities. Moreover, the computer-readable medium includes a fifth set of codes for causing a computer to, in response to receiving the quantum-level processed data from the one or more external quantum-level processing entities, remove the one or more security measures from the data set. 
     In specific embodiments of the computer program product, the second set of codes is further configured to cause the computer to determine the one or more security measures, wherein the one or more security measures include (i) segmenting the data set into data blocks, (ii) obfuscating the data to rearrange or shift data elements within the data set or the data blocks, and (iii) generating and inserting dummy data within the data set or the data blocks. 
     Thus, systems, apparatus, methods, and computer program products herein described in detail below provide for determining and applying security measures, such as segmentation, obfuscation and/or insertion of dummy data, to data sets determined to require external quantum-level computing processing. The security measures herein described and implemented lessens the risk associated with the data being breached/comprised at the external entity. 
     The features, functions, and advantages that have been discussed may be achieved independently in various embodiments of the present invention or may be combined with yet other embodiments, further details of which can be seen with reference to the following description and drawings. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
       Having thus described embodiments of the invention in general terms, reference will now be made the accompanying drawings, wherein: 
         FIG. 1  provides a schematic diagram of an exemplary system for implementing security measures for data sets requiring external quantum-level computing processing, in accordance with embodiments of the present invention; 
         FIG. 2  provides a block diagram of a quantum optimizer apparatus, in accordance with embodiments of the present invention; 
         FIG. 3  provides a block diagram of a system for implementing data segmentation for data sets requiring external quantum-level computing processing, in accordance with embodiments of the present invention; 
         FIG. 4  provides a block diagram of a system for determining and implementing security measures for a data set requiring external quantum-level computing processing, in accordance with embodiments of the present invention; 
         FIG. 5  provides a schematic diagram of system for implementing data segmentation in a trusted zone environment, in accordance with embodiments of the present invention; 
         FIG. 6  provides a flow diagram of a method for implementing data segmentation for data sets requiring external quantum-level computing processing, in accordance with embodiments of the present invention; and 
         FIG. 7  provides a flow diagram of a method for determining and implementing security features for a data set requiring external quantum-level computing processing, in accordance with embodiments of the present invention. 
     
    
    
     DETAILED DESCRIPTION OF EMBODIMENTS OF THE INVENTION 
     Embodiments of the present invention will now be described more fully hereinafter with reference to the accompanying drawings, in which some, but not all, embodiments of the invention are shown. Indeed, the invention may be embodied in many different forms and should not be construed as limited to the embodiments set forth herein; rather, these embodiments are provided so that this disclosure will satisfy applicable legal requirements. Like numbers refer to like elements throughout. 
     As will be appreciated by one of skill in the art in view of this disclosure, the present invention may be embodied as an apparatus (e.g., a system, computer program product, and/or other device), a method, or a combination of the foregoing. Accordingly, embodiments of the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment (including firmware, resident software, micro-code, etc.), or an embodiment combining software and hardware aspects that may generally be referred to herein as a “system.” Furthermore, embodiments of the present invention may take the form of a computer program product comprising a computer-usable storage medium having computer-usable program code/computer-readable instructions embodied in the medium. 
     Any suitable computer-usable or computer-readable medium may be utilized. The computer usable or computer-readable medium may be, for example but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device. More specific examples (e.g., a non-exhaustive list) of the computer-readable medium would include the following: an electrical connection having one or more wires; a tangible medium such as a portable computer diskette, a hard disk, a time-dependent access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or Flash memory), a compact disc read-only memory (CD-ROM), or other tangible optical or magnetic storage device. 
     Computer program code/computer-readable instructions for carrying out operations of embodiments of the present invention may be written in an object oriented, scripted or unscripted programming language such as JAVA, PERL, SMALLTALK, C++ or the like. However, the computer program code/computer-readable instructions for carrying out operations of the invention may also be written in conventional procedural programming languages, such as the “C” programming language or similar programming languages. 
     Embodiments of the present invention are described below with reference to flowchart illustrations and/or block diagrams of methods or apparatuses (the term “apparatus” including systems and computer program products). It will be understood that each block of the flowchart illustrations and/or block diagrams, and combinations of blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, or other programmable data processing apparatus to produce a particular machine, such that the instructions, which execute by the processor of the computer or other programmable data processing apparatus, create mechanisms for implementing the functions/acts specified in the flowchart and/or block diagram block or blocks. 
     These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instructions, which implement the function/act specified in the flowchart and/or block diagram block or blocks. 
     The computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions, which execute on the computer or other programmable apparatus, provide steps for implementing the functions/acts specified in the flowchart and/or block diagram block or blocks. Alternatively, computer program implemented steps or acts may be combined with operator or human implemented steps or acts in order to carry out an embodiment of the invention. 
     Thus, as described in more detail below, the present invention applies security measures to data sets requiring external/third-party quantum-level processing. By providing such security measures to the data sets prior to communicating/transferring the data to the external/third-party data processors, the present invention limits, if not eliminates, the risk associated with the data being breached/comprised, either intentionally or unintentionally, by the external/third-party entity. 
     In specific embodiments of the invention, the security measures that are applied to the data set are determined based on at least one of the sensitivity/confidentiality of the data set and the timing requirements for processing the data (e.g., whether the data set requires immediate/real-time processing or whether the data set can be processed in due course). The security measures may include, but are not limited to, (i) segmenting the data such that a different external entity is assigned to each segment, (ii) obfuscating the data set or data segment by rearranging the data elements, and (iii) inserting dummy data into the data set or data segment. 
     Accordingly, in specific embodiments of the invention, the data set may be segmented into discrete random or systematic (based on tiering criteria) data blocks with each individual data block being communicated/transferred to a different external/third-party entity for subsequent quantum-level data processing. As a result, none of the external/third-party entities have access to the entire data set and, as such, in the event that the data possessed by external/third-party entity is breached/comprised, the risk posed to the data owner is minimized. 
     In other embodiments of the invention, the data set and/or the data blocks are obfuscated, such that asymmetrical cryptography or the like is implemented to re-arrange/shift the data in the data set and/or data blocks prior to communicating/transferring the data sets/segments to the external/third-party entities for quantum-level processing. Once the data set/data blocks have been quantum-level processed and returned to the data owner, the obfuscation is removed from the data set/data block. 
     In still further embodiments of the invention, the data set and/or data blocks may be injected with “dummy” data (i.e., benign information that does not contain any useful data, but serves to reserve space where real data is nominally present). Insertion of dummy data further prevents breached data from being read/used by a wrongdoer. In specific embodiments of the invention the “dummy” data may be logically programmed (i.e., so-called smart “dummy” data) so that the data owner can discern whether the dummy data has been accessed, read or otherwise manipulated. 
     In additional embodiments of the invention, the various functions of the system are segregated in different trusted zones and, as such, processing occurs in a silo-like fashion without the processing module being cognizant of rules that are being applied and/or upstream and downstream processing parameters. For example, in specific embodiments of the invention, data set segmentation, data set re-formation, the rules associated with data segmentation and re-formation and, in some embodiments, the communication/transfer of data sets are segregated in separate trusted zones. Trusted zones allow for segmentation and reformation rules to be applied without the corresponding segmentation and reformation algorithm being aware of which segmentation/reformation rules are being applied. Additionally, in those embodiments in which the communication/transfer occurs within a separate trusted zone, the data segmentation and re-formation may occur absent knowledge as to which external/third-party entity processed a data block. 
     Referring to  FIG. 1 , a schematic diagram is provided of a system  100  for implementing data segmentation for a data sets requiring external/third-party entity quantum-level computing processing, in accordance with embodiments of the present invention. The system  100  is implemented in a distributed communication environment via computing network  200 , which typically comprises the Internet and may include various sub-nets and/or intranets. System  100  includes system  300  which may comprise one or more computing devices. System  300  includes a computing platform  302  having a memory  304  and one or more processors  306  in communication with the memory. The memory  304  stores data segmentation module  310  that is executable by processor(s)  306  and configured to receive a data set  312  that has been determined to require quantum-level processing and segment the data set  312  into a plurality of data blocks by applying segmentation rules. 
     The memory  304  additionally stores data block communication module  320  that is executable by the processor(s)  306  and configured to select, for each data block  312 , an external entity  322 - 1 ,  322 - 2 ,  322 - 3  for quantum-level computing processing of the data block  312  and initiate communication, via distributed communication network  200 , of the data blocks  312  to the corresponding selected external entity  322 - 1 ,  322 - 2 ,  322 - 3  or the like. 
     The external entities  322 - 1 ,  322 - 2 ,  322 - 3  include a quantum computing apparatus  700 - 1 ,  700 - 2 ,  700 - 3  or the like configured to provide quantum-level computing. As used herein, a quantum computing apparatus  700 - 1 ,  700 - 2 ,  700 - 3  or the like is any computer that utilizes the principles of quantum physics to perform computational operations. Several variations of quantum computer design are known, including photonic quantum computing, superconducting quantum computing, nuclear magnetic resonance quantum computing, and/or ion-trap quantum computing. Regardless of the particular type of quantum computing apparatus implementation, all quantum computers encode data onto qubits. Whereas classical computers encode bits into ones and zeros, quantum computers encode data by placing a qubit into one of two identifiable quantum states. Unlike conventional bits, however, qubits exhibit quantum behavior, allowing the quantum computer to process a vast number of calculations simultaneously. 
     A qubit can be formed by any two-state quantum mechanical system. For example, in some embodiments, a qubit may be the polarization of a single photon or the spin of an electron. Qubits are subject to quantum phenomena that cause them to behave much differently than classical bits. Quantum phenomena include superposition, entanglement, tunneling, superconductivity, and the like. 
     Two quantum phenomena are especially important to the behavior of qubits in a quantum computing apparatus: superposition and entanglement. Superposition refers to the ability of a quantum particle to be in multiple states at the same time. Entanglement refers to the correlation between two quantum particles that forces the particles to behave in the same way even if they are separated by great distances. Together, these two principles allow a quantum computer to process a vast number of calculations simultaneously. 
     In a quantum computer with n qubits, the quantum computer can be in a superposition of up to 2 n  states simultaneously. By comparison, a classical computer can only be in one of the 2 n  states at a single time. As such, a quantum computer can perform vastly more calculations in a given time period than its classical counterpart. For example, a quantum computer with two qubits can store the information of four classical bits. This is because the two qubits will be a superposition of all four possible combinations of two classical bits (00, 01, 10, or 11). Similarly, a three qubit system can store the information of eight classical bits, four qubits can store the information of sixteen classical bits, and so on. A quantum computer with three hundred qubits could possess the processing power equivalent to the number of atoms in the known universe. 
     Quantum computing apparatus  700 - 1 ,  700 - 2 ,  700 - 3  and the like can outperform classical computers in a specialized set of computational problems. Principally, quantum computers have demonstrated superiority in solving optimization problems. Generally speaking, the term “optimization problem” as used throughout this application describe a problem of finding the best solution from a set of all feasible solutions. In accordance with some embodiments of the present invention, quantum computing apparatus  700 - 1 ,  700 - 2 ,  700 - 3  as described herein are designed to perform adiabatic quantum computation and/or quantum annealing. Quantum computers designed to perform adiabatic quantum computation and/or quantum annealing are able to solve optimization problems as contemplated herein in real time or near real time. 
     Embodiments of the present invention make use of quantum ability of optimization by utilizing a quantum computing apparatus in conjunction with a classical/binary computer. Such a configuration enables the present invention to take advantage of quantum speedup in solving optimization problems, while avoiding the drawbacks and difficulty of implementing quantum computing to perform non-optimization calculations. Examples of quantum computing apparatus  700 - 1 ,  700 - 2 ,  700 - 3  that can be used to solve optimization problems parallel to a classic system are described in, for example, U.S. Pat. No. 9,400,499, 9,207,672, each of which is incorporated herein by reference in its entirety. 
       FIG. 2  is a block diagram of an exemplary quantum optimizer  710  that can be used in parallel with a classical computer to solve optimization problems. The quantum Optimizer  710  is comprised of a data extraction subsystem  706 , a quantum computing subsystem  702 , and an action subsystem  704 . As used herein, the term “subsystem” generally refers to components, modules, hardware, software, communication links, and the like of particular components of the system. Subsystems as contemplated in embodiments of the present invention are configured to perform tasks within the system as a whole. 
     As depicted in  FIG. 2 , the data extraction subsystem  706  communicates with the network to extract data for optimization. It will be understood that any method of communication between the data extraction subsystem  706  and the network is sufficient, including but not limited to wired communication, Radiofrequency (RF) communication, BLUETOOTH®, WIFI®, and the like. The data extraction subsystem  706  then formats the data for optimization in the quantum computing subsystem  702 . 
     As further depicted in  FIG. 2 , the quantum computing subsystem  702  comprises a quantum computing infrastructure  714 , a quantum memory  712 , and a quantum processor  710 . The quantum computing infrastructure  702  comprises physical components for housing the quantum processor  710  and the quantum memory  712 . The quantum computer infrastructure further comprises a cryogenic refrigeration system to keep the quantum computing subsystem  702  at the desired operating temperatures. In general, the quantum processor  710  is designed to perform adiabatic quantum computation and/or quantum annealing to optimize data received from the data extraction subsystem  706 . The quantum memory  712  is comprised of a plurality of qubits used for storing data during operation of the quantum computing subsystem  704 . In general, qubits are any two-state quantum mechanical system. It will be understood that the quantum memory  712  may be comprised of any such two-state quantum mechanical system, such as the polarization of a single photon, the spin of an electron, and the like. 
     The action subsystem  704  communicates the optimized data from the quantum computing subsystem  702  over the network. It will be understood that any method of communication between the data extraction subsystem  706  and the network is sufficient, including but not limited to wired communication, Radiofrequency (RF) communication, BLUETOOTH®, WIFI®, and the like. 
     Returning to  FIG. 1 , memory  304  of system  300  additionally stores data re-formation module  330  that is executable by the processor(s)  306  and configured to receive the data blocks  314  processed by the external entities  322 - 1 ,  322 - 2 ,  322 - 3  and the like implementing the quantum computing apparatus  700 - 1 ,  700 - 2 ,  700 - 3  and the like described above and combine the data blocks  314  to re-form the data set  312  by applying re-formation rules. 
     Referring to  FIG. 3  a block diagram is presented of a system  300 , which is configured for segmenting data sets into data blocks for subsequent external quantum-level computing processing, in accordance with embodiments of the present invention. In addition to providing greater detail,  FIG. 3  highlights various alternate embodiments of the invention. The system  300  may include one or more of any type of computing device, such as one or more servers, personal computers or the like. The present systems and methods can accordingly be performed on any form of one or more computing devices. 
     The system  300  includes a computing platform  302  that can receive and execute algorithms, such as routines, and applications. Computing platform  302  includes memory  304 , which may comprise volatile and non-volatile memory, such as read-only and/or random-access memory (RAM and ROM), EPROM, EEPROM, flash cards, or any memory common to computer platforms. Further, memory  304  may include one or more flash memory cells, or may be any secondary or tertiary storage device, such as magnetic media, optical media, tape, or soft or hard disk. Moreover, memory  304  may comprise cloud storage, such as provided by a cloud storage service and/or a cloud connection service. 
     Further, computing platform  302  also includes one or more processors  306 , which may be an application-specific integrated circuit (“ASIC”), or other chipset, processor, logic circuit, or other data processing device. Processors  306  or other processor such as ASIC may execute an application programming interface (“API”)  308  that interfaces with any resident programs, such as data processing-level determining module  340 , data segmentation module  310 , data block security module  350 , data block communication module  320 , data block forensic analysis module  380  and data set reformation module  330  and routines, sub-modules associated therewith or the like stored in the memory  304  of the system  300 . 
     Processor  306  includes various processing subsystems (not shown in  FIG. 3 ) embodied in hardware, firmware, software, and combinations thereof, that enable the functionality of system  300  and the operability of the system  300  on a network. For example, processing subsystems allow for initiating and maintaining communications and exchanging data with other networked devices, such as those quantum-level computing apparatus  700 - 1 ,  700 - 2 ,  700 - 3  shown in  FIG. 1 . For the disclosed aspects, processing subsystems of processor  306  may include any subsystem used in conjunction with data processing-level determining module  340 , data segmentation module  310 , data block security module  350 , data block communication module  320 , data block forensic analysis module  380  and data set reformation module  330  and related algorithms, sub-algorithms, modules, sub-modules thereof. 
     Computer platform  302  may additionally include communications module (not shown in  FIG. 3 ) embodied in hardware, firmware, software, and combinations thereof, that enables communications among the various components of the system  300 , as well as between the other networked devices. Thus, communication module may include the requisite hardware, firmware, software and/or combinations thereof for establishing and maintaining a network communication connection. 
     In specific embodiments of the system  300 , the memory  304  stores data processing-level determining module  340  that is configured to determine the level of processing required of the data set. The level of processing may include, but is not limited to, quantum-level computing  342  and conventional binary-level computing  344 . In specific embodiments of the invention, the determination of the level of processing may include a combination of quantum-level computing  342  and binary-level computing  344 . In such embodiments of the invention, the data processing-level determining module  340  may determine which processing is to be performed by the quantum-level computing  342  and which processing is to be performed by conventional binary-level computing  344 . The data processing-level determining module  340  is configured to determine the level of processing required based on the complexity of the computations, the accuracy required of the computations, processing time requirements and the like. 
     Further the memory  304  of system  300  stores data segmentation module  310  that is configured to receive a data set  312  that have been determined to require quantum-level computing processing and segment the data set  312  into a plurality of data blocks  314  by applying predetermined segmentation rules  316 . The minimum quantity of data blocks  314  may be based on the quantity of external entities  322  that the data owner has engaged in quantum-level computing processing. Segmentation rules  316  may be defined that determine the size  317  of the data block  314  (e.g., defined by a unit of memory size or quantity of data elements) and or the sequence/order  318  of data blocks  314  and/or the tiering/slicing criteria  319  (discussed, infra.). The size of the data blocks may be uniform or variable. The size of variable sized data blocks  314  may be based on the quantum-level computing capabilities of the external entity that is selected or will be selected to process the data block. In other embodiments of the invention, the size of variable sized may be random subject to a minimum size requirement. The sequencing/order  318  of the data blocks provides for the data blocks to include a sequence/order identifier, which is needed to subsequently reform the data set  312 . 
     In specific embodiments of the system, the data segmentation module  310  is configured to randomly determine (through application of “horizontal” analytics) which data from the data set  312  to include in the data blocks  316  (i.e., so-called “chopping” or “blocking” of the data set  312 ). 
     In other embodiments of the system, the data segmentation module  310  is configured to systematically determine (through application of “vertical” analytics which data from the data set in include in the data blocks  316 . In such embodiments, predetermined rules  316  define criteria/requirements  319  as to which data from the data set  312  to include in the data blocks  316  (i.e., so-called “slicing” or “tiering” of the data set  312 ). The criteria  319  may be based on any classification or attribute associated with data elements in the data set  312 . For example, in those embodiments in which the data set  312  includes data elements associated with individuals, attributes associated with the individuals, (e.g., duration of life range, gender, region of physical location or the like) may be used to slice or tier the data set  312  into tiers/slices of data (collectively, referred to herein as data block  316 ). In such embodiments of the invention, each tier/slice of the data set  312  may be subsequently communicated to different external entities for quantum-level computing processing. It should be noted that multiple tiers of data may be employed in the segmentation of the data set  312 . For example, the entire data set  312  may first be segmented into first tiers based on duration of life groups of the individuals associated with data elements, and subsequently one or more of the first tier segments may be segmented into second tiers based on the gender of the individuals associated with the data elements and so on. In specific embodiments of the system each of the tiered segments may be designated for a specific one of the plurality of different external entities for subsequent quantum-level computing processing. 
     In other embodiments of the system, the data segmentation module  310  is configured to use both random chopping/blocking of the data set  312  and systematic slicing/tiering of the data set  312  to form the data blocks  316 . In such embodiments of the system, random chopping/blocking of the data set  312  may occur first, followed by one or more instances of systematic slicing/tiering of the data set  312  based on predetermined tiering criteria. While in other embodiments of the system, the data set  312  may be systematically sliced/tiered first, followed by one or more instances of randomly chopping/blocking the data set  312 . In this regard, random chopping/blocking of the data set  312  (i.e., horizontal analytics) and systematic slicing/tiering of the data set  312  (i.e., vertical analytics) may be applied to the data set in any order and/or in any number of instances. 
     Memory  304  of system  300  additionally includes data block security module  350  that is configured to provide additional security measures to data blocks  314  based on predetermined security rules  360 . Security rules  360  may be based on the data sensitivity  362  (i.e., more sensitive data may provide for heightened security measures), timing requirements  364  for processing the data (i.e., immediate/real-time processing requirements may dictate less security measures, while processing with minimal or no time requirements may provide for more/full security measures) and external entity security capabilities  366  (i.e., less security capabilities at the external entity may dictate more/full security measures, while more security measures at the external entity may provide for less security measures). 
     The data block security module  350  may include obfuscation sub-module  352  that is configured to re-arrange or otherwise shift data elements within a data block  314 . It should be noted that the obfuscation scheme applied to the data blocks  314  may vary by data block, such that one data block may be subject to a first obfuscation scheme, while a second data block may be subject to a second obfuscation scheme different than the first obfuscation scheme. For example, a first obfuscation scheme may provide for shifting certain data elements horizontally to the left by a certain number of columns, while a second obfuscation scheme may provide for shifting certain data elements vertically upward by a certain number of rows. Moreover, while examples herein provide for shifting of data elements, other obfuscation schemes may be implemented that rearrange data elements by other means. 
     In further embodiments of the system, data security module  350  may include dummy data sub-module  354  that is configured to insert “dummy” data in the data block. Dummy data as used herein is benign information that does not contain any useful data, but serves to reserve space where real data is nominally present. Dummy data serves to make the data block less comprehensible in the event that the data block is compromised (i.e., unauthorized access or use of the data). In specific embodiments of the invention the dummy data may be logically programmed (i.e., so-called smart “dummy” data  356 ) to record or otherwise detect accessing (or attempted accessing/reading) of the dummy data. In this regard, the owner of the data may be able to subsequently detect unauthorized accessing of the data block or an attempt to access the data at the external entity. 
     The memory  304  of system  300  additionally includes data block communication module  320  that is configured to select an external entity  322  for each of the plurality of data blocks  314  based on external entity selection rules  370  and initiate communication of the data block  314  to the selected external entity  322 . Any one external entity may be selected to process one or more of the data blocks  314 . The external entity selection rules  370  may be based on data sensitivity  372 , security capabilities  374  of the external entity, processing capability  376  of the external entity, including processing turnaround times and the like. 
     Additionally, system  300  may store data block forensic analysis module  380  that is configured to forensically analyze data blocks  314  once the data blocks  314  have been quantum-level computing processed by the external entities  322  and communicated back to the system  300 . Forensic analysis provides for analyzing the data block to determine if the data has been accessed, read or otherwise used in an unauthorized manner. In those embodiments of the invention, in which the data blocks  314  include smart “dummy” data  356 , the forensic analysis may include obtaining recorded information associated with the smart “dummy’ data  356  that indicated accessing or an attempted access of the dummy data. 
     Further, system  300  stores data re-formation module  300  that is configured to combine the data blocks  314  to re-form the data set in accordance with data re-formation rules  332 . The data re-formation rules may be data block or data set specific and take into account the type of data segmentation implemented by the data segmentation module  310  and the security measures applied by the data block security module  350 . In this regard, the data reformation module  300  may be configured to remove security measures from the data blocks  314  (or in some embodiments, after the data set  312  has been re-formed), such as, but not limited to, removing previously applied obfuscation and/or dummy data. 
     Referring to  FIG. 4  a block diagram is presented of a system  400 , which is configured for determining security measures for a data set determined to require external quantum-level computing processing, in accordance with embodiments of the present invention. In addition to providing greater detail,  FIG. 4  highlights various alternate embodiments of the invention. The system  400  may include one or more of any type of computing device, such as one or more servers, personal computers or the like. The present systems and methods can accordingly be performed on any form of one or more computing devices. 
     The system  400  includes a computing platform  402  that can receive and execute algorithms, such as routines, and applications. Computing platform  402  includes memory  404 , which may comprise volatile and non-volatile memory, such as read-only and/or random-access memory (RAM and ROM), EPROM, EEPROM, flash cards, or any memory common to computer platforms. Further, memory  404  may include one or more flash memory cells, or may be any secondary or tertiary storage device, such as magnetic media, optical media, tape, or soft or hard disk. Moreover, memory  404  may comprise cloud storage, such as provided by a cloud storage service and/or a cloud connection service. 
     Further, computing platform  402  also includes one or more processors  406 , which may be an application-specific integrated circuit (“ASIC”), or other chipset, processor, logic circuit, or other data processing device. Processors  406  or other processor such as ASIC may execute an application programming interface (“API”)  408  that interfaces with any resident programs, such as data and routines, sub-modules associated therewith or the like stored in the memory  404  of the system  400 . 
     Processor  406  includes various processing subsystems (not shown in  FIG. 3 ) embodied in hardware, firmware, software, and combinations thereof, that enable the functionality of system  400  and the operability of the system  400  on a network. For example, processing subsystems allow for initiating and maintaining communications and exchanging data with other networked devices, such as those quantum-level computing apparatus  700 - 1 ,  700 - 2 ,  700 - 3  shown in  FIG. 1 . For the disclosed aspects, processing subsystems of processor  406  may include any subsystem used in conjunction with data processing-level determining module  340  data set security measure determining module  410 , data segmentation module  430 , obfuscation module  440 , dummy data module  450 , data block communication module  460 , forensic analysis module  480  and security measure removal module  490  and related algorithms, sub-algorithms, modules, sub-modules thereof. 
     Computer platform  402  may additionally include communications module (not shown in  FIG. 4 ) embodied in hardware, firmware, software, and combinations thereof, that enables communications among the various components of the system  400 , as well as between the other networked devices. Thus, communication module may include the requisite hardware, firmware, software and/or combinations thereof for establishing and maintaining a network communication connection. 
     In specific embodiments of the system  400 , the memory  404  stores data processing-level determining module  340  that is configured to determine the level of processing required of the data set. The level of processing may include, but is not limited to, quantum-level computing  342  and conventional binary-level computing  344 . In specific embodiments of the invention, the determination of the level of processing may include a combination of quantum-level computing  342  and binary-level computing  344 . In such embodiments of the invention, the data processing-level determining module  340  may determine which processing is to be performed by the quantum-level computing  342  and which processing is to be performed by conventional binary-level computing  344 . The data processing-level determining module  340  is configured to determine the level of processing required based on the complexity of the computations, the accuracy required of the computations, processing time requirements and the like. 
     Further the memory  404  of system  400  stores data set security measure determining module  410  that is configured to determining which security measures  420  should be applied to a data set requiring external entity quantum-level computing processing. The determination as to which security measures should be applied may be based on the sensitivity  412  of the data in the data set  312  (i.e., more sensitive data may provide for more/full security measures, while less sensitive data may provide for less security measures or less complex/intrusive security measures), the processing time requirements of the data set (i.e., immediate/real-time processing may provide for less security measures or less complex/intrusive security measures, while processing with minimal or no processing time requirements may provide for more/full security measures). The security measures  420  that may be determined and applied may include, but are not limited to, data segmentation, data obfuscation, insertion of “dummy’ data and the like. 
     As such, system  400  stores data segmentation module  430  that is configured to receive a data set  312  that have been determined to require quantum-level computing processing and segment the data set  312  into a plurality of data blocks  314  by applying predetermined segmentation rules  432 . The minimum quantity of data blocks  314  may be based on the quantity of external entities  322  that the data owner has engaged in quantum-level computing processing. Segmentation rules  432  may be defined that determine the size  434  of the data block  314  (e.g., defined by a unit of memory size or quantity of data elements) and or the sequence/order  436  of data blocks  314  and/or the tiering/slicing criteria  438 . The size of the data blocks may be uniform or variable. The size of variable sized data blocks  314  may be based on the quantum-level computing capabilities of the external entity that is selected or will be selected to process the data block. In other embodiments of the invention, the size of variable sized may be random subject to a minimum size requirement. The sequencing/order  436  of the data blocks provides for the data blocks to include a sequence/order identifier, which is needed to subsequently reform the data set  312 . 
     As previously noted, in specific embodiments of the system, the data segmentation module  430  may be configured to randomly determine (through application of “horizontal” analytics) which data from the data set  312  to include in the data blocks  316  (i.e., so-called “chopping” or “blocking” of the data set  312 ) and/or systematically determine (through application of “vertical” analytics which data from the data set in include in the data blocks  316 . In such embodiments, predetermined rules  316  may define criteria/requirements  438  as to which data from the data set  312  to include in the data blocks  316  (i.e., so-called “slicing” or “tiering” of the data set  312 ). The tiering criteria  438  may be based on any classification or attribute associated with data elements in the data set  312 . In such embodiments of the invention, each random block of the data set  312  and/or tier/slice of the data set  312  (each collectively referred to herein as data block  316 ) may be subsequently communicated to different external entities for quantum-level computing processing. It should be noted that multiple tiers of data may be employed in the segmentation of the data set  312  and/or combinations of random chopping/blocking of the data set  312  and systematic slicing/tiering of the data set  312  may be used in unison to form the data blocks  316 . In such embodiments, random chopping/blocking of the data set  312  (i.e., horizontal analytics) and systematic slicing/tiering of the data set  312  (i.e., vertical analytics) may be applied to the data set in any order and/or in any number of instances. 
     Security measures/features  420  additionally includes obfuscation module  440  that is configured to re-arrange or otherwise shift data elements within the data set  312  or data block  314 . It should be noted that the obfuscation scheme applied to the data set  312  or data blocks  314  may vary by within the data  312  or by data block  314 , such that one section of a data set  312  or a data block  314  may be subject to a first obfuscation scheme, while a second section of the data set  312  or second data block  314  may be subject to a second obfuscation scheme different than the first obfuscation scheme. For example, a first obfuscation scheme may provide for shifting certain data elements horizontally to the left by a certain number of columns, while a second obfuscation scheme may provide for shifting certain data elements vertically upward by a certain number of rows. Moreover, while examples herein provide for shifting of data elements, other obfuscation schemes may be implemented that rearrange data elements by other means. 
     In further embodiments of the system  400 , security measures/features  420  may include dummy data module  450  that is configured to insert “dummy” data in the data set  312  or data block  314 . In specific embodiments of the invention the dummy data may be logically programmed (i.e., so-called smart “dummy” data  356 ) to record or otherwise detect accessing (or attempted accessing/reading) of the dummy data. In this regard, the owner of the data may be able to subsequently detect unauthorized accessing of the data block or an attempt to access the data at the external entity. 
     The memory  404  of system  400  additionally includes data block communication module  320  that is configured to select an external entity  464  for the data set  312  or for each of the plurality of data blocks  314  based on external entity selection rules  370  and initiate communication of the data block  314  to the selected external entity  464 . In those embodiments in which the data set  312  is not subjected to segmentation, a single external entity  464  is selected for quantum-level processing of the entire data set  312 . In those embodiments in which the data set is subjected to data segmentation, each of the data blocks  314  are assigned to one of the plurality of external entities  464 , such that the entire data  312  is not processed by a single external entity  464 . In this regard, any one external entity may be selected to process one or more of the data blocks  314 . The external entity selection rules  470  may be based on data sensitivity  472 , security capabilities  474  of the external entity, processing capability  476  of the external entity, including processing turnaround times and the like. 
     Additionally, system  400  may store data block forensic analysis module  480  that is configured to forensically analyze the data set  312  or data blocks  314  once the data set  312  or data blocks  314  have been quantum-level computing processed by the external entities  322  and communicated back to the system  400 . Forensic analysis provides for analyzing the data set  312  or data block  314  to determine if the data has been accessed, read or otherwise used in an unauthorized manner. In those embodiments of the invention, in which the data set  312  or data blocks  314  include smart “dummy” data  452 , the forensic analysis may include obtaining recorded information associated with the smart “dummy’ data  452  that indicated accessing or an attempted access of the dummy data. 
     Further, system  300  stores security removal module  490  that is configured to remove or reverse the previously applied security measures from the data set  312  or data blocks  314  based on security removal rules  492 . In specific embodiments of the invention, in which the data set  312  was previously segmented into data blocks  314 , the security removal module  490  is configured to combine the data blocks  314  to re-form the data set  312  in accordance with data re-formation rules  332 . In other embodiments of the invention, in which obfuscation or dummy data was previously applied to the data set  312  or data blocks  314 , the security removal module  490  is configured to remove previously applied obfuscation and/or dummy data. The data re-formation rules may be data block or data set specific and take into account the type of data segmentation implemented by the data segmentation module  310  and the security measures  420  applied. 
     Referring to  FIG. 5  a schematic diagram is provided of system  100  in which the various functions and modules of the system  100  are segregated in separate trust zones, in accordance with embodiments of the present invention. Specifically, data segmentation module  310  is disposed in a first trusted zone  800 - 1 , segmentation and reformation rules  316  and  322  are disposed in a second trusted zone  800 - 2 , data block communication module  320  is disposed in a third trusted zone  800 - 3  and data re-formation module  330  is disposed in fourth trusted zone  800 - 4 . While  FIG. 5  depicts the trusted zones  800 - 1 ,  800 - 2 ,  800 - 3  and  800 - 4  as being embodied in separate apparatus/devices and in communication via distributed communication network  210 , such as an intranet or the like, in other embodiments of the invention two or more of the trusted zones  800 - 1 ,  800 - 2 ,  800 - 3  and  800 - 4  may be embodied in the same physical apparatus/device. 
     A trusted zone, otherwise referred to as a security zone are logical entities to which one or more interfaces are bound and serve as the building block for apply policies. Trusted zones provide a means to distinguish groups of hosts (servers or the likes) and their resources from one another in order to apply different security policies/measures to the hosts and their resources. In this regard, trusted zones have active security policies that enforce rules for the transit traffic, in terms of what traffic can be communicated through the firewall and the actions needed to take place when the traffic is communicated through the firewall. Further, trusted zones employ screens that allow or deny all connection attempts that require passage from one trusted zone to another. Thus, for every trusted zone, a predefined set of screen options can be set to detect and block various kinds of communication that the device determines to be potentially harmful. In addition, trusted zones include IP address books to identify members so that security policies can be applied to the trusted zone. 
     In accordance with embodiments of the present invention trusted zones allow for the data segmentation module  310  and the data reformation module  330  to access and implement the segmentation rules  316  and re-formation rules  332  absent knowledge as to which segmentation rules  316  or re-formation rules  332  are being applied to a give segmentation or re-formation instance. As a result a further layer of security is realized, in that, a user gaining access to the data segmentation module  310  via the first trusted zone  800 - 1  or the data re-formation module  330  via the fourth trusted zone  800 - 4  is unable to recreate the data segmentation scheme or the data re-formation scheme since the rules applied to segmentation and reformation are disposed in a separate trusted zone  800 - 2 . 
     In addition, in those embodiments of the invention in which the data clock communication module  320  is disposed in a separate trusted zone, such as third trusted zone  800 - 3 , segmentation and re-formation may be performed absent knowledge of which external entity performed the quantum-level processing on the associated data block(s). 
     Referring to  FIG. 6  a flow diagram is depicted of a method  500  for segmenting data sets for subsequent external entity quantum-level computing, in accordance with embodiments of the present invention. At Event  502 , a data set is determined to require quantum-level computing processing, in addition to or in lieu of conventional binary-level computing processing. The determination may be based on the complexity of the computation required, the accuracy required of the computation and/or the time allotted for completing the processing and/or other factors. 
     At Event  504 , the data set determined to require quantum-level computing processing is segmented into a plurality of data blocks according to data segmentation rules. The data blocks may be generated to include random data elements (so-called horizontal analytics) and/or the data blocks may be generated through a systematic tiering/slicing of data approach (so-called vertical analytics) to include data elements that meet predetermined criteria associated with the data elements. The data segmentation rules may define the size, in terms of memory storage or data elements, of the data blocks, which may be uniform or variable and/or the sequencing/order of the data blocks and/or the tiering/slicing criteria 
     At Event  506 , other security measures/features may be applied to the data blocks bases on security measure rules. The other security measures may include, but are not limited to, obfuscation (i.e., rearranging or shifting of data elements within the data block) or insertion of dummy data or the like. The security measure rules may be based on the sensitivity of the data, the timing requirements for processing the data, the security capabilities of the external entities and the like. 
     At Event  508 , which may occur after of before determining and implanting other security measures/features, external entities are selected for quantum-level processing of the data blocks. The selection of the external entities may be based on an external entity selection rules that take into account the sensitivity of the data, the security capabilities of the external entities and the processing capabilities of the external entities. At Event  510 , the data blocks are communicated to the selected external entities. 
     At Event  512 , in response to quantum-level computing processing of the data blocks by the external entities, the processed data blocks are received and, at Event  514 , the other security measures are removed from the data blocks. For example, the obfuscation is removed and the dummy data is removed from the data blocks. At Event  514 , the data set is re-formed by combining the data blocks in accordance with re-formation rules. 
     Referring to  FIG. 7  a flow diagram is depicted of a method  600  for determining and applying security measures to data sets for subsequent external entity quantum-level computing, in accordance with embodiments of the present invention. At Event  602 , a data set is determined to require quantum-level computing processing, in addition to or in lieu of conventional binary-level computing processing. The determination may be based on the complexity of the computation required, the accuracy required of the computation and/or the time allotted for completing the processing and/or other factors. 
     At Event  604 , security measures to be applied to the data set are determined based on at least one of the level of sensitivity of the data and timing requirements for processing the data. The security measures may include, but are not limited to, segmenting the data into data blocks, obfuscating the data set or data blocks and inserting dummy data into the data set or data blocks. At Event  606 , the determined security measures are applied to the data set. 
     At Event  608 , which may occur after of before determining and implanting other security measures/features, an external entity is selected for the data set or external entities are selected for the data blocks. The selection of the external entities may be based on an external entity selection rules that take into account the sensitivity of the data, the security capabilities of the external entities and the processing capabilities of the external entities. At Event  610 , the data set or data blocks are communicated to the selected external entity/entities. 
     At Event  612 , in response to quantum-level computing processing of the data set or data blocks by the external entities, the processed data set or data blocks are received and, at Event  614 , the security measures are removed from the data blocks. For example, the data set is re-formed by combining the data blocks in accordance with re-formation rules, the obfuscation is removed from the data set or data blocks and/or the dummy data is removed from the data set or blocks. 
     Thus, systems, apparatus, methods, and computer program products described above provide for determining and applying security measures, such as segmentation, obfuscation and/or insertion of dummy data, to data sets determined to require external quantum-level computing processing. The security measures herein described and implemented lessens the risk associated with the data being breached/comprised at the external entity. 
     While certain exemplary embodiments have been described and shown in the accompanying drawings, it is to be understood that such embodiments are merely illustrative of and not restrictive on the broad invention, and that this invention not be limited to the specific constructions and arrangements shown and described, since various other changes, combinations, omissions, modifications and substitutions, in addition to those set forth in the above paragraphs, are possible. 
     Those skilled in the art may appreciate that various adaptations and modifications of the just described embodiments can be configured without departing from the scope and spirit of the invention. Therefore, it is to be understood that, within the scope of the appended claims, the invention may be practiced other than as specifically described herein.