sadat2307/MSciNLI huggingface dataset:
Domain: Security and privacy
Sentence 1: Now,letuslookatFigure2(c).Here,weseethatthereis nointervalinwhichtheGeneralDoctorrolecanbeenabled.
Sentence 2: sincetheactivationhierarchyisoftypeAw,any userassignedtotheGeneralDoctorrolecanactivateeither ofthejuniorroleswhentheyareenabled.Inefect,anyone assignedtotheGeneralDoctorrolecanactivateboththe DayDoctorandtheNightDoctorroleswhenevertheyare enabled.
Relationship: contrasting
Domain: Security and privacy
Sentence 1: These sys­tems, however, either make assumptions about the collected information (i.e., that it will not to leak the source iden­tity) [46], or require an algorithm to decide which data are safe to contribute, which may not be easy to devise [45].
Sentence 2: our system combines di.erential privacy and separate encryption of answer messages to protect against identity leakage through the data, without any assumptions or prerequisites.
Relationship: contrasting
Domain: Security and privacy
Sentence 1: A = Au,w, the set E = Eu,w contains strictly less than 1-4 ·10-4 fraction of the edges touching i in GT .
Sentence 2: note that since we demand a strict inequality, the claim also implies that A = f. We remark that the claim does not follow di­rectly from the fact that A contains no iteratively expensive indices with respect to either u or w. The latter implies that u satis.es at least 0.1 fraction of the edges touching i, and so does w. it may be the case that there is not even a single edge that they both satisfy.
Relationship: contrasting
Domain: Security and privacy
Sentence 1: We could have designed Update to recompute each component Kj " " ,even inthe case where kj " " = kj .= ., causing the key to be fully re-randomized no matter how small the update.
Sentence 2: the selective re­randomization strategy gives us amortized constant time for single-step updates, which the indiscriminate strategy does not.
Relationship: contrasting
Domain: Security and privacy
Sentence 1: While the incorporation of the TVD concept in data cen­ters [3, 5] can be expected to be available in the near fu­ ture, only few research prototypes address the realization on desktop systems [7].
Sentence 2: a practical and usable im­plementation of TVDs for end-users must focus on a secure desktop environment and the end-user experience.
Relationship: contrasting
Domain: Security and privacy
Sentence 1: As a .nal point of arca de.nitions, we note that a variety of dif­ferent interpretations of denials of access to categories of principals can be naturally accommodated in an extended form of M.Due to space limitations, we do not give the details of that here.
Sentence 2: it should be clear that a d_arca predicate (say) could be used to de­.ne denials of permission assignments to categories of principals in essentially the same way that we have used arca de.nitions (and with different interpretations of denials being admitted e.g., denials by intention, denials as physical constraints, etc.).
Relationship: contrasting
Domain: Security and privacy
Sentence 1: As shown in the .gure, the unprocessed signal at rx2 seems unrelated to the target message m1 due to the mixture of m1 and m2 plus lack of clock synchronization between transmitters and re­ceivers.
Sentence 2: after correcting CFO and gain via intact pilot subcarriers and removing the component of m2, the residual signal is found highly correlated to the target message m1.
Relationship: contrasting
Domain: Security and privacy
Sentence 1: Especially, the random uniform sampling schemes show a tendency to concentrate ciphertexts at the edges of R. To lower the probability of the responsible unbalanced recursions, the usage of alternative distributions to choose splitting elements and ciphertexts should be investigated.
Sentence 2: the observed sensitivity of all stud­ied OPFs construction schemes against known and chosen plaintext attacks, motivates the further investigation of al­ternative schemes achieving higher disclosure-resilience un­der such adverse conditions.
Relationship: contrasting
Domain: Security and privacy
Sentence 1: If we choose the conjunction, disjunction, im­plication method, and aggregation to be min(x,y), max(x,y), min(x,y), and max(x,y), respectively, the risk surface function, as shown in Figure 5, is different especially in some boundaries.
Sentence 2: the risk surface in Figure 5 seems to follow the rules in  risk 90 80 70 60 50 40 30 20 10 500 1000 object-security-label subject-security-label Figure 5: The surface using different operations Table 1 as well.
Relationship: contrasting
Domain: Security and privacy
Sentence 1: This license is signi.cant, as an array read or write could trig­ger a full re-permutation of the array representation, and the CVM can safely perform this without worrying about preserving the previous state of the permuted array.
Sentence 2: there is no requirement that a scalar value be linear a single gate s scalar value can be used by many subsequent gates, for example if multiple expressions refer to a single variable.
Relationship: contrasting
Domain: Security and privacy
Sentence 1: [21] detect heap-spraying attacks by inspecting the JavaScript string objects to identify shellcode using lightweight emulation [9].
Sentence 2: this type of approach have dif.culty in dealing with shellcode obfuscation techniques, such as, shellcode encoding [28, 34], encryption [46], polymorphism [20, 24], and other obfuscationschemes[17,27,31,37].
Relationship: contrasting
Domain: Security and privacy
Sentence 1: The tool .nds that performing a zero-higher-order bit fault on k after it is sampled is su.cient to guarantee the fault condition (as we then have k = k » i).
Sentence 2: we do not automatically .nd more complex attacks (that use proposi­tion 5) on the algorithms computing scalar multiplications and .eld element inversions.
Relationship: contrasting
Domain: Security and privacy
Sentence 1: Now by the indistinguishability of lossy and in­jective functions, the same must be true when f is replaced with a lossy function f'.
Sentence 2: f'(x) statistically hides the value of x, because there are on average about 2k =2n/2 '' other values xsuch that f'(x)= f'(x), and all are equally likely.
Relationship: contrasting
Domain: Security and privacy
Sentence 1: Pairing would be easy to achieve, if there existed a global infrastructure enabling devices to share an on-or off-line trusted third party, a certi.cation authority, a PKI or any pre-con.gured secrets.
Sentence 2: such a global infras­tructure may not be possible in practice, thereby making pairing an interesting and a challenging research problem.
Relationship: contrasting
Domain: Security and privacy
Sentence 1: In addition, our algorithm relies on an automated prover to simplify the intermediate conditions generated by weakest precondition computations; the prover is specialized to formulae that combine arithmetic inequalities and size constraints; such formulae include many fault conditions, in­cluding all those we explore in this paper (see Figure 7).
Sentence 2: our algorithm noticeably departs from recent works on program synthesis by its simplicity: indeed, phys­ical limits on the number and nature of faults su.ciently constrain the search space for faulted implementations, al­lowing us to dispense from using more elaborate techniques that are required to manage very large search spaces (see Section 6).
Relationship: contrasting
Domain: Security and privacy
Sentence 1: Have each signer prepend its pub­lic key to its message before signing, so that the individual signatures now are (in the MS case) on the enhanced mes­sages pk 1 I m,...,pkl I m. Now, security is guaranteed as long as the enhanced messages are distinct.
Sentence 2: this is not enough for security against rogue key attack in our plain public-key model.
Relationship: contrasting
Domain: Security and privacy
Sentence 1: Figure 5: Example policy with generated authorization and obligation constraints The approach is a good starting point for understanding the concept and the motivation for semantically-enriched attestation.
Sentence 2: one of the major drawbacks of the approach is that property-based attestation is delegated to a trusted third party, which is then respon­sible for setting up an attestation communication with the client platforms.
Relationship: contrasting
Domain: Security and privacy
Sentence 1: To preserve utility, we expect certain ag­gregate characteristics (a.k.a., feature) of the original graph should remain basically unchanged or at least some properties can be re­constructed from the randomized graph.
Sentence 2: as shown in Ta­ 9(a) .1 9(b) µ2 9(c) h 9(d) Modularity 9(e) Transitivity 9(f) Subgraph centrality Figure 7: Identity Protection K vs.
Relationship: contrasting
Domain: Security and privacy
Sentence 1: For this study, we .xed the Phishiness value of unknown tokens to 0.5, which is also equivalent to the default value of robx spec­i.ed by Robinson s constants in [10].
Sentence 2: we do not present all possible adjustments in this paper, as the goal is not to build an ideal classi.er, but rather limited to show the e.ectiveness of our approach in lexically analyzing URLs for discriminating phishing and legitimate URLs.
Relationship: contrasting
Domain: Security and privacy
Sentence 1: The harness hides all of these details, so the user needs only specify the computation itself, of type DPComp q r v, and a function acting as the differentially private mechanism of type q -> r. A variant of the harness can even accept a query function of the type q -> IO r, which may be appropriate in many cases.
Sentence 2: its invocations will be wrapped in unsafePerformIO, so the this function is re­sponsible for maintaining apparent referential transparency.
Relationship: contrasting
Domain: Security and privacy
Sentence 1: F1.php in Figure 1), know how trustworthy their data are, because they know where the data come from.
Sentence 2: when F1.php puts all the data together into one HTML page, and presents it to the client-side browsers, there is no systematic mechanism for the server to convey the data s trust state to browsers, so the trust state gets lost in the process.
Relationship: contrasting
Domain: Security and privacy
Sentence 1: To prevent identity and link disclosures, one natural approach is to publish a node-anonymized version of the network that per­mits useful analysis without disclosing the identity of the individ­uals represented by the nodes.
Sentence 2: as pointed out in [2, 12], this simple technique of anonymizing graphs by replacing the iden­tifying information of the nodes with random ids does not guaran­tee identity/link privacy since adversaries may potentially construct a highly distinguishable subgraph with edges to a set of targeted nodes, and then to re-identify the subgraph and consequently the targets in the released anonymized network.
Relationship: contrasting
Domain: Security and privacy
Sentence 1: We did not implement any of these countermeasures, because each seems to involve an unacceptable loss of usability to either bridge operators or bridge clients, compared with somewhat un­clear bene.ts in terms of privacy.
Sentence 2: we can sketch a so­lution based on the third point above: The goal is to ensure that the probability a user s bridge is serving is the same in case she is sur.ng and in case she is not.
Relationship: contrasting
Domain: Security and privacy
Sentence 1: More importantly, PREC achieves practicability by 1) raising 0 false alarm on the benign appli­cations without native code.
Sentence 2: traditional schemes without our classi.ed system call monitoring raise 67-92% per-app false alarms; and 2) reducing the false alarm rate on the benign applications with native code by more than one orders of magnitude over traditional anomaly detection algorithms: from 100% per-app false alarm rate (FSA) and 78% per-app false alarm rate (HMM) to 3.75% per-app false alarm rate (PREC).
Relationship: contrasting
Domain: Security and privacy
Sentence 1: Applying SybilLimit naively to the Byzantine Dissidents v 2 problem yields a protocol which costs O(nm) bandwidth to protect against a maximum of o(n/ log n) attack edges.1 Unfortunately, this is more costly than the simple .ooding protocol described above.
Sentence 2: the next section shows how to adapt the underlying techniques developed for Sybil-Limit to produce an ef.cient protocol for the Byzantine Dis­sidents problem.
Relationship: contrasting
Domain: Security and privacy
Sentence 1: We then discuss some possible solutions to the routing table vulnerability in processor-interconnect systems and their trade-o.. 6.1 Other Performance Attacks Coherence Message: In this work, the modi.cation of the routing tables focused on request and response packets.
Sentence 2: (a) (b) another important class of messages in processor­interconnect is coherence messages and in the Hypertransport­based system, the corresponding broadcast messages.
Relationship: contrasting
Domain: Security and privacy
Sentence 1: For instance, CRBAC [12], GRBAC[11],andTRBAC[2] extendedtheRBAC modelin order to take into account some context dimensions for re­stricting access permissions on resources.
Sentence 2: as with RBAC these models are not suitable to control access on resources in open and dynamic environments with frequent and unpredictable changes, which we cannot assume the ex­istence of prede.ned roles and user-role associations.
Relationship: contrasting
Domain: Security and privacy
Sentence 1: We intend to investigate this aspect further in the future by capturing real-world user traces that provide the necessary details to analyze the e.ects of various devices and their di.ering capabilities.
Sentence 2: we note that tech­nological trends point to increasing capabilities of personal devices, such as laptops, handhelds and PDAs, which in turn provide a rich set of capabilities for users to access .les in much the same way as they do from a desktop PC, such as a trusted corporate terminal.
Relationship: contrasting
Domain: Security and privacy
Sentence 1: Speci.cally, during the .rst ex­ecution of a program 2 that encrypts a message m, d will de.ne a transition from qi to qi+1 based on the primitive Enc(.i,qi,m).
Sentence 2: the second time, the key will be dif­ferent, and the state transition will be from qi to qi' +1.
Relationship: contrasting
Domain: Security and privacy
Sentence 1: The Ivy project aims to combine SafeDrive with Shoal [3] and HeapSafe [14], which should provide improved isolation when completed.
Sentence 2: this combinationwould stillbe missingBGI sdynamictypestate checking andit wouldlikelyperform worse thanBGIbecause both Shoal and HeapSafe can introduce a large overhead.
Relationship: contrasting
Domain: Security and privacy
Sentence 1: To provide such a joint signature and encryp­tion tool, Zheng [26] introduced signcryption as a primitive, and several subsequent papers provided alternate constructions and im­provements [27, 20, 14, 2, 1, 19].
Sentence 2: these existing sign­cryption proposals all leave something to be desired in the security properties they achieve.
Relationship: contrasting
Domain: Security and privacy
Sentence 1: Our model is closely related to the Refereed Games (RG) model of Feige and Kilian [10] where they focus on two unbounded com­peting servers and polynomial time referee/client.
Sentence 2: we are faced with the additional challenges of building protocols with ef.­cient honest servers, with a super-ef.cient client and for any num­ber of servers.
Relationship: contrasting
Domain: Security and privacy
Sentence 1: Not only can these lists be used in building fast-propagating worms [36], they can also be used for targeted attacks, e.g., an attacker looking to exploit a crit­ical infrastructure industry that may use common services, such as the .nancial services industry.
Sentence 2: the advent of botnets [7, 10, 33] and other forms of indirection have made it far more dif.cult to discover the true at­tack source, instead of bot machines which play a small role in the actual process.
Relationship: contrasting
Domain: Security and privacy
Sentence 1: 4.3 Alleviating cookie theft An intuitive way to stop cookie theft in Web-based at­tacks is to address XSS.
Sentence 2: despite many e.orts to prevent XSS, such as client-side approaches [25, 12], server­side approaches [35], or hybrid client-server approaches [23, 16], XSS remains the top vulnerability [4].
Relationship: contrasting
Domain: Security and privacy
Sentence 1: In terms of e.ciency, the Workers Computation Phase requires only (on top of the complexity of securely comput­ing f) 5 secure additions, 2 secure openings and the cost of computing Verk(x, t).
Sentence 2: as described above, given that the key k is public this can be done by generating a random shared value s and computing ß = s · (t - k · x).
Relationship: contrasting
Domain: Security and privacy
Sentence 1: asgndP(r,P ) r1.descendants(r,R,RH) The user-permission assignment UPA(p) induced by a hier­archical PRBAC policy p is de.ned by: authUP(r, U, P, R, RH ) = {(u, p) .
Sentence 2: authU(r, U, R, RH ) × authP(r, P, R, RH ) |u, p |= con(r)} UPA((U, P, R, RH )) = authUP(r, U, P, R, RH ) r.R In the de.nition of authUP(r, U, P ), all authorized users and permissions of r, including the inherited ones, are subject to the constraint associated with r. constraints are not inherited ; in particular, the constraint associated with a role r a.ects only r s contribution to the user-permission relation induced by the policy.
Relationship: contrasting
Domain: Security and privacy
Sentence 1: Notice that our experiment sends messages using spoo.ng, making them just as likely to be caught in a spam .lter as a message that is a component of a spoo.ng attack (such as the attacks described above).
Sentence 2: our message does not contain a malicious link (Figure 8(a)) thus it simu­lates only one of the features of a real phishing attack.
Relationship: contrasting
Domain: Security and privacy
Sentence 1: Presently in VisFlowConnect, the user can select from several hard-coded threshold values the minimum transfer rate that is required for a .ow to be displayed.
Sentence 2: this could easily be extended to allow the user to set one or more user-speci.ed transfer rate ranges to display or hide, allowing the user to more closely examine very high speed of very low speed transmissions.
Relationship: contrasting
Domain: Security and privacy
Sentence 1: When the privacy must be pre­served not only against a third party, but also against the parties that participate in the protocol where the inputs are shared, secure multiparty computation constructions can be used.
Sentence 2: when the problem requires pro­cessing noisy signals consisting of a large number of samples, typical multiparty computation protocols become too costly in terms of computation and communication complexity.
Relationship: contrasting
Domain: Security and privacy
Sentence 1: Moreover, if we increase the timing-interval t to greater than 100 packets, the regularity test observes a di.erent number of packets for each t value within each window,asthe setsof t packets overlap with the window at di.erent points, making the test less reliable.
Sentence 2: if we decrease the timing-interval t to much less than 100 packets, the regularity test observes a similar number of packets for each t value within each window and the variance for each window is similar, which makes the test more reliable.
Relationship: contrasting
Domain: Security and privacy
Sentence 1: The reason is that if Bob veri.es Alice s signature on a piece of data, and then the next week, Alice s signature key is compromised, it doesn t a.ect the fact that that old signature was valid.
Sentence 2: if an encryption key is used to protect a piece of data, and then the next week, the encryption key is compromised, that old data is no longer protected.
Relationship: contrasting
Domain: Security and privacy
Sentence 1: Finally, if a malicious insider at the metadata store also dis­tributes capability tickets, as is done in some systems, then it can be assumed that the adversary also has access to chunks; a malicious metadata store can simply issue itself a valid capability.
Sentence 2: without access to the map key, the adversary would not know which chunks correspond to a give .le, and would lack the key needed to decrypt a chunk.
Relationship: contrasting
Domain: Security and privacy
Sentence 1: 7.1 FPToncurrenthardwareisfundamentallybroken We have discussed a few solutions to contain the spurious taint propagation, but they are prone to false negatives, and only slow down the outburst of false positives.
Sentence 2: the problem is even more serious as there are undecidable cases when the (most common) hardware itself is not able clean dirty very dirty calc.exe IEXPLORE.EXE kd.exe msmsgs.exe svchost.exe explorer.exe winlogon.exe lsass.exe services.exe svchost.exe wuauclt.exe csrss.exe 0 200 400 600 800 1000 1200 1400 1600 1800 2000 Intervals Figure 9.
Relationship: contrasting
Domain: Security and privacy
Sentence 1: Towards an Analytic Model of Epidemic Spreading in Heterogeneous Systems Xiaohu Li T. Paul Parker Shouhuai Xu Department of Computer Science, University of Texas at San Antonio {xli,tparker,shxu}@cs.utsa.edu  ABSTRACT Mathematical models have been utilized to help understand the epidemic spreading of malicious codes (e.g., computer virus and worms).
Sentence 2: existing such models are either adapted from the ones developed to capture the epidemic spreading of biologically infectious diseases in homogeneous systems, or suitable only for a very speci.c class of hetero­geneous systems.
Relationship: contrasting
Domain: Security and privacy
Sentence 1: If an observing agent is not able to access its own memory while the program is executed, then the above program can be considered secure, since after termination the state of the untrusted agent is una.ected by the state of the trusted one.
Sentence 2: in several scenarios this requirement is not satis­.ed: (i) the observer controls a device that is mapped to a memory area that belongs to the untrusted agent, (ii) the code is interrupted and scheduled in a preemptive environ­ment, (iii) memory stores have side e.ects, or (iv) the code is executed in a multi-core setting.
Relationship: contrasting
Domain: Security and privacy
Sentence 1: RELATED WORK Mainly two kinds of cardinality constraints are often mentioned in the literature - user cardinality and role cardinality [6, 9, 15].
Sentence 2: our approach of using status predicate, an evaluation function and a projection operator to define cardinality constraints allows one to express cardinality constraints associated with all states - role enabling, user or permission assignment as well as activation time including session.
Relationship: contrasting
Domain: Security and privacy
Sentence 1: Compared to the arbiter PUF described in the previ­ous section, the RO PUF allows an easier implementation for both ASICs and FPGAs, an easier evaluation of the en­tropy, and higher reliability.
Sentence 2: the RO PUF is slower, larger and consumes more power to gener­ate bits than the arbiter PUF.
Relationship: contrasting
Domain: Security and privacy
Sentence 1: Copyright 2009 ACM 978-1-60558-630-4/09/0010...$10.00.. Automaton (DFA) is widely used for multi-string matching for its constant matching speed even in worst case.
Sentence 2: for charac­ter-by-character based matching algorithms, the throughput is strictly proportional to the memory access frequency.
Relationship: contrasting
Domain: Security and privacy
Sentence 1: Obviously, without the condition of finding the minimal set of roles, the simplest way to solve this problem is to first select one role from R1 arbitrarily (there are total n choices, assuming |R1|= n), then selecting another role from the rest of R1, and so on, until the selected set R' satisfies Pau(R') = RQ.
Sentence 2: with the minimal set of roles condition, the question becomes hard.
Relationship: contrasting