Abstract:
Systems and methods are disclosed for responding to security events in real time. The disclosed systems and methods utilize the vast amount of risk and asset knowledge collected in a security data warehouse and aggregated in a security information manager, without the expense and latency associated with performing such calculations in real time. The disclosed systems and methods, thereby, significantly extend the time intervals feasible for temporal analysis.

Description:
TECHNICAL FIELD 
     Aspects of the disclosure relate generally to a cyber security analytics architecture. In particular, various aspects of the disclosure relate to methods and systems for analyzing events and detecting risks in real time and based on historical data to provide security for large-scale enterprises. 
     BACKGROUND 
     Large scale enterprises have become more complex and require a number of separate systems to communicate. As a result, computing devices are being required to interact with more systems in order to accomplish their assigned functionality. Furthermore, these computing devices must interact with overwhelming amounts of data. Therefore, it is becoming increasingly difficult for computing devices to perform data analytics and address real-time events and risks to an enterprise. Accordingly, there is a need for systems and methods addressing one or more of these shortcomings. 
     SUMMARY 
     The following presents a simplified summary of the present disclosure in order to provide a basic understanding of some aspects of the disclosure. This summary is not an extensive overview of the disclosure. It is not intended to identify key or critical elements of the disclosure or to delineate the scope of the disclosure. The following summary merely presents some concepts of the disclosure in a simplified form as a prelude to the more detailed description provided below. 
     Certain aspects disclose a computer-implemented method comprising: transferring, at a security event manager, data to a security data warehouse; comparing the data, at the security data warehouse, to information stored in a risk ontology, wherein the comparing is performed to determine whether the data should be transferred to a security information manager; receiving, at the security information manager, the data when the security data warehouse determines that the data should be transferred to the security information manager; comparing, at the security information manager, the data to stored rules and other stored information to determine a security context; transferring, at the security information manager, the security context to the security event manager, wherein the security context allows the security event manager to determine an event&#39;s risk level; receiving, at the security event manager, an event; and outputting, at the security event manager, the event&#39;s risk level. 
     Certain other aspects disclose a non-transitory computer-readable storage medium having computer-executable program instructions stored thereon that, when executed by a processor, cause the processor to: transfer, at security event manager, data to a security data warehouse; compare the data, at the security data warehouse, to information stored in a risk ontology, wherein the comparing is performed to determine whether the data should be transferred to a security information manager; receive, at the security information manager, the data when the security data warehouse determines that the data should be transferred to the security information manager; compare, at the security information manager, the data to stored rules and other stored information to determine a security context; transfer, at the security information manager, the security context to the security event manager, wherein the security context allows the security event manager to determine an event&#39;s risk level; receive, at the security event manager, an event; and outputting, at the security event manager, the event&#39;s risk level. 
     Further aspects disclose a system comprising: a security event manager configured to monitor and respond to real-time events; a security data warehouse configured to receive and store data in its original form, wherein the security data warehouse receives data from the security event manager, assets, monitoring, threat analysis, and external event sources; a risk ontology configured to provide a sustainable data model representing assets, relationships, and risk factors; and a security information manager configured to provide a description of an enterprise&#39;s risk landscape by gathering, combining, and rationalizing all of the asset, risk, and relationship data in the enterprise. 
     The details of these and other embodiments of the disclosure are set forth in the accompanying drawings and description below. Other features and advantages of aspects of the disclosure will be apparent from the description, drawings, and claims. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
       All descriptions are exemplary and explanatory only and are not intended to restrict the disclosure, as claimed. The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments of the disclosure and, together with the description, sever to explain principles of the disclosure. In the drawings: 
         FIG. 1  shows an illustrative operating environment in which various aspects of the disclosure may be implemented. 
         FIG. 2  shows an illustrative shows an illustrative block diagram of workstations and servers that may be used to implement the processes and function of one or more aspects of the present disclosure. 
         FIG. 3  shows an illustrative embodiment of a security analytics system in accordance with aspects of the disclosure. 
         FIG. 4  shows an illustrative embodiment of a risk ontology in accordance with aspects of the disclosure. 
     
    
    
     DETAILED DESCRIPTION 
     In accordance with various aspects of the disclosure, methods, non-transitory computer-readable media, and systems are disclosed for securing an enterprise via a cyber security analytics architecture. In certain aspects, when a server receives data from a computing device, the server processes and analyzes the data. The automated process may utilize various hardware components (e.g., processors, communication servers, memory devices, etc.) and related computer algorithms to generate image data related to the agency&#39;s business data. 
       FIG. 1  illustrates an example of a suitable computing system environment  100  that may be used according to one or more illustrative embodiments. The computing system environment  100  is only one example of a suitable computing environment and is not intended to suggest any limitation as to the scope of use or functionality contained in the disclosure. The computing system environment  100  should not be interpreted as having any dependency or requirement relating to any one or combination of components shown in the illustrative computing system environment  100 . 
     The disclosure is operational with numerous other general purpose or special purpose computing system environments or configurations. Examples of well-known computing systems, environments, and/or configurations that may be suitable for use with the disclosed embodiments include, but are not limited to, personal computers (PCs), server computers, hand-held or laptop devices, multiprocessor systems, microprocessor-based systems, set-top boxes, programmable consumer electronics, network PCs, minicomputers, mainframe computers, distributed computing environments that include any of the above systems or devices, and the like. 
     With reference to  FIG. 1 , the computing system environment  100  may include a server  101  wherein the processes discussed herein may be implemented. The server  101  may have a processor  103  for controlling the overall operation of the server  101  and its associated components, including random-access memory (RAM)  105 , read-only memory (ROM)  107 , communications module  109 , and memory  115 . Processor  103  and its associated components may allow the server  101  to run a series of computer-readable instructions related to receiving, storing, and analyzing data to determine an event&#39;s risk level. 
     Server  101  typically includes a variety of computer-readable media. Computer-readable media may be any available media that may be accessed by server  101  and include both volatile and non-volatile media, removable and non-removable media. For example, computer-readable media may comprise a combination of computer storage media and communication media. 
     Computer storage media include volatile and non-volatile, removable and non-removable media implemented in any method or technology for storage of information such as computer-readable instructions, data structures, program modules, or other data. Computer storage media include, but are not limited to, random access memory (RAM), read only memory (ROM), electronically erasable programmable read only memory (EEPROM), flash memory or other memory technology, CD-ROM, digital versatile disks (DVD) or other optical disk storage, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other medium that can be used to store the desired information that can be accessed by server  101 . 
     Computing system environment  100  may also include optical scanners (not shown). Exemplary usages include scanning and converting paper documents, such as correspondence, data, and the like to digital files. 
     Although not shown, RAM  105  may include one or more applications representing the application data stored in RAM  105  while the server  101  is on and corresponding software applications (e.g., software tasks) are running on the server  101 . 
     Communications module  109  may include a microphone, keypad, touch screen, and/or stylus through which a user of server  101  may provide input, and may also include one or more of a speaker for providing audio output and a video display device for providing textual, audiovisual and/or graphical output. 
     Software may be stored within memory  115  and/or storage to provide instructions to processor  103  for enabling server  101  to perform various functions. For example, memory  115  may store software used by the server  101 , such as an operating system  117 , application programs  119 , and an associated database  121 . Also, some or all of the computer executable instructions for server  101  may be embodied in hardware or firmware. 
     Server  101  may operate in a networked environment supporting connections to one or more remote computing devices, such as computing devices  1141 ,  151 , and  161 . The computing devices  141 ,  151 , and  161  may be personal computing devices or servers that include many or all of the elements described above relative to the server  101 . Computing device  161  may be a mobile device communicating over wireless carrier channel  171 . 
     The network connections depicted in  FIG. 1  include a local area network (LAN)  125  and a wide area network (WAN)  129 , but may also include other networks. When used in a LAN networking environment, server  101  may be connected to the LAN  125  through a network interface or adapter in the communications module  109 . When used in a WAN networking environment, the server  101  may include a modem in the communications module  109  or other means for establishing communications over the WAN  129 , such as the Internet  131  or other type of computer network. It will be appreciated that the network connections shown are illustrative and other means of establishing a communications link between the computing devices may be used. Various well-known protocols such as TCP/IP, Ethernet, FTP, HTTP and the like may be used, and the system may be operated in a client-server configuration to permit a user to retrieve web pages from a web-based server. Any of various conventional web browsers may be used to display and manipulate on web pages. 
     Additionally, one or more application programs  119  used by the server  101 , according to an illustrative embodiment, may include computer executable instructions for invoking functionality related to communication including, for example, email short message service (SMS), and voice input and speech recognition applications. In addition, the application programs  119  may include computer executable instructions for invoking user functionality related to access a centralized repository for performing various service tasks like routing, logging, and protocol bridging. 
     Embodiments of the disclosure may include forms of computer-readable media. Computer-readable media include any available media that can be accessed by a server  101 . Computer-readable media may comprise storage media and communication media and in some examples may be non-transitory. Storage media include volatile and nonvolatile, removable and non-removable media implemented in any method or technology for storage of information such as computer-readable instructions, object code, data structures, program modules, or other data. Communication media include any information delivery media and typically embody data in a modulated data signal such as a carrier wave or other transport mechanism. 
     Various aspects described herein may be embodied as a method, a data processing system, or as a computer-readable medium storing computer-executable instructions. For example, a computer-readable medium storing instructions to cause a processor to perform steps of a method in accordance with aspects of the disclosed embodiments is contemplated. For instance, aspects of the method steps disclosed herein may be executed on a processor  103  on server  101 . Such a processor may execute computer-executable instructions stored on a computer-readable medium. 
       FIG. 2  illustrates another example operating environment in which various aspects of the disclosure may be implemented. As illustrated, system  200  may include one or more workstations  201 . Workstations  201  may, in some examples, be connected by one or more communications links  202  to computer network  203  that may be linked via communications links  205  to server  204 . In system  200 , server  204  may be any suitable server, processor, computer, or data processing device, or combination of the same. Server  204  may be used to process the instructions received from, and the transactions entered into by, one or more participants. 
     According to one or more aspects, system  200  may be associated with a financial institution, such as a bank. Various elements may be located within the financial institution and/or may be located remotely from the financial institution. For instance, one or more workstations  201  may be located within a branch office of a financial institution. Such workstations may be used, for example, by customer service representatives, other employees, and/or customers of the financial institution in conducting financial transactions via network  203 . Additionally or alternatively, one or more workstations  201  may be located at a user location (e.g., a customer&#39;s home or office). Such workstations also may be used, for example, by customers of the financial institution in conducting financial transactions via computer network  203 . 
     Computer network  203  may be any suitable computer network including the Internet, an intranet, a wide-area network (WAN), a local-area network (LAN), a wireless network, a digital subscriber line (DSL) network, a frame relay network, and asynchronous transfer mode network, a virtual private network (VPN), or any combination of any of the same. Communications links  202  and  205  may be any communications links suitable for communicating between workstations  201  and server  204 , such as network links, dial-up links, wireless links, hard-wired links, and/or the like. 
     Having described an example of a computing device that can be used in implementing various aspects of the disclosure and an operating environment in which various aspects of the disclosure can be implemented, several embodiments will now be discussed in greater detail. 
     In an embodiment, an enterprise, such as a bank, may service user requests from a user computing device. For example, a bank may service user requests generated at a computing device and routed to a bank computing device through a network, for example the Internet. User requests may be generated by entities that work with the organization, divisions within the organization, or individuals, such as bank customers. These requests may include user requests to electronically manage a customer account with the bank, to access electronic information, or any other suitable request. 
     The users accessing server  204  in system  200  may be referred to as assets. Assets may also describe other entities that may attempt to access an enterprise, such as workstations, network equipment, computer systems, and the like. In certain aspects, an asset may be considered an individual component in a system. For example, system  200  may represent an enterprise&#39;s, such as a large bank&#39;s, computer system. Each workstation, server, user, application, and network device may be considered an asset. Thus, to ensure security of the enterprise&#39;s system, the bank (in this and foregoing examples) must be able to monitor its assets and detect and respond to real-time threats posed by any particular asset. 
       FIG. 3  illustrates an example of a security analytics system  350  in which aspects of the disclosure may be implemented. The security analytics system  350  comprises a architecture  300 . The architecture  300  may comprise a security event manager (SEM)  301 , a security data warehouse  302 , a security information manager (SIM)  303 , and a risk ontology  304 . In some aspects, architecture  300  may be located in a server  101 , or across a plurality of servers  101 . The architecture  300  may be stored, in certain aspects, in a memory  115  of server  101 . In certain other aspects, portions of the architecture  300  may be stored in a plurality of servers  101 . For instance, SEM  301  and security data warehouse  302  may be stored in a first server and SIM  303  and risk ontology  304  may be stored in a second server. Furthermore, architecture  300  may include a plurality of SEMs  301 , security data warehouses  302 , SIMs  303 , and risk ontologies  304 . 
     Architecture  300  may allow an enterprise to monitor its assets and detect and respond to real-time threats posed by any particular asset. Architecture  300  may secure a system against threats by monitoring the data transmitted by assets. In some aspects, the data transmitted by assets may include, or be associated with, events. An event may be an action taken by an asset that could serve as a threat to a system or enterprise. Such actions may include, for example, transmitting data over the system, downloading or uploading data, logging into the system, and the like. As an example, a user may attempt to log into the system by entering username and password into workstation  201 . The data entered by the user is associated with an event (i.e. logging into the system). Therefore, the data is initially received by security event manager  301  in architecture  300 . 
     SEM  301  may receive and act upon data in real time. SEM  301  may comprise one or more components of server  101 . Further, SEM  301  may comprise computer executable instructions, that when executed by a processor, cause the processor to perform a set of actions. SEM  301  may act upon data in real time using rules provided by analytics  321  information received from SIM  303 . In certain aspects, the information transferred from SIM  303  to SEM  301  may include security context. A security context may be considered an understanding of the environment in which an event is occurring. Security context transferred from SIM  303  may provide the SEM  301  with greater insight as to the event and its implications on the system and other assets within the system. Thus, security context may allow SEM  301  to quickly analyze data associated with an event and determine whether the asset associated with the data is a threat. The method with which the SIM  303  may establish security context will be discussed in greater detail below. 
     SEM  301  may also receive data from security monitoring  316 . Security monitoring  316  may monitor the fastest moving network data, such as proxy logs, firewall information, and other data that must be processed at the asset level. In some aspects security monitoring  316  network events may be the only type of data that is mapped against a rule manager located in SEM  301 . In certain aspects, a copy of the event may be transferred from SEM  301  to security data warehouse  302  for more analysis. 
     In certain aspects, SIM  303  may transfer one or more correlated events to SEM  301 . The correlated events may be determined at SIM  303  based on use cases received from analytics  321 , as will be discussed in greater detail below. SEM  301  may also receive and store rules transmitted by analytics  321 . In some aspects, the rules transmitted by analytics  321  may provide SEM  301  instructions for handling and responding to analyzed events. As an example, SEM  301  may receive data associated with the event that a user has logged into the system. Based on the security context and any correlated events, the SEM  301  may determine that the user (i.e. asset) has a risk level of 7 out of 10. SEM  301  may then analyze its stored rules provided by analytics  321 , which may provide that assets with a risk level of 5 out of 10 or greater must be denied access to the system. The security contexts, correlated events, and rules may be stored in SEM  301  prior to the event, thereby avoiding delays associated with analyzing events and performing calculations at SEM  301 . Rather, SEM  301  may be able to receive and respond to events in real time. 
     In some aspects, after the SEM  301  receives data associate with an event, SEM  301  may transfer the data or a copy of the event to security data warehouse  302 . Security data warehouse  302  may comprise one or more components of server  101 . Further, security data warehouse  302  may comprise computer executable instructions, that when executed by a processor, cause the processor to perform a set of actions. In certain aspects of the disclosure, the security data warehouse  302  may receive data in its original form, unmodified and unfiltered. The security data warehouse  302  may serve as a repository for all raw data distributed throughout the system  350 . Data may be stored in security data warehouse  302  over long periods of time for analysis and anomaly detection. 
     In certain aspects, one or more security data warehouses  302  may store all of the raw data distributed throughout an enterprise&#39;s system. A benefit this provides over other prior art systems is that it allows the SIM  303  to provide a richer security context to SEM  301 . Rather than performing all of the steps in a single component of a system, architecture  300  may more efficiently handle received data by separating data into at least three components. Architecture  300  does not require one component to store all data in the system, perform calculations and determine security contexts, while also responding to events that may occur. Instead, SEM  301  may focus on responding to events in real time, security data warehouse  302  may focus on storing all data passed through the system, and SIM  303  may be responsible for analyzing the relevant data (determine via risk ontology  304 ) in order to provide security context for SEM  301 . Because, in some aspects, security data warehouse  302  may only be responsible for storing data, it may be configured to store all data distributed in an enterprise&#39;s system, whereas other prior art systems may not have been able to store such large quantities of data. More data stored in security data warehouse  302  provides more tools for SIM&#39;s  303  analytics in determining a rich security context, which in turn enables SEM  301  to more thoroughly detect and respond to threats. 
     In some aspects of the disclosure, security data warehouse  302  may receive and store data from one or more other sources, such as an identity and access management (IAM)  310 , assets  311 , monitoring  312 , application logs  313 , threat analysis  314 , and external event sources (or Open SEM)  315 . System  350  may comprise one or more of these sources, or each source may comprise a component of another system communicating with architecture  300 . IAM  310  may control user access to resources within the enterprise. IAM  310  may maintain each user&#39;s level of access within the enterprise and provide that entitlement information to security data warehouse  302 . For example, users determined to be “administrators” in IAM  310  may be provided greater access than those determined to be “end users”. Security data warehouse  302  may store this entitlement information received from IAM  310 . 
     Security data warehouse may also receive and store configuration information from assets  311 . As shown in  FIG. 3 , assets  311  may also receive access rights from IAM  310 , which may provide areas of the enterprise that the asset may access. Furthermore, monitoring  312  may provide scans of the assets  311  and transmit vulnerabilities to security data warehouse  302 . In certain aspects, monitoring  312  may be a security system downloaded on the asset, such as an antivirus system. The vulnerabilities detected by monitoring  312  may be stored in security data warehouse  302 . 
     In some aspects, applications logs  313  may record transactions processed by applications in the enterprise. Applications logs  313  may transfer the recorded transactions to the security data warehouse  302 . In certain other aspects, applications logs  313  may transfer events to security data warehouse  302 . Security data warehouse  302  may also receive and store threats determined by threat analysis  314 . Threat analysis  314  may be a source that collects information about external risks facing an enterprise. Threat analysis  314  may, further, provide a classification of vulnerabilities, overall risk landscape of the enterprise, and a description of potential threats. Similarly, security data warehouse may store external events received from external event sources  315 . External event sources  315  may serve as an interface between the enterprise and other risk partners. For example, the bank enterprise may partner with government officials, financial security services, or other third parties to share information regarding various threats or attacks that may be eminent. This data may be transmitted from external event sources  315  to security data warehouse  302  and vice versa. 
     Once data has been received and stored in security data warehouse  302 , the data is mapped, or compared to, information stored in risk ontology  304 . An exemplary portion of an enterprise&#39;s risk ontology is illustrated in  FIG. 4 . As shown in  FIG. 4 , the ontology may be a sustainable data model representing assets, relationships, and risk factors in various databases, or tables. Each table stores data corresponding to a particular object. Objects in exemplary  FIG. 4  include Person, AccessRealm, Login, AccessGroup, AccessRole, ProtectedResource, ManagementGroup, CustodianRole, and ManagedResource. Each table in the ontology may store primary keys (PK) and foreign keys (FK) for each element of the table. Also shown in  FIG. 4  are arrows displaying the relationship between the various objects. For example, Login is related to AccessRealm and Person according to the stored primary keys and foreign keys in Login. Administrators or other parties may format the tables and corresponding objects and data in the risk ontology according to their preferred data to be monitored by SIM  303 . In some aspects, the risk ontology may be a dynamic risk ontology that may be mapped to other ontologies, such as IAM ontologies. 
     In certain aspects, every data element transferred from security data warehouse  302  to SIM  303  may first be mapped to risk ontology  304 . In such aspects, the risk ontology  304  may define every data element before being transferred to SIM  303 . Thus, system  350  may, in attempt to accelerate data ingestion rates and onboarding of new data sources, allow consumption of undocumented data elements, without any regard to how these data elements are related to other elements and the overall risk model. In some aspects, risk ontology  304  may be modified at any time. For example, risk ontology  304  may be modified such that previously unused data elements stored in security data warehouse  302  may be added to SIM  303 . Therefore, system  350  may ensure that no data is lost in translation at risk ontology  304 . 
     In some aspects, security data warehouse  302  may compare its stored data to information in risk ontology  304  to determine if the data should be transferred to SIM  303 . For example, the security data warehouse  302  may determine that the data should be transferred to the security information manager after locating the data on the risk ontology. In certain other aspects, processor  103  may compare the data stored in security data warehouse  302  to the information in risk ontology  304  to determine if the data should be transferred to SIM  303 . In some aspects, once security data warehouse  302  has determined that the data should be transferred to SIM  303 , SIM  303  will receive the data from security data warehouse  302 . 
     After receiving data from security data warehouse  302 , SIM  303  may gather, combine, and rationalize some or all of the data it has received to provide the best possible description of the enterprise&#39;s risk landscape at that time. SIM  303  may comprise one or more components of server  101 . Further, SIM  303  may comprise computer executable instructions, that when executed by a processor, cause the processor to perform a set of actions. SIM  303  may be configured to analyze the data it receives from security data warehouse  302  in order to provide a rich security context to SEM  301 . SIM  303  may be programmed to analyze trends in received data to detect anomalies associated with particular events and threats. For a simplified example, SIM  303  may analyze collected data that displays a trend of a high threat alert when a user login is attempted at a unique IP address for the first time. SIM  303  may recognize that the trend in this example tends to display a high likelihood of computer hacking SIM  303  may transfer this security context information to SEM  301 , so when a user login is attempted at a unique IP address for the first time, SEM  301  will immediately recognize the event and respond in real-time, i.e. by disallowing login access at that time. 
     SIM  303  may generally handle static data, security data warehouse  302  may handle time-based data, and SEM  301  may handle event-based data. Thus data may be segregated by system  350  in such a way as to deal with multiple types of data (i.e. real-time data, historical, structured data mapped to a risk model, etc.) rather than separating data by niche (i.e. network data, asset data, etc.). In some aspects, SIM  303  may serve as a single source of truth for all asset and risk data used within system  350 . System  350  may also maximize data accuracy by eliminating re-provisioning and minimizing distance to source. In certain aspects, SIM  303  may only store information understood in the context of a risk model. Therefore, the amount of data stored in SIM  303  and the latency to access data in SIM  303  may be substantially reduced. 
     SIM  303  may receive use cases from analytics  321 . An example of a use case may be a change in an employee&#39;s status from active to terminated. Analytics  321  may provide this information directly to SIM  303 . SIM  303  may, in turn, analyze the information and transfer it to SEM  301  in the form of a correlated event. Thus, if the employee attempts to log into the system once terminated, SEM  301  will recognize the correlated event and block the employee&#39;s attempt. In some aspects, SEM  301  may also notify analysts  322  of an actionable event so that they can conduct appropriate action. Further, analysts  322  may send a security case notification to output  330 , which may be similar to communications module  109  or workstations  201 . Output allows a party to view information about a particular event or set of events. Similarly, SIM  303  may send event information to output  330 . In certain aspects, SIM  303  may analyze data received from security data warehouse  302  to assess the risks associated with a particular asset and transmit the calculated asset risk to IAM  310 . 
     Algorithms may be configured in SIM  303  to enable it to calculate risk scores associated with assets. In some aspects, SIM  303  and/or SEM  301  may determine an event&#39;s risk level by comparing an event&#39;s risk score to a threshold level, as discussed above. So, when SEM  301  receives an event, SEM  301  may output the event&#39;s risk level, for instance, at output  330 . Thus, SEM  301  may respond to events in real time, as discussed above, by storing and analyzing previously received data to provide the SEM  301  with security context when receiving subsequent events. In other words, event data from time A may be received at SEM  301 , stored in security data warehouse  302  along with data received prior to time A. The data received at time A may be mapped to risk ontology  304  and transferred to SIM  303  for analysis along with other data received prior to time A. From this analysis, SIM  303  may transfer a security context to SEM  301  so that SEM  301  may respond to an event received at subsequent time B and respond to the data received at subsequent time B in real time. 
     The foregoing descriptions of the disclosure have been presented for purposes of illustration and description. They are not exhaustive and do not limit the disclosure to the precise form disclosed. Modifications and variations are possible in light of the above teachings or may be acquired from practicing of the disclosure. For example, the described implementation includes software by the present disclosure may be implemented as a combination of hardware and software or in hardware alone. Additionally, although aspects of the present disclosure are described as being stored in memory, one skilled in the art will appreciate that these aspects can also be stored on other types of computer-readable media, such as secondary storage devices, like hard disks, floppy disks, or CD-ROM.