sadat2307/MSciNLI huggingface dataset:
Domain: Security and privacy
Sentence 1: We restrict the gen­eral concept of usage control in the following way: only trusted applications are run and the underlying assumption is that these applications will not violate the policies.
Sentence 2: we do not im­plement the usage restrictions at the level of Java API or operating systems calls but rather assume that this is done by the trusted ap­plications (this assumptions can clearly be justi.ed in the running example of this paper).
Relationship: entailment
Domain: Security and privacy
Sentence 1: {0, 1}m as input if m  yiUji >Z, i=1 where Z =20ck is a threshold parameter.
Sentence 2: s(y) consists of the indices j for which the jth entry of UyT exceeds Z. Theorems 1 and 2 summarize the basic properties of the above construction.
Relationship: entailment
Domain: Security and privacy
Sentence 1: Similarly, the degree of anonymity is about 0.13 and 0.97 (and anonymity is 2.14 and 15.97) when using community-aware and community-blind algo­rithms, respectively.
Sentence 2: the community-aware algo­rithm decreases the anonymity by 13.83 additional bits compared to the community-blind algorithm.
Relationship: entailment
Domain: Security and privacy
Sentence 1: [1, m]) represents the comparison result of attributes Ai and A'i.
Sentence 2: bi = fi(Ai, Ai'), where fi() is a compar­ison function for the type of the i-th attribute in the  ID Time PID DestAddr Request (Q) Host Referrer (R) Q Type R Type ParentID ... 4 5 6 22.723 22.733 22.973 2724 2724 2724 64.30.224.103:80 198.82.164.40:80 198.82.164.40:80 / .../combined.js .../matrix.css www.cnet.com i.i.com.com i.i.com.com N/A www.cnet.com/ www.cnet.com/ website javascript css NULL website website 0 4 4 ... 14 25.307 2724 198.82.164.40:80 .../bgBody.gif i.i.com.com .../matrix.css multimedia css 6 ... Table 1: Original network events observed.
Relationship: entailment
Domain: Security and privacy
Sentence 1: As discussed in VMST [14], this enumeration is often application-speci.c and has to be done by kernel experts, not the end users of our E X TE RIOR.
Sentence 2: after manually examining all the syscalls, we classify those of our interest into the following three categories: (1) Inspection In order to recon.gure the OS or recovery from an attack, we have to introspect the OS to get its current status and perform the response.
Relationship: entailment
Domain: Security and privacy
Sentence 1: Carman, Kruus and Matt have analyzed several approaches for key management and distribution in sensor networks [5].
Sentence 2: they discuss the energy consumption of three di.erent approaches for key establishment pre-deployed keying protocols, arbitrated protocols involving a trusted server, and autonomous key agreement protocols.Basagni et al [2] discuss a rekeying scheme for periodically updating the group-wide tra.c encryption key in a sensor network.
Relationship: entailment
Domain: Security and privacy
Sentence 1: The Stackelberg equilibrium is a pair of choices (f * for the LPPM and h * for the attack) such that neither the user nor the adversary would gain anything by changing their respective choices.
Sentence 2: h * is the choice that minimizes privacy against f * , and f * is the choice that maximizes privacy against an adversary who will make her choice after observing f * while respecting the quality constraint.
Relationship: entailment
Domain: Security and privacy
Sentence 1: X1 = x1 X1 = x2 X1 = x3 32/100 2/100 2/100 X0 = x1 12/100 12/100 12/100 X0 = x2 2/100 6/100 20/100 X0 = x3 Figure 5: H2 n(b) (lower graph with stars), H1 n(b) (up­per graph with stars), log22 (b) (lower graph with W n W n circles), and log21 (b) (upper graph with circles), with b = (010101010101), X0 = X6 = x1, X2 = X8 = x2, and X4 = X10= x3 for the joint probability distribu­tions given in Table 3.
Sentence 2: how entropy and guesswork changes with the num­ber of encrypted units, i.e., the encryption level This is done for languages up to the second order by deriving equations for entropy of selectively encrypted messages and then trans­ferring the result to guesswork through an equation relating the two measures.
Relationship: entailment
Domain: Security and privacy
Sentence 1: End-users could see a catalogue of potential access privileges that they could request, and security ad­ministrators could identify and correct inappropriate privi­leges.
Sentence 2: security administrators would be freed up to become security analysts, engaging in questions of how roles should be built and structured, which was expected to be bene.cial to the organization in terms of both e.ective identity management and employee retention.
Relationship: entailment
Domain: Security and privacy
Sentence 1: Then, we can easily evaluate the power-sum symmetric polynomi­als Enc(pk, Pj(x1,· · · , xn)) for 1 = j = d with only an ad­ditive homomorphic property, and evaluate symmetric poly­nomials of degree d by decrypting Enc(pk, Pj(x1,· · · , xn)) s and multiplying and adding on the decrypted data.
Sentence 2: this method is more e.cient when evalu­ating low-degree symmetric polynomials in many variables.
Relationship: entailment
Domain: Security and privacy
Sentence 1: 4.3 Discussions For both low and high security applications, our analyses show that after a certain number of login sessions, the probability of successful impersonation into the system in choose-two scheme becomes higher than the probability of successful impersonation in choose-one scheme.
Sentence 2: as the passwords are used over and over again, asking two passwords per login session becomes less secure as compared to asking one password per login session.
Relationship: entailment
Domain: Security and privacy
Sentence 1: R, rs_acquires(u, p, r, s, t)  It is important to note that can_activate(u, r, t), can_acquire(u, p, t), r_can_acquire(u, p, r, t) and can_be_acquired(u, r, t) predicates do not assume anything about the state of a role.
Sentence 2: they do not say in which state role r is at time t. For example, if can_activate(u, r, t) and enabled(r, t) hold, then a user u s request to activate r at time t is granted provided there are no other activation or SoD constraints prohibiting it.
Relationship: entailment
Domain: Security and privacy
Sentence 1: If the conventions of orthodox PKI were to be applied to this operation, then a number of additional complexities would be imposed from outside on how the stock exchange runs its business.
Sentence 2: most PKI regulators today would expect standardized identity proofing for all certificate recipients at a level equivalent to passport application, irrespective of how the existing listing rules operate.22 Furthermore, the company officer, as certificate Subject, would generally have execute a user agreement with the CA.
Relationship: entailment
Domain: Security and privacy
Sentence 1: To ensure the isolation between the legacy host and the isolated environments, SICE prevents the legacy host from a.ecting the execution of the isolated environment, and the isolated workload (excluding the security manager, which needs to be trusted by the legacy host) from a.ecting the ex­ecution of the legacy host.
Sentence 2: we need to prevent the interference through explicit inter-core communication as well as those through modifying each other s memory.
Relationship: entailment
Domain: Security and privacy
Sentence 1: For clarity, we .x the .nal Q-bits of the hash output as the target string.
Sentence 2: for a given puzzle with (Q, D), a solution x should satisfy (h(x) mod 2Q) : D. For instance, if SHA-1 is used and (Q, D) = (32, 65537), then a string x is a solution, only if (SHA-1(x) mod 232) : 65537.
Relationship: entailment
Domain: Security and privacy
Sentence 1: Role-based access control (RBAC) [30], attribute­based access control (ABAC) [34], federated identity [27,32], trust negotiation [4, 5, 36], and distributed proof [3, 19] sys­tems all assess the trustworthiness of a user based upon ver­i.able and unforgeable statements regarding the identity, roles, or attributes ascribed to that user by one or more trusted certi.ers.
Sentence 2: these trusted certi.ers serve as roots of vertical chains of trust associated with a particu­lar principal.
Relationship: entailment
Domain: Security and privacy
Sentence 1: This type of quadratic state problem cannot be solved by an NFA-based approach.
Sentence 2: the corresponding NFA con­tains 1042 states; among these, one is for the matching of SEARCH, one for the matching of s+, and the rest of the 1024 states for the counting of [^n]{1024} with one state for each count.
Relationship: entailment
Domain: Security and privacy
Sentence 1: For graphs of dimension d > 1, an e.cient data struc­ture can also be built using dimension reduction techniques.
Sentence 2: [5] shows that, given a solution to the one-dimensional graph, a data structure for a graph of dimension d will have an extra factor of O((log n)d-1) in the space complexity of the data structure, and extra 2(d-1) edges in the maximum distance between any nodes (between which a path exists) in the data structure.
Relationship: entailment
Domain: Security and privacy
Sentence 1: For a discrete ran­dom variable X, the min-entropy of X is related to the most probable value that X can assume, speci.cally min­entropy(X)= -log2 (maxx Pr[X = x]).
Sentence 2: if min-entropy(X)= e then X does not assume any value with probability of more than 2-£ .
Relationship: entailment
Domain: Security and privacy
Sentence 1: Moreover, as in the statistical evaluation, Lux0R substan­ tially outperforms PjScan in terms of classi.cation accuracy.
Sentence 2: when our detector was trained on PDF sam­ ples exploiting only CVE 2007-5659, more than 96% of mal­ ware samples exploiting other vulnerabilities, i.e.
Relationship: entailment
Domain: Security and privacy
Sentence 1: Leveraging these ties, it is possible to design ef.­cient and distributed algorithms that, with a moderated degree of node cooperation, enforce the emergent property of node capture detection.
Sentence 2: in this paper we provide a proof of concept proposing a set of algorithms that leverage, to different extent, node mobility and node cooperation that is, identifying social ties to thwart node capture attack.
Relationship: entailment
Domain: Security and privacy
Sentence 1: As a compensation, a tireless attacker devotes more time and labor in the attacking process to maximize the chance of suc­cess.
Sentence 2: a tireless attacker knows some of the at­tributes of his/her target (seed attributes), and submits such attributes to search engines, and tirelessly browsing and ex­amining the results for clues.
Relationship: entailment
Domain: Security and privacy
Sentence 1: The depth of the cascade Bloom .lter generated in the .rst strategy, where m is set initially to 1 mil­lion counters, is always 2.
Sentence 2: constructCascadeBF always has enough space to allocate to the counting Bloom .lter of the .rst level of the cascade, and can afford to have just one more level, which is the explicit list.
Relationship: entailment
Domain: Security and privacy
Sentence 1: F2, by g .. c3||c2||c1||c0 Table 1: The LED round constant  Rounds Constants 1 - 24 01, 03, 07, 0F, 1F, 3E, 3D, 3B, 37, 2F, 1E, 3C, 39, 33, 27, 0E, 1D, 3A, 35, 2B, 16, 2C, 18, 30 25 - 48 21, 02, 05, 0B, 17, 2E, 1C, 38, 31, 23, 06, 0D, 1B, 36, 2D, 1A, 34, 29, 12, 24, 08, 11, 22, 04 Figure 1: The LED block cipher Table 2: The LED S-Box x 0 1 2 3 4 5 6 7 8 9 A B C D E F S[x] 4 1 2 2 8 6 5 6 B E A 9 2 2 F B where || denotes the concatenation of bits.
Sentence 2: this mapping identi.es an element of F16 with a bit string.
Relationship: entailment
Domain: Security and privacy
Sentence 1: We implemented the FVDS scheme in the OpenSSL open source cryptographic library [29], both as a standalone signa­ture scheme and for use in the SSL protocol (we discuss the latter issue in the next section).
Sentence 2: we modi.ed OpenSSL version 1.0.0 to support FVDS using the built­in big-integer operations, and compared the performance of this scheme with the built-in RSA implementation.
Relationship: entailment
Domain: Security and privacy
Sentence 1: In the pro­posed scenario, an adversary is assumed to possess a small piece of seed information about a targeted user, and con­duct extensive and intelligent search to identify the target over both the Web and an information repository collected from the Web.
Sentence 2: two types of attackers are mod­eled, namely tireless attackers and resourceful attackers.We then analyze detailed attacking mechanisms that could be performed by these attackers, and quantify the threats of both types of attacks to general Web users.
Relationship: entailment
Domain: Security and privacy
Sentence 1: In particular, we only assume an upper bound on the number of corrupted sensors; thus, it is not possible to map subsets of the polyhedra while guaranteeing that the fusion polyhedron contains the true value.
Sentence 2: such mappings would require additional assumptions on the num­ber of corrupted sensors in certain subsets of N (t); hence, all permitted actions in this work are: a) computing fu­sion polyhedra for all n polyhedra in a given time step; b) mapping this fusion polyhedron to the next time step; c) or mapping all polyhedra to the next time step, thus doubling both n and f .
Relationship: entailment
Domain: Security and privacy
Sentence 1: While optimized implementations for speci.c named curves and .eld degrees can provide high performance, it is a de­sired security feature for both ECC software libraries and hardware accelerators to support elliptic curves over a wide range of binary polynomial .elds GF (2m).
Sentence 2: the implementer of an ECC library or hardware platform may not know all curves that will eventually be used.
Relationship: entailment
Domain: Security and privacy
Sentence 1: Fusking or Fuskering is a procedure where a program is able to do a brute force type of attack where it uses typical filenames to guess the next logical file to appear in the sequence.
Sentence 2: if you have an album that contains multiple photos named pic01, pic02, and pic03, but sent someone only the link to the first one; if they assume that those others exist, they can then use the same link and substitute the next logical name or number and it would display the file if one existed.
Relationship: entailment
Domain: Security and privacy
Sentence 1: Note that correctness still holds even if the circuit C com­pletely ignores all ciphertexts encrypted under a public key pki ., or if none of the original ciphertexts were encrypted un­der this key.
Sentence 2: using super.uous keys in the decryption process does not a.ect its correctness (as long as decryption uses at most N keys).
Relationship: entailment
Domain: Security and privacy
Sentence 1: However, it might be possible to employ the same type of side-channel analysis to detect Flush-Reload attacks, sim­ilar to the ideas of HomeAlone [39].
Sentence 2: a victim might be able to infer the presence of an adversary by means of performing Flush-Reload monitoring of the cache to de­tect the Flush-Reload pattern induced by an adversary s likely choice of NFA.
Relationship: entailment
Domain: Security and privacy
Sentence 1: Diagram 5(a) has been obtained by considering, for each Di , all the range queries whose edges are a half of the size of the correspond­ing dimension of Di .
Sentence 2: we considered queries of size 1 · V ol(D) (that is 12.5%) in the 3D case, 1 · V ol(D) (that 23 24 is 6.25%) in the 4D case, up to 21 7 · V ol(D) (that is 0.78%) in the 7D case.
Relationship: entailment
Domain: Security and privacy
Sentence 1: UNIFORMLY RANDOM PUBLIC VIEW We .rst consider the e.ectiveness of an adversary in our model if the graph is produced by uniform random sampling.
Sentence 2: given a request for public neighbours..(..), the net­work responds with a random selection of .. of the .. s friends, or returns all of their friends if ..(..) = ... We assume that the network responds deterministically to each request, provid­ing the same set of friends every time public neighbours..(..) 1 ..(..) /..*(..) i. the sampled graph includes false edges.
Relationship: entailment
Domain: Security and privacy
Sentence 1: For any valid (s, L) that is hold by a credential holder UH , he can only designate the credential s to any veri.er that is listed in L, speci.ed by the credential issuer.
Sentence 2: there exists no algorithm for any (s, L) that will allow the credential holder to designate s to a user UO .. L, such that T rue .
Relationship: entailment
Domain: Security and privacy
Sentence 1: Our attack highlights the nuances of properly designing traceability algorithms by demonstrating how it is possible to take advantage of a seemingly benign discrep­ancy between the ciphertexts that are emitted during the traitor tracing operation compared to the ciphertexts used during normal transmission.
Sentence 2: our attack capitalizes the fact that during regular transmission in the scheme of [9] each ciphertext transmitted by the sender can be decomposed into parts by the illicit decoder, one part for each traitor key, and that each component can be submitted to a statistical test that returns a random bit.
Relationship: entailment
Domain: Security and privacy
Sentence 1: For example, in the role graph model it is generally as­sumed that no user should be assigned to MaxRole [13]; (U,{MaxRole} ,s) expresses this constraint succinctly.
Sentence 2: we can express role exclusion con­straints: such constraints can also be used to impose a ceiling on the roles to which a user can be assigned.
Relationship: entailment
Domain: Security and privacy
Sentence 1: One scheme that encompasses the above properties is the Paillier cryptosystem [26], which we use in our implementa­tion.
Sentence 2: the Paillier cryptosystem is a semantically se­cure additively homomorphic encryption scheme, which can be used as a threshold scheme [18, 11] whose key generation can be performed in a fully distributed manner [4, 12].
Relationship: entailment
Domain: Security and privacy
Sentence 1: Con­sider an alternative (hypothetical) de.nition of policies in which a policy has the following function type instead: L×L×U ×U G(I, L) × G (J , U) .
Sentence 2: 2(6) a policy takes a spatial network and a social network as input, and produces a 4-ary relation that relates an owner location, a requester location, an owner and a requester.
Relationship: entailment
Domain: Security and privacy
Sentence 1: If T is in fact noticeably less than q, a simpli.cation of this is a close upper bound: N * (T/q)m (2) T As shown in [1], Equation 2 not only re.ects the probabil­ity of the existence of such a coalition of size T ,it isalso the probability that a larger completely di.erent coalition could have incriminated this coalition of size T when this coalition is actually completely innocent.
Sentence 2: the formula gives the false positive probability in the detection.
Relationship: entailment
Domain: Security and privacy
Sentence 1: This relation depends on a local reduction relation, ., that describes the reduc­tion of expressions under an environment and a pool of threads.
Sentence 2: call and return programs reduce un­der -., and all other code reduces under .. Of speci.c interest are (Red let-return), (Red send), (Red call), and (Red return), that can cause data .ows across contexts.
Relationship: entailment
Domain: Security and privacy
Sentence 1: We then determine the range of time over which this activity occurred and, within that interval, identify which sources appear to have contributed to the activity.
Sentence 2: we apply this approach to the problem of detect­ing distributed SSH brute-forcing: attackers employing a number of systems that each try different username/password combinations against a site s SSH login servers, hoping that one of them will stumble across a working combination made possible by a careless user.
Relationship: entailment
Domain: Security and privacy
Sentence 1: While these browser extensions provide control over cache-based tracking and visited link tracking, we show that there are limits to user control over tracking from co­operating web sites.
Sentence 2: although cookie policies provided by some browsers may suggest otherwise, we argue that it is not feasible to allow multiple-session tracking by a single site without also allowing multiple-session tracking by any collection of cooperating sites.
Relationship: entailment
Domain: Security and privacy
Sentence 1: discuss a number of challenges related to the evaluation of results generated by malware clustering systems.
Sentence 2: by using plagiarism detection algorithms to measure the similarity between malware samples, they show that a factor con­tributing to the strong results reported in [2] might be that the 2,658 validation instances selected via majority voting on multiple AVs are simply easy to classify.
Relationship: entailment
Domain: Security and privacy
Sentence 1: Aread/write(R/W).ag is maintainedineachpagetableentry(PTE),describingthe R/Wproperty of thepage mappedby thePTE.Thisallows thesamepagetobe mapped with adi.erentR/Wproperty in di.erent PTEs.
Sentence 2: writability is a property of the mapping of a page, not a property of the page itself.
Relationship: entailment
Domain: Security and privacy
Sentence 1: Since the discount is a resource, the head of this policy, BookSt.discount(phoneNum = x3 ), de­.nes a part of the application interface provided by the ATN sys­tem using this policy; the parameter phoneNum is made avail­able to the application through this interface.
Sentence 2: the applica­tion will issue a query to determine whether the requester satis.es BookSt.discount(phoneNum = x3 ), and if it succeeds, the vari­able x3 will be instantiated to the phone number of the requester.
Relationship: entailment
Domain: Security and privacy
Sentence 1: Our protocol, which builds directly on the protocol of Feige and Kilian, is qualitatively more practical than known techniques for delegating computation in the single-server setting.
Sentence 2: all known protocols rely either on arithmetization and PCP tech­niques [20, 12], or provide only amortized performance advan­tages and rely on fully homomorphic encryption [11, 9].
Relationship: entailment
Domain: Security and privacy
Sentence 1: We formally cover these assumptions by modelling Read, Gen and Chk as oracles.
Sentence 2: whenever P wants, e.g., to ex­ecute Read(State(P), a), P sends a to the Read-oracle and receives the corresponding result s. While sending and re­ceiving messages between P and the oracles are modelled to take no time, the determination of the response does.
Relationship: entailment
Domain: Security and privacy
Sentence 1: Then Q is a valid type 1 forgery if and only if (g) m = s¯0 = s 0; and e N (h) (¯s0 - s 0) + (¯ci - c i)ai = 0. i=1 Therefore, if A can produce a valid type 1 forgery Q, then it would be able to learn (g) and (h).
Sentence 2: a can determine f possibilities of a, say a1, .
Relationship: entailment
Domain: Security and privacy
Sentence 1: (A trie can be viewed as a tree-structured .nite-state automaton for matching strings.)
Sentence 2: when a variable v is encountered in the trace with value s, we traverse down a path in the trie that matches s. If there is a complete match for s, and this match takes us to a state S in the trie, then the variables associated with S are candidates for equality with v. Each vari­able v ' associated with any descendant state S ' of S is a candidate for the relationship prefix(v, v ' )= v and prefix(v, v ' )= s. Similarly, any variable v '' associated with an ancestor state S '' '' '' of S is a candidate for the relationship prefix(v, v )= v and '' '' prefix(v, v )=s '' ,where s is the string corresponding to state S '' ''' .
Relationship: entailment