sadat2307/MSciNLI huggingface dataset:
Domain: Security and privacy
Sentence 1: O = ((S >> 16) ^ S) &#38; 0xffff; O= O | O << 16; Here there are 32 · 31/2 = 496 two-bit patterns on O to determine; the only interesting ones are that bits i and i + 16 must be equal, for 0 = i = 15.
Sentence 2: bits i and i + 16 can be (0, 0) or (1, 1), but not (0, 1) or (1, 0).
Relationship: entailment
Domain: Security and privacy
Sentence 1: For this purpose, it may be useful to decorate terms with additional type in­formation, so that proof-checking can be as straightforward as possible.
Sentence 2: such type information may help in applying the rule [BindM ] backwards with the rule in its present form, we have to guess A and s in order to .nd the  semantics of Simply Typed DCC is standard.
Relationship: entailment
Domain: Security and privacy
Sentence 1: Our study of setresuid() in prior work [12, 21] and the documentation for it in the three sys­ tems that support it [4, 5, 7] tells us that all of them specify the same semantics for it with respect to processes with and without appropriate privileges.
Sentence 2: even where the speci.cations for the function s behavior may di.er, they do not di.er for success and failure conditions for a process with appropriate privileges, or for a process without appropriate privileges.
Relationship: entailment
Domain: Security and privacy
Sentence 1: This is more general than Facebook-style SNSs, in which the social net­work is a simple graph [17].
Sentence 2: we denote by G(V, I) the set of all social networks de.ned over vertex set V andrelationindexset I.members of G(V, I) share the same vertex set V , but di.er only in the edges.
Relationship: entailment
Domain: Security and privacy
Sentence 1: Inthispaper,weprovideaformalizationofWindowsVista sin­tegrity model.
Sentence 2: we specify an information-.ow prop­erty called data-.ow integrity (DFI), and present a static type sys­temthatcan enforceDFIonWindowsVista.Roughly,DFIprevents any .ow of data from the environment to objects whose contents are trusted.
Relationship: entailment
Domain: Security and privacy
Sentence 1: If there is a safe disclosure sequence G=(C1,...,Ck,R) under the covering policies, then either there is also one under the original policies, or PC* is satis.ed by {C1,...,Ck}.
Sentence 2: after Ck is disclosed in the sequence, it is safe for Alice to tel l Bob that she does not possess C*.
Relationship: entailment
Domain: Security and privacy
Sentence 1: Thus, one solution to this problem would be to employ some form of irreversible state change in the usage mechanism for these certi.cates.
Sentence 2: what we need is some form of trusted mem­ory on Bob s machine (other than the untrusted and reversible hard disk) that is somehow changed irreversibly during the usage proto­col, such that it would be infeasible for Bob to revert his machine to a previous state.
Relationship: entailment
Domain: Security and privacy
Sentence 1: Moreover, all the deployment points need not be decided before deployment; therefore, we can deploy nodes on an ad hoc basis.
Sentence 2: we can move to any point, measure the current location, distribute keys to the node (according to the location and the pdf ), and deploy  1Actually, the area of selectable keys is slightly larger than the area of the possible resident points due to the in.uence Figure 6: Keys to be distributed to S of r, but for explanation purpose we ignore the di.erence.
Relationship: entailment
Domain: Security and privacy
Sentence 1: 2.2 GTRBAC The Generalized Temporal Role Based Access Control (GTRBAC) model is an extension of Temporal RBAC (TR-BAC) which is an RBAC extension to address temporal con­straints.
Sentence 2: gTRBAC model allows one to ex­press periodic and duration constraints on roles, user-role assignments, and role-permission assignments.
Relationship: entailment
Domain: Security and privacy
Sentence 1: The BBS algorithm works as fol­lows.
Sentence 2: giventwoprime numbers p, q, a factor n = p ×q, and a random number s (seed)such that s is relatively prime to n; meaning that neither p nor q is a factor of s. The pre­dictability of the numbergeneratedisbased on thedi.culty of factoring n, i.e., given n one needs to determine its two prime factors p and q. Duringthe secure authentication, everyEApresents a cer­ti.cate, whichisgenerated as apart of theSP.Asdetailedin [21], eachSP, amongothers,de.neand storeprincipaliden­tities,issuerof thecerti.cate, alegitimate evaluatorID,and a securitypro.le of agiven asset(orTOE).each asset is assigned a lightweight version of X.509 based SP containing evaluator s unique ID, evaluator s public key information,identityanddigital signature oftheissuer, time stamp, serial number, version, last evaluation date, period of validity, and digital signature algorithm (the algorithm is for signing the certi.cate).
Relationship: entailment
Domain: Security and privacy
Sentence 1: PRIVACY VIA SAFE FUNCTIONS Rather than hiding the shared access policies from the SCSs in the confederation, in this section we consider a so­lution in which all shared access policies are allowed to be publicly known, thereby accommodating the use of default policies.
Sentence 2: we ensure that the policies are safe, in the sense that even if a party obtains the output of the SMC protocol, it will not be able to deduce any information regarding the inputs to the function.
Relationship: entailment
Domain: Security and privacy
Sentence 1: A data owner has di.erent trust relationships with di.erent parties and he should be able to set the ac­cess control policies accordingly.
Sentence 2: we map the policy model of visibility policies to the following levels of access control: A1: for each tuple A2: for each party, all tuples corresponding to items that the party possessed A3: for each party, all tuples corresponding to items that the data owner previously possessed These levels are a subset of visibility policies [6] which havebeende.nedfor mobilephysical objects, such asgoods in a supplychain, and canbe enforced via authentication[8].
Relationship: entailment
Domain: Security and privacy
Sentence 1: The performance is measured in terms of the average required number of observation sam­ples, E[N] in order to derive a decision, which essentially denotes the delay in detecting a misbehavior instance.
Sentence 2: we evaluate the performance with respect to the following parameters:  Speci.ed values of PFA and PM (or probability of de­tection, PD =1 - PM).
Relationship: entailment
Domain: Security and privacy
Sentence 1: Forging for the same participant: (....,1,....,2, ··· ,....,.. ) .
Sentence 2: .. * after observing ..,... tags (....,1,....,2, ··· ,....,.. )fromthe ..-th participant, the adversary generates a ..,.. of the same forgery .. * party for some time interval .. .
Relationship: entailment
Domain: Security and privacy
Sentence 1: 4.2 STAC with state transitions Another STAC scenario we are interested in is where accessi­bility to the mapping does not only depend on the current location and time, but also on the mobile user s previous spatio-temporal characteristics.
Sentence 2: we want a stateful form of access control, where state is de.ned as being at a speci.c location in a speci.c time interval.
Relationship: entailment
Domain: Security and privacy
Sentence 1: To see this, note that as long as there is no wrap-around modulo q, f1f2(c1 + c2) (mod 2) = 2(f1f2(e1 + e2)+ f2g1s1 + f1g2s2) + f1f2(m1 + m2) (mod 2) = m1 + m2 (mod 2) and f1f2(c1c2) (mod 2) = 2(2g1g2s1s2 + g1s1f2(2e2 + m2)+ g2s2f1(2e1 + m1)+ f1f2(e1m2 + e2m1 +2e1e2)) + f1f2(m1m2) (mod 2) = m1m2 (mod 2) since f1 = 1 (mod 2) and f2 = 1 (mod 2).
Sentence 2: the joint secret key f12 = .
Relationship: entailment
Domain: Security and privacy
Sentence 1: To our knowledge, this is the only reported implementation that supports GF (2m) for variable .eld de­grees m. All other implementations described above target either one or a small number of speci.c curves.
Sentence 2: none of them can handle a curve that is not speci.ed at implementation time without requiring the software to be modi.ed or the hardware to be recon.gured.
Relationship: entailment
Domain: Security and privacy
Sentence 1: For example: The conversation requires a common language (including both vocabulary and sentence structure) They are a two-way conversation Both expect answers to questions asked Both expect answers to be given in a timely manner Both expect communications to be in the proper context.
Sentence 2: an answer should make sense given the question asked  All applications communicate via these types of electronic conversations , and any form of web application security must be capable of understanding all these conversations, and be able to distinguish one conversation from another while listening to both sides of every conversation.
Relationship: entailment
Domain: Security and privacy
Sentence 1: To avoid repeatedly searching the hierarchy tree for the same value during the shortest path computation, we pro­pose to assign each node a hierarchy code (Hcode), indicat­ing the position of each node.
Sentence 2: the root node is assigned an Hcode equal to 1 , and its children nodes are named in the order from left to right by appending their po­sition to the parent s Hcode with a separator .
Relationship: entailment
Domain: Security and privacy
Sentence 1: The type of hint received determines the amount of work a user must do to recover the session key, and thus whether or not the user is provided with a cue.
Sentence 2: a high-quality hint is given to the privileged users, a lesser quality hint is pro­ 1If a degraded user can modify their system so that the service degradation is unobtrusive we still view the system as successful because the act of modi.cation demonstrates they experienced the cue.
Relationship: entailment
Domain: Security and privacy
Sentence 1: {0, 1} identi.es Con.ict of Interest.
Sentence 2: c(Di, Dj ) = 1 if and only if Di Dj ,  = Di D[s], Dj D[s] and Di and Dj are in con.ict (i.e., = = in the same Con.ict of Interest class).
Relationship: entailment
Domain: Security and privacy
Sentence 1: Speci.cally, for any given two set of features, a feature with the largest di.erence between the two sets is eliminated before computing 1-norm pairwise distance or Manhattan distance.
Sentence 2: n N D1(Fa, Fb) = | fi b - fi a | - max | fi b - fi a | (1) i i=1 where Fa = is the vector of N distance mea- N surements of user a and Fb =< f b N 1 , ..., f b > is the vector of N distance measurements of user b.
Relationship: entailment
Domain: Security and privacy
Sentence 1: As a .nal contribution, we give a non-interactive adap­tively secure threshold signature scheme in the standard model that retains all the useful properties (including the erasure-freeness) of our .rst realization.
Sentence 2: ped­ersen s protocol can still be used in the key generation phase if a set of uniformly random common parameters which can be shared by many public keys is set up beforehand.
Relationship: entailment
Domain: Security and privacy
Sentence 1: They also motivate the question: given a query language, it is possible to achieve the group-exponential property with the strict IF provided there exists an obfuscation algorithm for this query language on a single record?
Sentence 2: given a class of predicates over single records and an ef­.cient obfuscator for the corresponding circuit class, does there exist an obfuscator for the entire database that real­izes the group-exponential ideal functionality for that query language?
Relationship: entailment
Domain: Security and privacy
Sentence 1: To encrypt a message, M, the encryption algorithm .rst creates the .rst two elements of the ciphertext, which in the Waters scheme are indepen­dent of the identity; next these two elements are hashed to determine a one-time identity ; .nally the ciphertext is completed by constructing the third element to form an en­cryption to the identity determined from the previous step.
Sentence 2: the identity that we encrypt to is actually deter­mined by the .rst two elements of the ciphertext itself.
Relationship: entailment
Domain: Security and privacy
Sentence 1: However, the particular implementation described in Fig- ure 2 allows an attack on the system when 5 _> 2, whereby a member who is active in time j -1 and revoked in time j can still find Kj.
Sentence 2: in session j -1, if user U, is active, he can remove the masking polynomial from pj-2(x) sj-l(N,x) to reveal pj-2(i).
Relationship: entailment
Domain: Security and privacy
Sentence 1: Aggregating all Face­book pages about q, sentiment orientation of u towards q (Sq u)is s +/s -if the number pages with positive sentiment orientation is greater/lesser than the number of pages with the negative sentiment orientation respectively; otherwise o s .
Sentence 2: if the sentiment orientation of q and Sq u is same, then, = = u is added to the set uq otherwise to uq .( () = + + o uq =u .
Relationship: entailment
Domain: Security and privacy
Sentence 1: Notice that this intuition is already adopted in XACML v3 for the target evaluation.
Sentence 2: if at least one ele­ment (AllOf) matches the query, then the element (AnyOf) containing that (AllOf) evaluates to Match regardless if an error occurs in another element (AllOf) of the same (AnyOf) [2, p. 81-82].
Relationship: entailment
Domain: Security and privacy
Sentence 1: With forward safety below we express that unless a is already authorized to c, authorizing b to c after a is authorized to b does not grant a authorization to c. From the standpoint of intuitive appeal, we see forward safety as the natural counterpart of forward avail­ability.
Sentence 2: simply because b is now authorized to c should not give a authorization to c via b.
Relationship: entailment
Domain: Security and privacy
Sentence 1: Meanwhile, since SB invokes system calls on behalf of the protected applications, our architecture does not require modi.ca­tions of the underlying OS.
Sentence 2: existing applications can run on top of SB without change, and existing OS can use SB to pro­vide strong trusted computing and security services, such as iso­lated runtime space and controlled accesses between processes, for applications.
Relationship: entailment
Domain: Security and privacy
Sentence 1: In­tuitively, if the oracle responds TERMINATE then low-security in­formation is suf.cient to determine that c will terminate.
Sentence 2: command c is guaranteed to terminate for any execution of pro­gram c0 that starts with an initial memory that is low equivalent to m0 and reaches castp[c], after producing an output trace o' that is low equivalent to o, in memory m' that is low-equivalent to m. Formally, if O(p, m, o)= TERMINATE, then '''''' .m0,m,o.m0 L m0 .
Relationship: entailment
Domain: Security and privacy
Sentence 1: When H decides that d may no longer reside on the sys­tem, part of the cleanup process must involve taking action against running processes which have accessed d. Deter­mining which processes have accessed d is a matter of in­formation .ow tracking [24, 13, 41].
Sentence 2: if a process has read data from f , and then communicates with another process, the latter process is considered to have had access to d. Once the system knows that set of processes, it must somehow make them inaccessible.
Relationship: entailment
Domain: Security and privacy
Sentence 1: By utilizing Goldreich[12] s (., d) - hitter2, we can represent the subset I with log|F | + 3log(1/d) bits, where |F | is the size of the encoded data .le, and d is the error probability.
Sentence 2: given a data .le less than 1024 TB (i.e.
Relationship: entailment
Domain: Security and privacy
Sentence 1: Entity Issues Action ] [,,owo I p,omen .on I lmp,omoo .on ] Figure 1: Event Graph for Access Control Decisions In real systems, the policy enforcement mechanisms may be compromised by either maliciously by attackers, or ex- posed as a vulnerability due to poor software engineering.
Sentence 2: different types of "faults" or deviations from authorized behavior may manifest themselves.
Relationship: entailment
Domain: Security and privacy
Sentence 1: We assume that S-box input masks within one round are all not necessarily the same, but all AES rounds share same maskedS-boximplementations(asthe originaldescription [11] allows).
Sentence 2: i-th S-box in any round has the same input mask ni that is randomly chosen in each execution as we are considering now the modi.ed method.
Relationship: entailment
Domain: Security and privacy
Sentence 1: 3.1 Inferring Fine-grained Permissions To answer these questions, we developed Re.neDroid, a static analysis tool that analyzes an app s Dalvik bytecode to infer which of our .ne-grained permissions are used by that app.
Sentence 2: re.neDroid infers which network domains are accessed, i.e., InternetURL( d) permissions (cat­egory 1); which contact columns are used, i.e., ContactCol( c) permissions (category 2); which phone states are read, e.g., for ReadPhoneState(p) permissions (category 4); and which system settings are written, e.g., for WriteSettings( s) per­missions (also category 4).
Relationship: entailment
Domain: Security and privacy
Sentence 1: The using of Zi ti (and the introduction of Q ' i,Q '' i and Q ''' i )enables us to prove the index-hiding prop­ v erty while achieving (e.cient)ciphertext size of O( K +l).
Sentence 2: when reducing the index-hiding property to vi ·wvc) the 3-Party Di.e-Hellman assumption, ftsi(wand fp bc ac will contain terms of g and g respectively, where the simulator cannot compute, and only with the help of Zi ti the simulator can cancel them and form the challenge ci­phertext, i.e., let Zi contain the term g c and ti contain the bc ac vi ·wvc) in ftsi(wti ti terms b and a, so that the terms g and g and fp can be canceled out by those in Zi , while Q ''' i = g can be formed using terms A = g a and B = g b .
Relationship: entailment
Domain: Security and privacy
Sentence 1: Itkis and Reyzin [21] propose a FSS (based on the Guillou-Quisquater [18] scheme), which does not have linear de­pendence on T in any of its parameters, and optimized signing and verifying time.
Sentence 2: signing and verifying in their FSS scheme is comparable to (about twice as expensive as) the underly­ing [18] standard signature scheme.
Relationship: entailment
Domain: Security and privacy
Sentence 1: [0, 1] P 2. i Wi =1 and where '' ' F (z1,z2,...,zn)= W1.z1 + W2.z2 + ... + Wn.zn ' with zi being the ith largest element in the collection z1, ..., zn.
Sentence 2: z' is an ordered vector composed of the elements of Z put in descending order, which means that the weights Wi are associated with a particular ordered position rather than a particular element.
Relationship: entailment
Domain: Security and privacy
Sentence 1: MP3 .les recompressed at a higher bit-rate) authors observed that there are many more quantized MDCT coef­.cients with small values in a single compressed MP3 .le than that in the fake-quality MP3, no matter which bit rate the fake quality MP3 is transcoded from.
Sentence 2: the detector just measures the number of MDCT coe.cients as­suming ±1 values and comparing this value with a given threshold: if it is lower than the threshold, it is decided that the .le is a fake-quality one, otherwise that it is a sin­gle compressed one.
Relationship: entailment
Domain: Security and privacy
Sentence 1: In our BLAC system construction we will need a gener­alized version of the above S-protocol to prove that a user is not currently on the blacklist.
Sentence 2: we need a protocolthat allows onetoproveinzero-knowledgethat,for some n> 1 and for all i =1 to n, x .logbi ti, where ti .
Relationship: entailment
Domain: Security and privacy
Sentence 1: Because of this, network based security technologies such as Network based Intrusion Detection Systems (NIDSs), In­trusion Prevention Systems (IPSs), .rewalls have received remarkable attention to defend our crucial computer sys­tems, networks and sensitive information from attackers on the Internet.
Sentence 2: there has been much effort towards high-performance NIDSs based on data mining and machine learning techniques.
Relationship: entailment
Domain: Security and privacy
Sentence 1: Therefore, a key property we need to show is that IFEDAC main­tains the integrity levels for subjects correctly.
Sentence 2: if a subject has integrity level £ according to IFEDAC, then the subject is be­nign for integrity level £ in the sense that any operation performed by the subject re.ects the intention of only those users in £.
Relationship: entailment
Domain: Security and privacy
Sentence 1: However, they may be practical during startup, when the server issues a batch of tickets re­quired for basic operation, and delays any operations requiring further BottleCap invocations until some later point.
Sentence 2: both of these limitations espouse the same basic idea: that tickets should be issued in bulk, with fairly long validity periods, so that the number of BottleCap in­vocations is minimised.
Relationship: entailment
Domain: Security and privacy
Sentence 1: However, if the attacker uses Hc as the attack vector a (i.e., a = Hc), then the L2-norm of the mea­surement residual of za is equal to that of z,as shown in Theorem 1.
Sentence 2: if the attacker chooses a as a linear combination of the column vectors of H, za can pass the detection as long as z can pass the detection.
Relationship: entailment
Domain: Security and privacy
Sentence 1: A little thought shows that such a constraint de.nes the following con­strained sets: {(u, r), (u, s)}, {(v, r), (v, s)}, {(u, r), (v, s)}and {(u, s), (v, r)}.
Sentence 2: we could introduce a fourth parameter in our de.nition of constraint which de­termines the direct product semantics of the constraint: that is, whether we should iterate over both the scope and the constraint set or simply over the constraint set (as we currently do).
Relationship: entailment
Domain: Security and privacy
Sentence 1: 3.2 Extension of the authentication procedure In this section we will see a practical demonstration of the feasi­bility of the integration within the Uni-Fy gate of other authentica­tion mechanisms.
Sentence 2: we will see a secure authentication scheme based on Session Initiation Protocol (SIP) [12] and related to the scheme that is used in 3GPP/IMS security framework [11].
Relationship: entailment
Domain: Security and privacy
Sentence 1: 3.2 Con.dence Factor We follow the principle that the more you interact with a relay, the more con.dent you become about its behavior, and associate a con.dence factor with our local reputation score.
Sentence 2: if a user A performs n1 and n2 (where n1 > n2) interactions with relays B and C respectively, then the reputation score reported for relay B is more close to its stable score than that reported for C. We, therefore, formulate the con.dence factor as a monotonically increasing function of the number of interactions with a given relay.
Relationship: entailment
Domain: Security and privacy
Sentence 1: Theorem 1 shows that ind1+key1 security of the encryption scheme is suf.cient for the privacy of HK1.
Sentence 2: we now show that it is also necessary.we show that for any encryption scheme .Enc that is not ind1+key1 se­ , .PSS , .IDA cure, .= HK1[.Enc , .ECC ] can fail to provide privacy.
Relationship: entailment
Domain: Security and privacy
Sentence 1: The attacker s action set is denoted by Aa = {k1 =1.1,k2 = -0.8} which correspond to two false voltage values that the at­tacker may choose to inject into the STATCOM.
Sentence 2: the values for the attacker s actions were chosen because based on the output of the Simulink simulation, they were e.ective in 4we studied the Markov game generated from Scenario 2 in Section VI(B) of [7], where load L3 is a variable load instead of a .xed load.
Relationship: entailment
Domain: Security and privacy
Sentence 1: to break UF-CS-CMA of the credential scheme) is de.ned to be U F -C S-C M A SuccA (k) A credential scheme is said to be existentially unforgeable under a chosen message attack if the probability of success of any polynomially bounded adversary A in the above exper­iment is negligible.
Sentence 2: succU F -C S-C M A (k) = A ., where .
Relationship: entailment