sadat2307/MSciNLI huggingface dataset:
Domain: Security and privacy
Sentence 1: The penalty is higher for the other hash table types, as we can t know how many uniquekeysfall into anygivenbucket until the cuckoo tables arebuilt.Ifabucketfailstobuildits tables,the whole process must restart from Phase 1.
Sentence 2: the chance of this happening decreases as multiplicity increases: because the amount ofbuckets allocatedis dependentonthe total numberof itemsand notthe numberof uniquekeys,it becomes moredif.culttoover.ll abucket.
Relationship: contrasting
Domain: Security and privacy
Sentence 1: Furthermore, the cooperating server policy extension mitigates this prob­lem.
Sentence 2: the protection o.ered by the server-side ex­tension depends on the serverpolicywriter by relaxing the client-side policy, the server policy is able to reduce the amount of false positives, but it is also able to introduce false negatives if this relaxation is pushed too far.
Relationship: contrasting
Domain: Security and privacy
Sentence 1: When using class loader DexClassLoader in Dalvik, the protected method loadClass() in Dalvik does check whether the class is already loaded or not; if it is, it will not reload the same class.
Sentence 2: this is only enforced inside DexClass-Loader, so if a malicious component extends DexClassLoader and overrides loadClass(), it can successfully reload a class.
Relationship: contrasting
Domain: Security and privacy
Sentence 1: 4.1 A Binary Feature Space Mapping consumption traces to a vector space may seem trivial at a .rst glance, as the measurements of a day are already represented as a d-dimensional vector.
Sentence 2: for discriminating di.erent patterns in this data, we require a more advanced representation that emphasizes the charac­teristics of each consumer and provides an expressive basis for application of machine learning.
Relationship: contrasting
Domain: Security and privacy
Sentence 1: Under these circumstances problems of the improving information management systems in all spheres of society s activity come to the forefront of economic and social development and intensive and large-scale research in recent years.
Sentence 2: the information society development leads to an increase of threats to national and international security related to violation of the established modes of ICT systems usage, infringement of the constitutional rights and freedoms of citizens, malware spread as well as the use of modern IT in hostile, terrorist and other criminal acts.
Relationship: contrasting
Domain: Security and privacy
Sentence 1: To expose these behavioral similari­ties, malware binaries are usually executed in a monitored sandbox environment, in order to identify malware families characterized by similar host-level events [e.g., 1, 3, 20, 27] or network tra.c patterns [e.g., 13, 14, 24, 25].
Sentence 2: regardless the behavioral features being used, all these proposals su.er from the same vulnerability: cluster­ing algorithms have not been originally devised to deal with data from an adversary.
Relationship: contrasting
Domain: Security and privacy
Sentence 1: This is handled as follows: The parties will only choose the new hash function after the previous HH was sent over the channel, so in order to create a collision, the adversary must change the hash function (rather than its input).
Sentence 2: if the adversary created errors in the hash function, then the states of the two parties will di.er since one of them received the wrong description of the hash function (while the party who generated the hash function of course has the correct value).
Relationship: contrasting
Domain: Security and privacy
Sentence 1: R(n) =n 1+R( B l), if n > t L J B For a generic hidden volume construction, the number of block plog22nl n operations using Path ORAM is then max·A( max ).
Sentence 2: for this construction the total number of access is justSimilarly, we can de.ne relations W (n) and R(n) for our write-W (n), since we do not divide the system into separate volumes.
Relationship: contrasting
Domain: Security and privacy
Sentence 1: 2.1 Application Scenarios We fully respect that people have the right to protect their pri­vacy, so the most important goal of this paper is not to propose new tracking techniques to invade people s privacy, but instead to bring a new possible privacy attack into people s attention and raise an alarm of such new user tracking method.
Sentence 2: as a device .ngerprinting technology, the proposed user tracking method itself is neutral, so if it is used properly, it could bene.t our society to a large extent.
Relationship: contrasting
Domain: Security and privacy
Sentence 1: In this paper, we focus on TCP .ows, becauseTCP carriesabout 90% of Internettraf.c[16],andpopular anonymity networks (e.g., Tor [17]) currently only support TCP-basedapplications.
Sentence 2: the same idea could be appliedtoother end-to-endprotocols.
Relationship: contrasting
Domain: Security and privacy
Sentence 1: UCS inherits same principle and structure of XCS where an initial population of rules is derived from training data.
Sentence 2: it di.ers from XCS as (1) it is based on a supervised learning scheme that computes .tness instead of reinforcement, (2) the GA is applied to correct the rule-set for updating its population, and (3) it does not use a prediction array.
Relationship: contrasting
Domain: Security and privacy
Sentence 1: For those computing units thatexecute tamperedveri.cation codes, the minimum time for .nishing their tasks alone can be estimated in the same way as estimated on uniprocessor platforms [16, 15].
Sentence 2: the estimated time cannot be used as the timing thresh­olds if the adversary is able to accelerate the remaining computation process by using the idle computing units that .nish the execution of the legitimate veri.cation code.
Relationship: contrasting
Domain: Security and privacy
Sentence 1: INTRODUCTION Due to the rapid evolution of data collection and storage technolo­gies, extracting knowledge and hidden patterns from stored data has become a major necessity for individuals, companies, and gov­ernment agencies.
Sentence 2: applying data mining techniques to extract information is considered a challenge when the data is dis­tributed over multiple owners, and each data owner is concerned about the privacy of individuals in his data.
Relationship: contrasting
Domain: Security and privacy
Sentence 1: As mentioned above, they might route or forward data in multi-hop situations, but there is no need for an applied end-to-end communication.
Sentence 2: to ensure authenticity and data-origin-proof, it will also be necessary for, e.g., the sink to verify that certain received aggregated data has been aggregated in a correct way, set aside the meaning of correct.
Relationship: contrasting
Domain: Security and privacy
Sentence 1: While there was a "Trusted Network Interpretation", the interpretation was in some senses a permutation of the central assumptions of the Orange Book.
Sentence 2: the Common Criteria allows one the freedom to specify a secure kangaroo if one wishes, provided one uses the proper terminology, and can adequately state the threats, goals, mechanisms, procedures and countermeasures which apply to the kangaroo security domain.
Relationship: contrasting
Domain: Security and privacy
Sentence 1: Several consent models with associated consent templates have been identi.ed [7, 23], and a few e-Consent based systems have been built upon these guidelines [22, 19].
Sentence 2: it is still essen­tial to develop a systematic approach to determining how a patient s consent is expressed and at what granularity the consent is applied to the EHRs.
Relationship: contrasting
Domain: Security and privacy
Sentence 1: Furthermore, from a purely mathematical point of view integrity is the dual of con.den­tiality so the results from one should carry over to the other, and intrusion detection can entail con.dentiality concerns, in addition to integrity or availability.
Sentence 2: the differences between con­.dentiality and integrity go well beyond the mathematical, as illus­trated by the differences between Biba s model for integrity [3] and those of Lipner [33] or Clark andWilson [9].
Relationship: contrasting
Domain: Security and privacy
Sentence 1: For instance, a ma­licious third-party component provider can invoke typical security-sensitive operations such as the retrieval of cookies, navigation of the browser to another page, launch of exter­nal requests or access and updates to the Document Object Model (DOM).
Sentence 2: with the emerging HTML5 speci.cation and APIs, the impact of injecting and executing arbitrary Java-Script has massively increased.
Relationship: contrasting
Domain: Security and privacy
Sentence 1: Traditional security considerations revolve around protecting the network connection s confidentiality and integrity, protecting the system from break-in, and protecting the user s private information from unintended disclosure.
Sentence 2: one area that has long been neglected is that of service availability in the presence of Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page.
Relationship: contrasting
Domain: Security and privacy
Sentence 1: In the case of changing order of concurrent operations, the authenticator Tj@R is still valid (it passes the check of Algorithm 3 -line 7).
Sentence 2: if R continues to work on the document and adds new opera­tion opk after opj, then commits an authenticator Tk@R, other sites cannot change the order of opi, opj and opk since this misbehavior will make the authenticator Tk@R invalid by the checking procedure in Algorithm 3 -line 8.
Relationship: contrasting
Domain: Security and privacy
Sentence 1: For example, in Figure 3, all the r 2 values below 0.01 are dropped.
Sentence 2: we can still .gure out haplotype frequencies for individ­ual haplotype blocks using the r 2 within blocks, and connect dif­ferent blocks together by running a maximum likelihood estimator over the remaining LDs between blocks.
Relationship: contrasting
Domain: Security and privacy
Sentence 1: Critics would argue that any government intervention in the media marketplace in an attempt to protect privacy is an unwarranted intrusion on the freedom of press.
Sentence 2: if the government cannot be trusted to regulate the press, why should anyone believe that the press will do a better job of showing self-restraint and exercising higher moral and ethical judgement, especially in light of increasing market competition?
Relationship: contrasting
Domain: Security and privacy
Sentence 1: We can conclude this sectionby observing that, combining basic methodswith boolean operationscanbehelpfulto selectadifferent combinationofFARandIPR.Thatis,asitis possiblebyvarying T and ß ,also with boolean combinations we might look foradifferent value of one of the performance metrics (FAR and IPR).
Sentence 2: we observe that also with boolean combinations is not possible to improve bothFAR and IPR at the same time.
Relationship: contrasting
Domain: Security and privacy
Sentence 1: Whereas after analyzing the statistical data, the participants in Group2 have not shown too much advantages in the as­pect of click-numbers though they actually generated their passwords more securely.
Sentence 2: we .nd that the user guidelines are very e.ective for new users who did not use the graphical passwords before in terms of the participants feedback as well as the password-pattern analysis.
Relationship: contrasting
Domain: Security and privacy
Sentence 1: TPM-based attestation protocols use measure­ments, typically hashes of software packages loaded for execution, to establish the trustworthiness of a platform.
Sentence 2: this ap­proach may reveal speci.cs of the cloud provider s software infras­tructureto competitors.Forexample, measurementsmayrevealthe use of a module implementing a particular scheduling algorithm or a performance-enhancing library.
Relationship: contrasting
Domain: Security and privacy
Sentence 1: 5.2 Password Manager Since Versipass does not store passwords, there is no risk that an attacker who gains access to Versipass might be able to access the user s accounts.
Sentence 2: such an at­tacker would be able to access personal information (the list of sites where the user has accounts, and the user s user­names), and cause signi.cant disruption for the user (by changing their category passwords or by deleting informa­tion).
Relationship: contrasting
Domain: Security and privacy
Sentence 1: If the compromised node cannot modify the received aggregate, i.e., it can only forge a false reading of its own, then the aggregation data may range from 98.7F(100*50+32 ) ~ 51 101F( 100*50+150 51 ), which does not deviate far away from the true average value.
Sentence 2: if it can launch a count changing attack by reporting a bogus large count value, then it can make the average re­sult be any value in the range from 100F to 150F (assuming its own reported temperature is 150F).
Relationship: contrasting
Domain: Security and privacy
Sentence 1: As previewed in Fig­ure 1, while the information disclosed in the public pro.les covers many classes (e.g., demographics, location, education, and af.lia­tion), it is generally coarse-grained (and thus less identi.able and less sensitive) and static (and thus less timely).
Sentence 2: the in­formation leaked on to the network is .ner-grained and/or dynamic which closely re.ects users cyber and real-world activities and in­terests.
Relationship: contrasting
Domain: Security and privacy
Sentence 1: The security strength of the Diffie-Hellman key exchange protocol comes from the difficulty of the discrete logarithm problem [2, 11].
Sentence 2: an attacker can relatively easily sniff and capture the public values used for the key exchange, R1 = gx mod p, and R2 = gy mod p. given R1 and R2, it is computationally difficult to find x and y.
Relationship: contrasting
Domain: Security and privacy
Sentence 1: The overall reachability analysis will then show that there is a direct information .ow path through the encryption device, con­necting the high-security domain to the low-security domain, via pins a, b, c, d, e and f in all of the EncOff modes.
Sentence 2: this is not a security concern it merely tells us that data .ows freely through the device when it is not required to encrypt, as expected.
Relationship: contrasting
Domain: Security and privacy
Sentence 1: NativeGuard: Protecting Android Applications from Third-Party Native Libraries Mengtao Sun Gang Tan Lehigh University Lehigh University 27 Memorial Drive West 27 Memorial Drive West Bethlehem, PA 18015, United States Bethlehem, PA 18015, United States  mengtao.sun@lehigh.edu gtan@cse.lehigh.edu ABSTRACT Android applications often include third-party libraries writ­ten in native code.
Sentence 2: current native components are not well managed by Android s security architecture.
Relationship: contrasting
Domain: Security and privacy
Sentence 1: It would seem that at least the approaches targeting at arbitrary, interacting bad measurements (e.g., [4,12,21,25]) can also defeat the malicious ones injected by attackers, since such malicious measurements are indeed arbitrary, interact­ing bad measurements.
Sentence 2: despite the variations in these approaches, all of them use the same method (i.e., lz - H xl >t ) to detect the existence of bad measure­ments.
Relationship: contrasting
Domain: Security and privacy
Sentence 1: attack on Grain-v1, by using a guess-and-determine attack to decrease the sampling resistance by R =2-18 which re­sults in lower pre-computation complexity.
Sentence 2: the 20 Table 1: Comparison of TMD Attacks on Estream Table 2: Comparison of TMD Attacks on Block Ci-Finalists phers Cipher Key IV State Size Our Attack Existing Attacks HC-128 Rabbit Salsa20 SOSEMANUK Grain-v1 MICKEY-v2 TRIVIUM 128 128 128 128 80 80 80 128 64 64 64 64 64 80 32778 513 512 384 160 200 288 No Yes Yes Yes Yes Yes No No No No No No No No Note : The existing attacks refers to BS-TMD, HS-TMD and DK-TMD attack.
Relationship: contrasting
Domain: Security and privacy
Sentence 1: Readings or messages from several sensors are processed at a data fusion node and aggregated into a more compact report before being relayed to the parent node in the data fusion hierarchy [13].Passive participation is another form of in-network processing in which a sensor node can take certain actions based on overheard messages [14, 20], e.g., a sensor can decide to not report an event if it overhears a neighboring node reporting the same event.
Sentence 2: particular keying mechanisms may preclude or reduce the e.ectiveness of in-network processing.To support passive participation, it is essential that intermediate nodes be able to decrypt or authenticate a secure message exchanged be­tween two other sensor nodes.Thus, passive participation of secure messages is only possible if multiple nodes share the keys used for encryption and authentication.if a pairwise shared key is used for encrypting or authenticating a message, it e.ectively precludes passive participation in the sensor network.
Relationship: contrasting
Domain: Security and privacy
Sentence 1: This type of access control is referred to as static authentication.
Sentence 2: we .nd Continuous Authentication (also called Active Au­thentication1), where the genuineness of a user is continuously ver­ 1http://www.darpa.mil/Our_Work/I2O/Programs/ Active_Authentication.aspx Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for pro.t or commercial advantage and that copies bear this notice and the full citation on the .rst page.
Relationship: contrasting
Domain: Security and privacy
Sentence 1: This is nec­essary since examples of benign PDF documents with JavaScript content are quite rare, and it takes a lot of manual e.ort to verify that they are benign.
Sentence 2: examples of malicious PDF documents abound on malware collection systems, and their maliciousness can be ascertained with high con.dence if they are detected by antivirus systems.
Relationship: contrasting
Domain: Security and privacy
Sentence 1: On the one hand, any role-dependent IA-DHKE, like robust (H)MQV and KEA/OPACITY, does not satisfy, by de.­nition, the completeness property of role-independent SK­security.
Sentence 2: any role-independent IA-DHKE like the basic (H)MQV is totally broken according to role­dependent SK-security (as the session-key of the test-session can exist in a non-matching session by the cross-message at­tack [25]), which might be viewed as more dangerous.
Relationship: contrasting
Domain: Security and privacy
Sentence 1: Many watermarking schemes have been developed for gray-scale and color images.
Sentence 2: these watermarking schemes cannot be applied to binary document images, since such schemes achieve embedding by small changes to the gray/color pixel values which is not possible for binary values, and also since perceptible image distortion of binary images (see section 2.3) is quite different from that of gray/color images.
Relationship: contrasting
Domain: Security and privacy
Sentence 1: The event s participants appear in the Facebook event with the identity of the account they provided.
Sentence 2: textual posts, comments, likes and photos are posted in the Facebook event in cleartext, to maintain the .exibility and convenience of the Facebook interface.4 video and audio recording posted to the event are uploaded using the Dropbox conduit (encrypted with the shared event key), and a URL to that content is posted in the Facebook event.
Relationship: contrasting
Domain: Security and privacy
Sentence 1: CRAFT: A New Secure Congestion Control Architecture Dongho Kim , Jerry T. Chiang , Yih-Chun Hu , Adrian Perrig , and P. R. Kumar Department of Electrical and Computer Engineering, University of Illinois at Urbana-Champaign, IL, USA Department of Electrical and Computer Engineering, Carnegie Mellon University, PA, USA {dkim99,chiang2,yihchun,prkumar}@illinois.edu, perrig@cmu.edu ABSTRACT Congestion control algorithms seek to optimally utilize network re­sources by allocating a certain rate for each user.
Sentence 2: mali­cious clients can disregard the congestion control algorithms im­plemented at the clients and induce congestion at bottleneck links.
Relationship: contrasting
Domain: Security and privacy
Sentence 1: Once highly motivated bot developers know the HOP approach, it is possible for them to create more advanced game bots to evade the HOP system.
Sentence 2: the purpose of the HOP system is to raise the bar against game exploits andforce adeterminedbotdeveloper to spend signi.canttime and e.ortinbuilding next-generationgame bots for detection evasion.
Relationship: contrasting
Domain: Security and privacy
Sentence 1: This means that the packing of inputs will a.ect LSBs complexity in a slightly negative way; given the additive constants ax in the previous equations and a .xed s, the dif­ference in complexity between running h LSBs and running one LSBs with h packed integerswillbe(h-1)ax (indepen­dent of the bit-size l of the integers), while the number of rounds will increase in 2l(h-1), as without packing the h gates can be parallelized.
Sentence 2: the computation complexity is O(s 4), so using Damg°ard-Jurik encryptions would suppose a con­siderable increase in complexity, what justi.es the preference for packing only using s = 1.
Relationship: contrasting
Domain: Security and privacy
Sentence 1: They demonstrated their technique on three example programs (about 30 lines each), as well as real applications such as Apache, showing that about 90% of the time, control could be successfully returned to the attack code.
Sentence 2: the focus of their evaluation was to demonstrate the ability of their symbolic execution technique to generate con.gura­tions that can return control back to the attack code.
Relationship: contrasting
Domain: Security and privacy
Sentence 1: If Revent-past and Rnormal-past are of equal cardinality, then Revent-past is a better predictor of the report Revent-present at pre.x length n if: |Cn(Revent-past) n Cn(Revent-present)| > |Cn(Rnormal-past) n Cn(Revent-present)| (4) If temporal uncleanliness exists, then we expect that un­clean reports will consistently be better predictors of future unclean reports than a control report.
Sentence 2: we note that due to spatial uncleanliness, an unclean report will pop­ulate fewer equally sized blocks than an equivalent control report.
Relationship: contrasting
Domain: Security and privacy
Sentence 1: Reviewing the results from both user studies, we conclude that although Line Snaking has better defence performance, the Disappearing Stroke technique is more appropriate for general deployment, since it offers reasonable protection and good usability, and it is also preferred by the users.
Sentence 2: with regards to technique choice, it is possible that users themselves should be able to decide on which defence technique to apply depending on their situation, as our results indirectly show that although users reported Disappearing Stroke as more comfortable to use, they immediately spotted the security advantage of Line Snaking.
Relationship: contrasting
Domain: Security and privacy
Sentence 1: Trapdoor Permutations (TDPs) A family of trapdoor permuta­tions (TDPs) is a family of permutations such that it is easy to randomly select a permutation f and some trapdoor associated with f. Furthermore, f is easy to compute and, given the trapdoor information, so is its inverse f-1 .
Sentence 2: without the trapdoor, f is hard to invert on random inputs: No PPT adversary A, given y = f(x) for random x, can .nd x with probability greater than ETDP, which is negligible in the security parameter e of the gener­ation algorithm.
Relationship: contrasting