sadat2307/MSciNLI huggingface dataset:
Domain: Security and privacy
Sentence 1: Both the authentication key and the access key are updated after a successful session in order to give backward untraceability.
Sentence 2: the scheme still permits backward andforwardtraceability,because a strong attackerthat com­promises a tagcanidentify a tag spastinteractionsfrom the previouscommunicationsand the .xedEPC of thetag,and canalsoread thetag sfuturetransactions.
Relationship: contrasting
Domain: Security and privacy
Sentence 1: The low false 0.3 negative rate suggests that FBCluster is able to detect most 0.2 0.1 spam in our dataset as spam URLs are often shared by spam 0 0 50 100 150 200 250 300 350 Time (day) # of Posts  (a) New users created every day(b) Cumulative distribution of post number by spammers/non­spammers Figure 1: Statistics of a social blog dataset  2.2 Evaluation of AutoRE 1 posts.
Sentence 2: the high false positive rate indicates that FBCluster has mistakenly included a number of non-spam posts in the detected spam clusters.
Relationship: contrasting
Domain: Security and privacy
Sentence 1: measuring the shape of the ear channel using acoustic data).
Sentence 2: we found the current phys­iological biometric solutions to be affected by one or more of the following problems: (i) non transparent usage; (ii) performances are heavily in.uencedbyexternalfactors such as illumination, po­sition or occlusion [20];(iii) lackof required hardware on current smartphones.
Relationship: contrasting
Domain: Security and privacy
Sentence 1: In particular, once a subset of parties and a function are chosen, the protocols of [19, 4] require the parties to be online and run an interactive MPC protocol to generate a joint public key.
Sentence 2: we require that once the function and a subset of parties is cho­sen, the cloud performs the (expensive) computations non­interactively, without help from any of the users.
Relationship: contrasting
Domain: Security and privacy
Sentence 1: LoPA and DiPA solved the same problem (i.e., aggregating data from sev­eral meters), which is also addressed by a number of other existing protocols in the literature [4, 3, 5, 9, 10, 11].
Sentence 2: the billing protocol allowed for the computation and veri.cation of the monthly bill of an individual house­ 1A large amount of this implementation has been done by George Danezis from Microsoft Research.
Relationship: contrasting
Domain: Security and privacy
Sentence 1: Since our goal is to ensure that a malicious user doesn t learn any unintended information, the above de.nition is similar to what is termed sender s security in [27] and vendor s security in [2].
Sentence 2: we di.er from both no­tions in that inference channels are a more general concept than the query counts in [27] and the query prices in [2], that determine access controls in those works.
Relationship: contrasting
Domain: Security and privacy
Sentence 1: From the existing metadata standards and metadata mod­els, only the Functional Requirements for Bibliographic Re­cords (FRBR) [18] and COMM consider the separation of information objects and information realizations [8], i.e., the separation of an information object like an image and its multiple realizations.
Sentence 2: it is not fully supported in FRBR as the annotations can only be applied on the in­formation objects.
Relationship: contrasting
Domain: Security and privacy
Sentence 1: In fact, for currently best-known TDP-based encryption methods, one either has to lose exact security [25] or has to pad the message to be longer than the length of the TDP [16].
Sentence 2: we com­mit to m once and then apply a deterministic, length-preserving Feistel Transform to obtain the required w and s. Moreover, we are guaranteed to always obtain tight exact security.
Relationship: contrasting
Domain: Security and privacy
Sentence 1: As we discuss below, websites often serve lo­calized and/or personalized content, making it non-trivial to form a consensus of a retrieved webpage even in the absence of an adver­sary.
Sentence 2: by verifying content rather than certi.cate .nger­prints, Senser does not rely on SSL/TLS or the web s PKI and is thus compatible with sites that do not support HTTPS.
Relationship: contrasting
Domain: Security and privacy
Sentence 1: TIGHT KEY ENCAPSULATION FROM SELECTIVE-ID IBE It is easy to turn our CCA2-secure encryption system into a CCA2-secure Key Encapsulation Mechanism (KEM).
Sentence 2: we can get a simpler construction with a tight secu­rity reduction if we take the lesser requirements of the KEM to our advantage and start from the Boneh-Boyen IBE [3].
Relationship: contrasting
Domain: Security and privacy
Sentence 1: FromSpeculation toSecurity: Practical andEf.cientInformationFlow TrackingUsingSpeculativeHardware HaiboChen ,XiWu ,LiweiYuan ,BinyuZang ,Pen-chungYew , andFredericT.Chong§ ParallelProcessingInstitute,FudanUniversity Department ofComputerScience andEngineering,University ofMinnesota atTwin-Cities § Department ofComputerScience,UniversityofCalifornia atSantaBarbara Abstract Dynamicinformation .owtracking(alsoknownastaint tracking) is an appealing approach to combat various se­curity attacks.
Sentence 2: the performance of applications can severely degrade without hardware support for track­ing taints.
Relationship: contrasting
Domain: Security and privacy
Sentence 1: It could be argued that whenever a policy is satis.ed, the resource it protects must be disclosed.
Sentence 2: such a requirement would impinge on the agent s autonomy in determining what to disclose, and would lead to a potential need-to-know attack in the other direction: a client could send all of its credentials and then wait to receive a list of resources for which it has satis.ed the policies.
Relationship: contrasting
Domain: Security and privacy
Sentence 1: There exists certainly many di.erent classi.cation algorithms that are able to map multiple input features to multiple output classes, even for complex, non-linear mappings, such as Support Vector Ma­chines, Arti.cial Neural Networks, etc.
Sentence 2: we are con­fronted to speci.c constraints that do not allow us to use this type of supervised machine learning techniques.
Relationship: contrasting
Domain: Security and privacy
Sentence 1: If the execution path is de­tected, the adversary will have some con.dence that the detecting attacker instance is co-located with the victim.
Sentence 2: this approach may have false positives, in which not-co-located instances were reported as co-located due to activities of other tenants sharing the same OS, and false negatives, in which co-located instances were not reported so.
Relationship: contrasting
Domain: Security and privacy
Sentence 1: Following [34], protocols secureinthepresence ofsemi-honest adversaries assume that parties faithfully follow all protocol speci.cations and do not misrepresent any information related to their inputs, e.g., size and content.
Sentence 2: during or after protocol execution, any party might(passively) attempttoinferadditionalinformation about other party s input.
Relationship: contrasting
Domain: Security and privacy
Sentence 1: For malware detection, it is used to mine the system call dependency graphs [12].
Sentence 2: when such a system is deployed for analyzing new executables, searching for exact subgraphs could be a brittle approach LEAP will not iden­tify malicious behavior if it does not correspond to a graph it has seen before (a slight change in the graph may be enough to avoid detection).
Relationship: contrasting
Domain: Security and privacy
Sentence 1: MOV ECX,200 XCHG EAX,ECX LOOP -1 Listing 1: SUB with LOOP instruction At .rst glance, this loop may seem entirely pointless, sim­ply exchanging the values of EAX and ECX at every iteration and decreasing the value of ECX.
Sentence 2: because ECX con­stantly witches between containing the actual loop counter and the value of EAX, the latter is actually decremented by the former until either of them reaches the value 0.
Relationship: contrasting
Domain: Security and privacy
Sentence 1: This is similar to the common notion of second pre-image resistance of cryp­tographic hash functions.
Sentence 2: due to the time-bound of the software attestation scheme it is su.cient that ChkN ful.lls only a much weaker form of second pre-image resis­tance since we need to consider only blind adversaries who (in contrast to the classical de.nition of second pre-image resistance) do not know the correct response rN to the ver­i.er s challenge (g0, r0).
Relationship: contrasting
Domain: Security and privacy
Sentence 1: We believe that the familiarity indications derived from the context should in the future be considered in combination with other fea­tures measuring also the trustworthiness of the devices in the user s proximity.
Sentence 2: we do feel that the notion of context familiarity provides a valuable tool on the way towards implementing functionalities that could adapt secu­rity policies dynamically according to the relevant context in which a mobile device is in at a speci.c point in time.
Relationship: contrasting
Domain: Security and privacy
Sentence 1: As a result, facilities must be provided for the operating sys­tem to identify the owner of data, and the security hashes of memory data must be available to the operating system, so that it may relocate data.Finally, the decomposition of complex functions into simple primitives, as in the case of register saves and restores, allows the operating system to better control resource usage.In the case of XOM Key Table management, the act of allocating a resource can be privileged, and thus decoupled from the act of accessing the resource, which remains unprivileged.
Sentence 2: our preliminary performance numbers look promising.The hardware overheads are not small with memory encryp­tion and decryption costing 15 cycles and saving and restor­ing a protected register requiring 13 instructions instead of 2.these costs are only incurred when the machine must do an even more expensive operation either a mem­ory fetch (which takes 150 cycles) or a trap into the kernel.
Relationship: contrasting
Domain: Security and privacy
Sentence 1: Also, we design originator related roles and collaborator roles that are resource shar­ing speci.c, in order to re.ect the special characteristics of an originator as well as to accommodate an originator s col­laborative sharing domain on the given resources.
Sentence 2: as an extension to the traditional RBAC per­mission assignment, our framework allows the originator to delegate usage and dissemination capabilities through the capability-role assignment.
Relationship: contrasting
Domain: Security and privacy
Sentence 1: The author investigated the resilience of commonly known aggregation functions and found that the average, the minimum and the maximum calculations are not resilient even against only one compromised node.
Sentence 2: the median was found to be resilient, the count to be acceptable and the trimmed average to be employable in some cases, namely when an upper bound on the percent­age of compromised nodes is known.
Relationship: contrasting
Domain: Security and privacy
Sentence 1: When a new SP is created, the Pro­.leRegister stores the SPde.nition in thePro.leStore and it also registersthe context expressions associated withtheSPintheCon­textExpressionDB.In this way, the newSP canbe activatedif the Context Detector evaluates to true the context expressions associ­ated with it.
Sentence 2: in MOSES, each SP has assigned an owner that is the entity authorised tode.ne and modify theSP.The owner of an SP canbe the user of thedevice that createsher ownSP.a user can deploy on her device SPs de.ned by third-parties.
Relationship: contrasting
Domain: Security and privacy
Sentence 1: Since J would thus use three blockcipher calls per message block, one might naively expect a 50% slowdown.
Sentence 2: eME computes various o.sets that are addedto theblockcipherinputs and outputs, and these com­putations are quite costly, so our simple ECB pass is less expensive compared to EME than one might imagine.
Relationship: contrasting
Domain: Security and privacy
Sentence 1: (If a hash func­tion produces n-bit digests, then one can surely obtain a collision by applying the hash function to 2n + 1 distinct inputs; and one can obtain a collision with high probability by applying the hash function to 2n/2 inputs.)
Sentence 2: suppose that M1,M1 are such that 0nt starting from IV and T1 = T2 = , they produce the same value for C(1) but not necessarily the same value for (1) (1) (1) (1) (1) (1) T1 ,T 2 , i.e., (T1 ,T 2 ) = ((T1 ) , (T2 ) ).
Relationship: contrasting
Domain: Security and privacy
Sentence 1: The client side aspect of the problem has been typically handled assuming a symmetric approach (based on access control rules) for regulating the release of user private information, and possibly enabling the client to engage in negotiation with the server.
Sentence 2: access control-like speci.cations do not completely .t the possible protection requirements at the client side, where users need approaches to express in an intuitive and easy to use way their natural perception of the privacy value of their infor­mation.
Relationship: contrasting
Domain: Security and privacy
Sentence 1: One thing to note is that in .gure 6, a virus can quickly infect the entire smartphone population in less than 3 hours, based on the mobility pattern in [36].
Sentence 2: the proxy can always catch the infection attempt (P(detection) = 1.0), our proposed solution can limit the number of infected users to 222, which is only 0.222% of the population.
Relationship: contrasting
Domain: Security and privacy
Sentence 1: Based on the Nyquist frequency, a camera that captures X frames per sec­ond is limited to X/2 bits per second when using an on/off encod­ing scheme.1 We could add multiple LEDs to encode more bits per frame.
Sentence 2: the user would have to pay careful attention to how the laptop is positioned within a trusted location to ensure the LEDs are easily differentiable so the laptop can successfully decode m. Instead, we design key derivation protocols which are 1TheLEDon is a 1.
Relationship: contrasting
Domain: Security and privacy
Sentence 1: 6.1 Stolen phone tracing and self-destruction Recently, lawmakers in California have approved a bill, which requires all smart phones sold in the state to have anti-theft software installed, so that once the device being lost or stolen, it cannot be used any more, even after a hard reset [16].
Sentence 2: in order to achieve that goal, the .rst step is to uniquely identify a device.
Relationship: contrasting
Domain: Security and privacy
Sentence 1: Consequently, compared to signal strength and carrier sensing time, PDR is a powerful statistic in that it can be used to di.erentiate a jamming attack from a congested net­work scenario, for di.erent jammer models.
Sentence 2: it still cannot di.erentiate the jamming attack from other network dynamics that can disrupt the communication between the sender and the receiver.
Relationship: contrasting
Domain: Security and privacy
Sentence 1: That is, two sessions with adversary interference under a cross-message attack [25] are de.ned to be matching.
Sentence 2: from our view, in light of the cross-message attack [25](that causes role con­fusion between two matching sessions for role-independent IA-DHKE), such a de.nition of matching sessions is ill , as it does not well capture the intuition of intended communi­cation partners without adversary interference.We notice that, for robust (H)MQV and KEA that are role-dependent as ( B) are involved in a .xed order in session-key deriva- A, tion, the more natural de.nition of matching sessions, where the two players are required to have matching roles,is used ACMIMadversary controls all the communication A channels among concurrent session runs of the KE protocol.
Relationship: contrasting
Domain: Security and privacy
Sentence 1: Predictive mitigation can address even dif.cult low­level timing channels such as those createdby hardware contention at the level of the processor or the bus, as long as the mitigator isabletodelayexternally visibleeventsto preciselythetimepre­dictedby the schedule.
Sentence 2: the very generality of predictive mitigation can make the leakage bounds conservative, and performance of the system is then hurt because the mitigator excessively delays the release of events.
Relationship: contrasting
Domain: Security and privacy
Sentence 1: Further examination showed that since our PC microphone in­cludes noise cancelation algorithm, the vibrations were hard to de­tect in recordings taken from 4 ft away and farther (as the vibra­tions were regarded as noise by the microphone).
Sentence 2: when investigating the IMD eavesdropping, we were able to utilize a parabolic microphone to distinguish between recordings of the piezo beep taken from a distance of 12 ft away.
Relationship: contrasting
Domain: Security and privacy
Sentence 1: Consider the example in Figure 2 from Line 15 to 18 of P 1,in which min(a, b, c) is computed by .rst comparing a and b to .nd the smaller one and then comparing it with c. These opera­tions are embedded in the loop from Line 2 and 7.
Sentence 2: an interesting observation is that if c is tainted, the .rst iteration of the loop only taints the statement at Line 17 and array D. the next iter­ation sees the statement at Line 16 also become tainted because this time, D is tainted.
Relationship: contrasting
Domain: Security and privacy
Sentence 1: We focus on bit.ly URLs since bit.ly offers an API [6] for querying the number of clicks received by every bit.ly link; thus our estimate of the number of clicks received by every application is strictly a lower bound.
Sentence 2: each bit.ly link that we consider here could potentially also have received clicks from other sources on web (i.e., outside Facebook); thus, for every bit.ly URL, the total number of clicks it received is an upper bound on the number clicks received via Facebook.
Relationship: contrasting
Domain: Security and privacy
Sentence 1: Upon detection of a malicious software on any one of these three hosts, one can proactively quar­antine the other two nodes without affecting messaging in the other clusters.
Sentence 2: if one quarantines the cluster with nodes (denoted in black circles) completely from the rest of the net­work, the total cost of quarantine will be the sum of messages ex­changed along overlapping edges e3,5, e4,13 , e7,13 , e13,15 , and e5,14 .
Relationship: contrasting
Domain: Security and privacy
Sentence 1: We note in passing that there exist low-cost (relying on symmetric key techniques) anonymous authen­tication protocols in the literature, for example Song and Mitchell s RFID protocol [50], that may be adopted to ad­dress our privacy concern.
Sentence 2: using such a solution provides only partial privacy protection because of the fun­damental limitations of a symmetric key approach [30, 45].
Relationship: contrasting
Domain: Security and privacy
Sentence 1: For example, from Ex­ample 1, it may appear, at .rst sight, that Dave s lack of authoriza­tion, as a consequence of his blacklisting, is inconsistent with Bob s intention to sell to Dave.
Sentence 2: it should be clear here that the speci.c information about Dave s lack of authorization overrides the general intention that Bob has to supply bangles.
Relationship: contrasting
Domain: Security and privacy
Sentence 1: The rule [Opt] corresponds to optimistic sampling, which allows substituting e. rby r 1Probability tags increase the readability of rules and sup­port a more uniform interpretation of judgments.
Sentence 2: they are super.uous and can be deduced from the shape of the event: for every valid judgment Fp c * : f, the probability tag pis 1/2 i. f= Guess.
Relationship: contrasting
Domain: Security and privacy
Sentence 1: The authors relate observational equi­valence to random variables and use Shannon entropy to quantify the information .ow.
Sentence 2: their measure cap­tures the information gain of a passive observer instead of an active attacker: the public input to the system is chosen 2The computation of <8(2) for .nite-.eld exponentiation took 40 minutes on a 2.4 GHz machine with 3 gigabytes of RAM.
Relationship: contrasting
Domain: Security and privacy
Sentence 1: Authenticated Multicast Immune to Denial-of-Service Attack* Shouhuai Xu Ravi Sandhu Laboratory for Information Security Technology SingleSignOn.Net, Inc. Reston, VA, USA George Mason University and MSN 4A4, University Dr., Fairfax, VA 22030, USA George Mason University, Fairfax, VA, USA sxul @ gmu.edu sandhu @ gmu.edu ABSTRACT Authentication of multicast streams has attracted a lot of at- tention in the last few years.
Sentence 2: two important issues, namely multicast denial-of-service and access control, have been ignored in previous proposals.
Relationship: contrasting
Domain: Security and privacy
Sentence 1: 5.7 Limitations Our work only examined high-pro.le IdPs and the 96 RPs in English that we found in the top 1,000 most-visited sites, and hence the evaluation results might not be generaliz­able to all IdPs and RPs.
Sentence 2: our statistical analysis did not reveal any correlation between websites popular­ity rankings and the discovered vulnerabilities.
Relationship: contrasting
Domain: Security and privacy
Sentence 1: More seriously, given reliable delivery noti.cation, a process could leak information using careful label changes, for ex­ample causing successful delivery to correspond to 1 bits and un­successful delivery to 0 bits.
Sentence 2: since only label checks (and resource exhaustion) will cause messages to be dropped, careful compartment management such as our Web server s can make delivery reliable in practice.
Relationship: contrasting
Domain: Security and privacy
Sentence 1: The simplest solution to this problem is to use on-line e-cash: the seller consults the bank during every transaction to ensure the promised e-coin is new.
Sentence 2: this approach places a heavy burden on the bank and compromises the privacy of the user (if a fair ex­change fails, new e-coins can be linked to old ones), and thus is not preferable.
Relationship: contrasting
Domain: Security and privacy
Sentence 1: Simi­larly, the .rst execution of a program that decrypts e(m) will traverse the states q0,...,qj ,qj+1, where qj+1 is the state that results from a successful decryption.
Sentence 2: return­ing the machine to its initial state q0, using the same instruc­tions r, the state traversal will be q0,...,qj ,q j' +1 .qj+1, = because the decryption fails.
Relationship: contrasting
Domain: Security and privacy
Sentence 1: As general purpose functions like MD5 or SHA1 were designed to be fast and e.cient, they serve in favor of the attacker who wants to compute a large number of digests in a short amount of time.
Sentence 2: adaptive hash functions, such as bcrypt [48] and scrypt [47], can be con.gured in terms of the work factor they introduce.
Relationship: contrasting
Domain: Security and privacy
Sentence 1: There are many construc­tions of leakage-resilient primitives in this model, including stream ciphers, symmetric key encryption, signatures, pub­lic key encryption, and identity-based encryption [1, 2, 3, 11, 15, 33, 41].
Sentence 2: assuming that leakage is bounded throughout the lifetime of the system seems unrealistic, since there is no bound a priori on the number of computations that will be performed.
Relationship: contrasting
Domain: Security and privacy
Sentence 1: The .rst approach at such a positive security result was taken for the WS-Federation Passive Requestor Interop (WSFPI), a Browser/POST pro.le of WS-Federation, in [11].
Sentence 2: this proof is built on top-down assumptions about the participating par­ties, i.e., assumptions made to suit the speci.c proof, in particular the browser and user, and not on a detailed, reusable model of these parties.
Relationship: contrasting