sadat2307/MSciNLI huggingface dataset:
Domain: Security and privacy
Sentence 1: ,.n=mn, that the following equation is correct: v(x0)=.1.1(x0)+.2.2(x0)+...+.n.n(x0).
Sentence 2: the solution without repetitions for the input (.F(x0), v(x0)) is the subset of the elements of .F(x0), the sum of which is equal to v(x0): .
Relationship: entailment
Domain: Security and privacy
Sentence 1: Since the .rst part of the simulation is , and then it computes perfect by assumption, and the second part is perfect by de.nition, hs1 Hs2 R = and sends R to V. *P(a) chooses blinding factors .Zss1 2 R, q it follows that the entire simulation is in fact perfect.
Sentence 2: *Zq the above simulation strategy establishes that, if SPK4 is honest­veri.er perfect zero-knowledge, then so is all of SPK2, even when the user reuses its blinding factors across all parallel instances in SPK5.
Relationship: entailment
Domain: Security and privacy
Sentence 1: We note, however, that the line between worms and viruses is not all that sharp.
Sentence 2: the contagion worms discussed in Staniford et al [47] might be considered viruses by the de.nition we use here, though not of the traditional form, in that they do not need the user to activate them, but instead they hide their spread in otherwise unconnected user activity.
Relationship: entailment
Domain: Security and privacy
Sentence 1: 1.2 Related Previous Work Research on oblivious simulation of one computational model by another began with Pippenger and Fischer [18], who show that one can obliviously simulate a computation of a one-tape Turing machine computation of length N with an two-tape Turing machine computation of length O(N log N).
Sentence 2: they show how to perform such an oblivious simu­lation with a computational overhead that is O(log N).
Relationship: entailment
Domain: Security and privacy
Sentence 1: AVMV represents the set of authorization views such that for each intentional relation Q de.ned in terms of AVMV , there exists an intentional re­lation Q" de.ned in terms of MV and an intentional relation Q"" de.ned in terms of AVAV such that Q.Q" and Q.Q"".
Sentence 2: for any database instance I, I(Q) is a subset of I(Q") and a subset of I(Q"").
Relationship: entailment
Domain: Security and privacy
Sentence 1: AE4 AE3 = AE2 AE4 = Salary> 400 r4 AE5 = Age > 60 r5 Not related to any attribute expression AE  AE AE AE AE Figure 2: A directed graph representing relation in table 2 One can argue that attribute expressions 2 and 3 are logically equivalent and should be consolidated in one equivalent class.
Sentence 2: one of these attributes expressions, say AE3 should be deleted as is the case in figure (3).
Relationship: entailment
Domain: Security and privacy
Sentence 1: The major weakness of group signature schemes is that in order to solve possible disputes at a later time, they give the group manager the unnecessary ability to trace any user even if there are no disputes.
Sentence 2: group signa­ture schemes provide only partial anonymity to the signer, and are not suitable for scenarios where users have privacy concerns, e.g., peer-to-peer networks.
Relationship: entailment
Domain: Security and privacy
Sentence 1: Software fault isolation with API integrity and multi-principal modules Yandong Mao, Haogang Chen, Dong Zhou , Xi Wang, Nickolai Zeldovich, and M. Frans Kaashoek MIT CSAIL, Tsinghua University IIIS ABSTRACT The security of many applications relies on the kernel being secure, but history suggests that kernel vulnerabilities are routinely discov­ered and exploited.
Sentence 2: exploitable vulnerabilities in kernel modules are common.
Relationship: entailment
Domain: Security and privacy
Sentence 1: This security collaborative communicates the how, what, when, who, and why of information security to our students, faculty members, administration, and staff, as well as others who are granted access to WVU data and technology resources.
Sentence 2: the collaborative  provides the knowledge and understanding necessary to identity and properly respond to security risks;  articulates individual roles and responsibilities for protecting data and information resources; and  emphasizes proactive, security conscious behavior.
Relationship: entailment
Domain: Security and privacy
Sentence 1: P1,..., Pn, L1,...,Lp and C1,...,Cm are sets of conditions that are dis­joint, in a pca rule, ., and any of these sets may be empty in .. Once a category c has been de.ned by a policy author a, a s de.nition of c can be used by any number of other policy authors.
Sentence 2: if a asserts that a principal p is assigned to a category c then any policy author that suf.ciently trusts a s categorization of p as one of a s c s can refer to that category in its speci.cations of access control requirements.
Relationship: entailment
Domain: Security and privacy
Sentence 1: The user also commits the score related to each of his past K transaction identi.ers: C(st1 ), C(st2 ),..., C(stK ).
Sentence 2: for each value a for a = 1 to K, the user proves to the SP one of the following is true: Transaction with identi.er ta is unjudged: C(sta ) is a commitment of score 0 and C(ta)C(-jp) is a com­mitment of a value within the range 1 to N. 1 = ta - jp = N;  Transaction with identi.er ta is judged with score sta : the user has a signature sta,sta on a tuple (ta,sta ), and C(ta) and C(sta ) are commitments of ta and sta .
Relationship: entailment
Domain: Security and privacy
Sentence 1: To this aim, a speci.c ontology of concepts (accessiblebythe RequestContext) has been created to map derived attributes to elementary ones, and to identify the correct Java function to be applied for their evaluation.
Sentence 2: getSpecialFunctionResult : i) retrieves all the attributes needed for the evaluation (line 8), ii) checks if some of these attributes are derived, and, if so, recursively applies itself (lines 12-13), iii) identi.es, via Java re.ection, the Java function tobe invoked for the evaluation of the derived attribute (lines 26-27).
Relationship: entailment
Domain: Security and privacy
Sentence 1: We adopt the Jaccard similarity coef.cient [17] to compute the similarity between S1 and S2, denoted Sim(S1,S2).
Sentence 2: sim(S1,S2)= a ,where a is the number of predi­ a+b+c cates in both S1 and S2, b is the number of predicates only in S1, and cis the number of predicates only in S2.
Relationship: entailment
Domain: Security and privacy
Sentence 1: Close inspection of the following three items indicated that no one respondent provided contradictory responses to these items.
Sentence 2: no one responded "strongly agree" to all three of the following: a) I would prefer to use biometrics over passwords or tokens b) I would prefer to use passwords over biometrics or tokens c) I would prefer to use tokens over biometrics or passwords Our resulting dataset of 115 responses was then used to do a factor analysis.
Relationship: entailment
Domain: Security and privacy
Sentence 1: ADVERSARIAL MODELING A prerequisite to building a secure RNG system is to understand how the underlying entropy source behaves in the presence of be­nign or malicious changes in the context the system is deployed in.
Sentence 2: it is important to determine whether or not the min­entropy of the output distribution of the source is affected under different operating conditions, and if so, to what level.
Relationship: entailment
Domain: Security and privacy
Sentence 1: 2) How to realize a tamper-resistant TBGP such that it can guar­antee the integrity execution of route attestation algorithms and rules, and thus preserve the consistency of routing control-and data-plane?
Sentence 2: can we ensure that a TBGP router cannot pretend to be a trusted one if the system is compromised, e.g., the route attestation service is disabled or routing control-and data-plane are not consistent?
Relationship: entailment
Domain: Security and privacy
Sentence 1: It may optionally at this point also update the Shunt device s tables to of.oad similar decisions in the future.
Sentence 2: the Analysis Engine must understand that the Shunt hardware is a cache: if a connection is of.oaded to the Shunt, the Analysis Engine must still maintain state for the connection, since it may be necessary to .ush the cache entry and return to diverting the connection s traf.c through the Analysis Engine.
Relationship: entailment
Domain: Security and privacy
Sentence 1: We also acknowledge the support of ALSTOM Schilling Robotics and SGI.
Sentence 2: we thank the members of the SCI Institute at the University of Utah, the Center for Applied Scienti.c Computing (CASC) at LLNL, the Computer Graphics and CAGD Research Group at Kaiserslautern, and the Center for Image Processing and Integrated Computing (CIPIC) at UC Davis for their support and many vivid research discussions.
Relationship: entailment
Domain: Security and privacy
Sentence 1: Thus, whenever we access a cell with index i, we actually perform a request for (an encryption of) this cell s contents using the obliviousness mechanism provided by B(N).
Sentence 2: to implement a standard or de-amortized cuckoo hashing scheme using B(N), we assume now that every (non-dummy) key in Alice s simulation is an index in the memory used to implement the hashing scheme.
Relationship: entailment
Domain: Security and privacy
Sentence 1: The startup time of WinAmp is much higher than that of other test applications because the number of .le access redirections overh the network is much higher (214) than others, as shown in Ta­ble 2.
Sentence 2: winAmp requires accesses to 214 executable or con.guration .les, which are fetched from the binary server at the initialization time.
Relationship: entailment
Domain: Security and privacy
Sentence 1: If the protocol satis.es our de.nition, the server will learn the average speed, say 30 mph, and nothing else.
Sentence 2: the server will not learn how manypeople passed through the street or whether there was an upload at 8:15 am (and hence whether Alicewenttowork).Moreover,the serverwillnotseetheindividual speed values uploaded so it cannot determine if there were some high speeds corresponding to Bob.
Relationship: entailment
Domain: Security and privacy
Sentence 1: Surprisingly, although the complexity of preprocessing time in the planar separator scheme is O(n 3/2 log n), it executes faster than the certifying algorithm (that has linear preprocessing time), because most of the work is non-cryptographic and can be imple­mented ef.ciently in regular C++ code.
Sentence 2: the planar separator scheme outperforms the certifying algorithm scheme in the preprocessing time by 29× on a graph with 10,000 nodes and it can scale to a graph with up to 200,000 nodes.
Relationship: entailment
Domain: Security and privacy
Sentence 1: We begin in the next section by considering the challenges to be considered when developing a generalized framework for system agility.
Sentence 2: we (a)explore the need and practice of hiding MTD behavior while sustaining system function, (b) consider hidden dependencies and impacts of MTD maneuvers on other systems, and (c) highlight the tradeoffs of MTD in terms of performance, function, and security.
Relationship: entailment
Domain: Security and privacy
Sentence 1: Nevertheless, identity-free routing only prevents a local inter­nal attacker from launching venue privacy attack VPA-a.As we describe below, the requirement of one-time packet content is needed to thwart venue privacy attack VPA-b and VPA-c. 3.3.2 One-time packet content In one-time packet content design, packet contents are com­putationally one-time.
Sentence 2: any two transmitted packets X.Y ,X ' .Y ' (i.e., packet sender s pseudonym is X or X ' , packet recipient s pseudonym is Y or Y ' ) are independent in the eyes of any node who is not X, X ' ,Y, Y ', that is, it is equally likely whether X = X ' or X = X ', also equally likely whether Y = Y ' or Y = Y ' .
Relationship: entailment
Domain: Security and privacy
Sentence 1: When HASTEN operates in active mode, it actively interferes with the execution of the binary.
Sentence 2: the tool at­tempts to force a stalling loop to exit (or, more precisely, to follow a code path that exits the whitelisted region that the previous analy­sis has identi.ed; this might force execution into parts of a stalling loop that have not yet been executed).
Relationship: entailment
Domain: Security and privacy
Sentence 1: Digital rights management systems, however, do not al­ways provide end-users of multimedia content with the expe­rience they have come to expect from older models of multi­media distribution.
Sentence 2: while many modern digi­tal rights management systems allow some restricted sharing of content amongst a small group of multimedia terminals, these systems lack the simplicity and .exibility formerly of­fered by physical media that could be easily transported between terminals, swapped amongst friends, stored in li­braries, and so on.
Relationship: entailment
Domain: Security and privacy
Sentence 1: For reasons stated earlier, the algorithm next tries to improve the merged network graph s access levels by utilizing newly added access edge esd and its corresponding hosts hs and hd as intermediates.
Sentence 2: hosts hs and hd and access edge esd are utilized by an indirect attack path that .nds them bene.cial in leveraging the path s access level at a target host.
Relationship: entailment
Domain: Security and privacy
Sentence 1: As shown in past work, one can use physical limitations on the speed at which a user may move and aggregate mobility models to de-obfuscate the mobility trace.
Sentence 2: we use the mobility trace to construct a Markovian mobility model built over all users: Pr(lt+1|lt), the probability that a user may be location lt+1 at time t +1 given that the user was at location lt at time t. We use the Markovian mobility model (built over all users) to en­rich per-user mobility traces.
Relationship: entailment
Domain: Security and privacy
Sentence 1: Sechduler Maintenance of the safety-critical infrastructures, e.g., nuclear power plants and avionics systems, is extremely crucial because a fail­ure to meet a single requirement may lead to a catastrophic conse­quence such as an explosion or an accident leading to loss of life.
Sentence 2: the realtime scheduling of tasks in those infrastructures such that individual timing requirements are met reliably is often a challenging endeavor.
Relationship: entailment
Domain: Security and privacy
Sentence 1: By using a type of anonymous authentication (e.g., group signatures) which allows the identity of the sender to be uncovered under ex­ceptional circumstances, abuse of the recommendation sys­tem service can be mitigated.
Sentence 2: if the TA observes an unusually high volume of contributions that do not align with already stored data, a large number of submissions for thesame(j, k) pair, or a number of extreme scores for the same physician that contradict the existing scores, the TA can provide the authentication records associated with the submissions to the CA who can then uncover the identity of the o.ending user(s).
Relationship: entailment
Domain: Security and privacy
Sentence 1: In this position paper, we argue that taking an ecological ap­proach to malware defense will suggest new defenses.
Sentence 2: we can exploit the fact that interactions of malware with its envi­ronment, and with other malware, are neither fully predictable nor fully controllable by the malware author yet the emergent behav­ior will follow general ecological principles that can be exploited for malware defense.
Relationship: entailment
Domain: Security and privacy
Sentence 1: The corresponding detection function f is given by X f(x)= (f(x),w) + b = fs(x) · ws + b. s.S and returns the orientation of f(x) with respect to the hy­perplane.
Sentence 2: f(x) > 0 indicates malicious activity in the report x and f(x) = 0 corresponds to benign data.
Relationship: entailment
Domain: Security and privacy
Sentence 1: No adversary running in time at most T can generate a (signature, set element, public key) triple that passes veri.cation, except with probability at most E. The above de.nition of a set-membership proof scheme may be modi.ed to include ancillary information about the set.
Sentence 2: the signing algorithm may be modi.ed to include this ancillary infor­ mation about the set as input.
Relationship: entailment
Domain: Security and privacy
Sentence 1: Dynamic vs. static approaches have historically suffered a com­patibility vs. performance trade-off.
Sentence 2: the dynamic approaches can currently handle a much larger class of binaries than the static ones, including large-scale COTS applications, but at the expense of signi.cant runtime overheads (e.g., 70% slowdown in Strata [32]).
Relationship: entailment
Domain: Security and privacy
Sentence 1: 3.3 Security Considerations The traitor tracing schemes presented in this section re­quire state-of-the-art obfuscation and tamper-resistant tech­niques.
Sentence 2: if the value of dID is recovered then the knowledge of sID enables the reconstruction of the private decryption key d as R(sID,dID).
Relationship: entailment
Domain: Security and privacy
Sentence 1: We then create the public key PK(I) as if the global secret key where SK' = (A', B') rather than SK = (A, B).
Sentence 2: we set y~ =" g Al(O) .g,B'(O), h~ ~ gA'(ze) .gIB'(ze),~ : 1 ...V, and let PK(I)-~ (y', h~,..., h;) (we omit fixed g, g', etc.).
Relationship: entailment
Domain: Security and privacy
Sentence 1: Figure 3 shows such an example, a signedness bug in crypt_blowfish that does not anticipate input that contains 0x80 characters with the most significant bit set (e.g., Unicode strings); this bug would make keys easier to crack.
Sentence 2: *ptr is of type char, which is interpreted as a signed integer type on many platforms; converting the value to unsigned int is a sign-extension, which should have been a zero-extension.
Relationship: entailment
Domain: Security and privacy
Sentence 1: I mean it was probably, I read something about like easy tips to safeguard your phone or something (P7) Our results indicate that most users actively enable locking mech­anisms on their devices due to speci.c privacy and security con­cerns, whereas a minority will do so when prompted and will con­tinue to do so, even if they see it as a nuisance.
Sentence 2: most users see locking as a valuable feature.
Relationship: entailment
Domain: Security and privacy
Sentence 1: At the same time, an attacker that has compromised the user s password for S is unable to access that account as he is lacking the pass­word for vouching service V and thus cannot complete the authentication process.
Sentence 2: for an attacker to compromise one account, he must acquire multiple account passwords for that user located in di.erent databases of dis­tinct services.
Relationship: entailment
Domain: Security and privacy
Sentence 1: Our basic idea is to create several new user accounts, one for each ring, so we can use the database s user-based access control.
Sentence 2: in our MySQL im­plementation, for the dbuser account, we create accounts dbuser_0, dbuser_1, and dbuser_2 (assuming there are only three rings), with dbuser_t corresponding to ring t. We then use MySQL s GRANT command to grant each dbuser_t the database-access privileges entitled to ring t. This is achieved by the database administrator from inside the database.
Relationship: entailment
Domain: Security and privacy
Sentence 1: A strong key, for our purposes, is a key independently sampled from a distribution over the set of possible keys that has at least k - polylog(k) bits of min-entropy, where k is the security parameter.
Sentence 2: a device generates strong keys if the probability that the device will generate a particular public key pk is at most 2-(k-polylog(k)) for all public keys pk.
Relationship: entailment
Domain: Security and privacy
Sentence 1: 3.2.1 Adding New Responses When the PDP allows a request (s, o, a, c, i), we can add further information to the dominance graph.
Sentence 2: we may add a new node for s or o if they do not already exist in the graph, and we may add an edge from s to o if a involves reading o (a is read or write), or from o to s if a involves writing to o (a is append or write).
Relationship: entailment
Domain: Security and privacy
Sentence 1: [1,n] constitute Shamir sharing of the secret committed in Coms with threshold t. For this, the parties use the fact that given the commitments to at least t + 1 distinct points on a t degree poly­nomial, it is possible to (homomorphically) compute the commit­ments of the coef.cients of the polynomial [14, 26].
Sentence 2: party Pi takes Coms along with {Comsj }j.
Relationship: entailment
Domain: Security and privacy
Sentence 1: Within such a family, 1609.2 deals with the issues related to security services for applications and management messages.
Sentence 2: the IEEE 1609.2 standard defines the use of PKIs, CAs and CRLs in VANETs, and implies that in order to revoke a vehicle, a CRL has to be issued by the CA to the RSUs, who are in charge of sending the information to the OBUs.
Relationship: entailment
Domain: Security and privacy
Sentence 1: In such sys­tems, the thesis is that if each node can be associated with a vir­tual coordinate in an appropriate space, distance between nodes can be trivially computed without direct measurement.
Sentence 2: as long as a reasonably accurate position for a node can be obtained with little effort, much of the distance measurement sam- 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: entailment
Domain: Security and privacy
Sentence 1: Our paper is complemen­tary to this previous work; our objective is to .lter out the third type of error.
Sentence 2: we aim to make the synopsis diffusion approach resilient to the falsi.ed local value attack and the falsi­.ed sub-aggregate attack, i.e., to enable the sink to get the true estimate of the aggregate being computed despite the presence of compromised nodes in the aggregation hierarchy.
Relationship: entailment
Domain: Security and privacy
Sentence 1: Let us consider the problem of computing a publicly known aggregate function f for a variable x with data distributed among a set of caregivers {C1, C2,..., Ck} from sub-aggregates a1,a2, ..., an, pre-computed by the caregivers Ci.
Sentence 2: f(a1,a2, ..., an) is the aggregate value needed for the pub­licly known function f. In Section 4, we show how such aggregates can be combined to compute functions such as sample mean, sample variance, maxima, linear regression, and sample correlation.
Relationship: entailment
Domain: Security and privacy
Sentence 1: The amount of public information required by the scheme S ' depends on the number of elements of the f-covering set Pe.
Sentence 2: in the following we show that the larger the cardinality of Pe, the smaller the value of f. Given a sequence T of n elements and an integer f =1, Alon and Schieber [2] established upper and lower bounds on the minimum possible cardinality of an f-covering set for T. they considered the problem in a quite dif­ferent context, where the n elements of T belong to a given semigroup (S,.)
Relationship: entailment
Domain: Security and privacy
Sentence 1: The above vulnerabilities basically arise from the neces­sity of having complex instruments between the (immate­rial) essence of an electronic document (i.e., a sequence of bits) and what the document presents to the user.
Sentence 2: while traditional documents are directly observable [6], since they can be properly interpreted by humans us­ing their senses (e.g., viewing and touching the document) mediated only by their capability of understanding the in­formation represented in the document, this is highly false for electronic documents.
Relationship: entailment