sadat2307/MSciNLI huggingface dataset:
Domain: Security and privacy
Sentence 1: Identi.cation of current remediation shortcom­ings: While mobile application markets have thus far successfully removed most discovered malware, we ar­gue that such mechanisms are unlikely to remain suc­cessful as the only mechanism given the expected in­crease in malicious software for mobile environments.
Sentence 2: markets do not have access to all traf­.c generated by such applications, nor the perfectly analyze all incoming applications prior to distribution.
Relationship: entailment
Domain: Security and privacy
Sentence 1: 4.1 Emulating SP3 secure paging As de.ned in Section 3.1, the heart of the SP3 system is the SP3 secure paging, which is capable of rendering different views of the same page frame.
Sentence 2: the page frame referenced by a PTE with non-zero KID should be rendered as decrypted if the page is accessed when the current SID has the permission to use the KID.
Relationship: entailment
Domain: Security and privacy
Sentence 1: Content .ltering problems have been extensively studied, and many of the proposed solutions are based on the gen­eral purpose pattern matching algorithms such as Boyer-Moore (BM) [10], Aho-Corasick (AC) [11], and Wu-Manber (WM) [12].
Sentence 2: the AC algorithm, one of the ear­liest multi-pattern matching algorithms, pre-processes the patterns (strings) to be matched and constructs a .nite state machine.
Relationship: entailment
Domain: Security and privacy
Sentence 1: Both (i) and (ii) pre­vented our approach from easily being applied to a wide va­riety of servers.
Sentence 2: while a high-level description of security-sensitive operations was available for the case study that we considered (the X server), this may not be the case with other servers, as indeed was the case with Pen­nMUSH.
Relationship: entailment
Domain: Security and privacy
Sentence 1: 4.1 Scope preserving hierarchy operations A hierarchy operation may cause a change to R or the partial ordering de.ned on R.If S .R, we will write S ' or (S) ' to denote the value of S following a hierarchy operation.
Sentence 2: we will write s(a) ' to denote the administra­  consider this in more detail in Section 6. tive scope of a following an operation, but for clarity we DIR E  (a) Role names (b) Administrative domains  DIR {E,...,DIR} PL1 ED QE2 {ENG2} (d) Administrator tree (c) Administrative domain tree Figure 1: An example role hierarchy prefer to write (.x) ' ,(.x) ' and (Jx) ' (rather than .x ' , .x ' and Jx ' ).
Relationship: entailment
Domain: Security and privacy
Sentence 1: GENERIC METAMODEL FOR PROCESS-RELATED BREAK-GLASS POLICIES To support the de.nition of break-glass policies in a business process context, we formally embed them into our generic metamodel for Process-Related RBAC models (see [26]).
Sentence 2: we specify that certain breakable tasks can be performed by subjects who are usually not allowed to execute these tasks.
Relationship: entailment
Domain: Security and privacy
Sentence 1: For each data record d, that Alice wishes to outsource, she computes d' and encrypts it attribute-wise using her master public key pka.
Sentence 2: alice computes Epka (d1 + r1),...,Epka (dn +rn),Epka (rn+1),...,Epka (rn+m).
Relationship: entailment
Domain: Security and privacy
Sentence 1: At .rst sight, it may appear that SBAC generalizes RBAC by making an important distinction between ascribed status (of which a role assignment is a particular type) and action status.
Sentence 2: principals can be assigned to a category as a consequence of them being a particular of.ce-holder, but their actions (as of.ce-holders) are also taken into account to determine their overall status.
Relationship: entailment
Domain: Security and privacy
Sentence 1: When meter error is assumed to be normally distributed with zero mean, these criteria lead to an identical estimator with the following ma­trix solution x =(HTWH)-1HTWz, (3) where Wis a diagonal matrix whose elements are reciprocals of the variances of meter errors.
Sentence 2: s-2 1 s-2 2 W = · , (4) · s-2 m where si 2 is the variance of the i-th meter (1 = i = m).
Relationship: entailment
Domain: Security and privacy
Sentence 1: Note that in the case when 8i, pi =1 we get T = d +2d o1 o(2d o1) = d. In the case of an adversary that has no better chance to guess each bit extracted from the accelerometer value we have 8i, pi =1/2 which leads to T = d+2d o1o2 "1(2d o1) = d +2d o1 o2d"1 +1/2= 2d"1 + d o1/2.
Sentence 2: an ad­versary will need roughly around 2d"1 computations which are infeasible for d = 128 in the case of an 128 bit key.
Relationship: entailment
Domain: Security and privacy
Sentence 1: Note that from the contrapositive, we know that if lo .LP s, then it is not possible to .nd a match of s in lr, i.e., lr .
Sentence 2: s. for any log extract lo[i..j]such that lo[i..j]is not an image occurrence of s in lo, then there cannot be a corresponding occurrence of s in the real counterpart of lo.
Relationship: entailment
Domain: Security and privacy
Sentence 1: We choose to use our FFT-based codes because of the relative conceptual and im­plementation simplicity.
Sentence 2: rebuilding a level He requires only taking O(2e) linear combinations of blocks in fact, in Section 5, we will leverage this linearity property and a homomorphic checksum scheme to make the client-server the bandwidth cost per writes independent of the block size.
Relationship: entailment
Domain: Security and privacy
Sentence 1: 3.2.2 Collision-Avoidance IDs Even if RFID tags were upgraded to control access to bar codes using read passwords or some other form of ac­cess control, many tags can still be identi.ed uniquely by their radio behavior.
Sentence 2: many tags use a glob­ally unique and static collision ID as part of their collision­avoidance protocol.
Relationship: entailment
Domain: Security and privacy
Sentence 1: The three temporal metric values used in CVSS are Exploitability (E), Remediation Level (RL), and Report Con.dence (RC).
Sentence 2: the Exploitability (E) can take one of the four annotated values: 0.85 (U), 0.9 (PoC), 0.95 (F), and 1.00 (H).
Relationship: entailment
Domain: Security and privacy
Sentence 1: When adversarial roles are designed into a social exper­iment, care should be taken to avoid undesirable e.ects of such an assignment.
Sentence 2: (i) a set of criteria should be established on who is eligible for adversarial roles, (ii) the adversaries should have anonymous means of raising ques­tions and concerns during the experiment, and (iii) the ad­versaries should participate in an evaluation session after­wards.
Relationship: entailment
Domain: Security and privacy
Sentence 1: In this last evaluation, we therefore combine our observations to measure the overall service availability.
Sentence 2: for each of the three layers (DNS, TCP, HTTP) we de.ne Category e.ective attacks (number / %) DNS 48 11.6% TCP 142 34.2% HTTP 187 45.1% Combined 270 65.1% Table 5: Combined victim unavailability results.
Relationship: entailment
Domain: Security and privacy
Sentence 1: For 1 = i = n, let (CS p i , xDIC2PBS(poli, root(poli), {p}).
Sentence 2: ((CScaptures the condition that poli p ) be the return value of i  6.2 The DIC2PBS Algorithm  p i , x evaluates to p.) p i ) We again assume that the underlying access control sys­ tem is uniform.
Relationship: entailment
Domain: Security and privacy
Sentence 1: Presenting a di.erent device ID to each application thwarts the use of this ID for cross­application pro.ling.
Sentence 2: when an application demands the device ID for the purpose of linking the user to a cross-application pro.le, shadowing the device ID empow­ers users to reply that their device is not the droid you re looking for.
Relationship: entailment
Domain: Security and privacy
Sentence 1: Subsequently, they are mapped on the multi-resolution CG, and the resulting maps {.v (r)}r=1,...,R are used as input of the SVMs related to the gallery user u; they classify the maps producing R (r) scores {cu,v}r=1,...,R that, once mediated, provide a single classi.cation score cu,v.
Sentence 2: each user produces R probe maps; each of them is given as test input to the correspondent SVM of the gallery user, providing a con.­dence score (the distance from the separating hyperplane).
Relationship: entailment
Domain: Security and privacy
Sentence 1: 4.3.2 Trusting the bottle When issuing a capability, the issuer must make a trust decision regarding the key with which it is binding the capa­bility.
Sentence 2: it must establish two facts: that the key is the SRK for a valid TPM, and that this TPM is not un­der the physical control of an adversary [28] (since the TPM provides the necessary guarantees for keeping the capabil­ities secrets).
Relationship: entailment
Domain: Security and privacy
Sentence 1: Such programs may be new, be managed at least partially by end users, and be su.ciently ad hoc that it is di.cult to determine how a new vulnerability may a.ect them.
Sentence 2: the reactive approach may not be e.ective because only their con.guration may have the vulnerability and the method of reaction may di.er between web appli­cation con.gurations.
Relationship: entailment
Domain: Security and privacy
Sentence 1: By a simple argument, our proofs of security for sign­cryption will also imply tight reductions for the IND-CCA security of encryptions and the sUF-CMA security of signatures when the TDPs are applied appropriately, shown in Table 2.
Sentence 2: this implies that our padding constructions can be used as univer­sal paddings , as in [6, 17].
Relationship: entailment
Domain: Security and privacy
Sentence 1: Travis Atkison Department of Computer Science Louisiana Tech University Ruston, LA 71270 atkison@latech.edu Traditionally, these defense tools used signature-based detection which involves comparing the byte sequence of a suspected malicious application to the signatures of known threats, stored in a virus signature database.
Sentence 2: signature-based detection tools are incapable of detecting new and previously unknown threats which do not contain any known signatures.
Relationship: entailment
Domain: Security and privacy
Sentence 1: Accurate characterization of PDN s role in SCA can be signi.cant in precise security analysis and design of secure crypto chips.
Sentence 2: it can provide the following ben­e.ts: 1) it provides a designer with more realistic measure of SCA resistance at design time; 2) it enables integration of the right level of protection; and 3) as we observe later, the PDN causes variation in SCA resistance with operating frequency, which helps a designer to choose right frequency of operation and/or accomplish balanced protection across frequency spectrum.
Relationship: entailment
Domain: Security and privacy
Sentence 1: The center will employ this transition when the users in S are late on payments, and the center wants to initiate gradual degradation of the service for the users in S. Lower: further degradation of users in D, that is the class C1 becomes C2,the class C2 becomes C3, and so forth.
Sentence 2: the users from the class CL become re­voked, i.e, they leave the class D of degraded users and join the class R of revoked users.
Relationship: entailment
Domain: Security and privacy
Sentence 1: Given the publish and discover concept that is so central to this architecture, we define the addition of security to Web services as the addition of security to the primary publish and discover mechanism .
Sentence 2: we discuss adding security to the Universal Description, Discovery, and Integration (UDDI) registry and to the Web Services Description Language (WSDL) document that defines the interface to a given Web service contained in that registry.
Relationship: entailment
Domain: Security and privacy
Sentence 1: , zn are variables that can be set multiple times by the colluding parties and take any value.
Sentence 2: after the .rst i parties complete their participation in the protocol, a collusion of the last n - i parties and the server can simulate the continuation of the protocol any number of times, where in each time they can provide di.erent inputs zi+1, .
Relationship: entailment
Domain: Security and privacy
Sentence 1: While con­siderable effort has focused on methods for defending against such attacks, there is comparatively little research describing the mal­ware ecosystem itself.
Sentence 2: how does one piece of malware relate to another, what pressures drive its structural and functional evolution, and what may this teach us about malware authors and 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: The Bel(V) denotes the the possibility that a wireless sta­tion in X involves in an acting relation (i.e., a frame de­livering path) de.ned in an ordered set V. In Table 1, we present the values of belief measure for the example given in Figure 7(b).
Sentence 2: bel((A, B, C))= m((A, B))+ m((B, C)) + m((A, B, C)), which represents the probability that an evidence supports the claim of path A .
Relationship: entailment
Domain: Security and privacy
Sentence 1: The take-a-tail method is identical to the cha.ng-by-tail­tweaking method, except that the tail of the new password is now randomly chosen by the system,and required in the user-entered new password.
Sentence 2: the password-change UI is changed from: Enter a new password: to something like: Propose a password: Append 413 to make your new password.
Relationship: entailment
Domain: Security and privacy
Sentence 1: Lev(A, B) represents the Levenshtein distance be­tween string A and B.
Sentence 2: the minimum number of single-character edits required to transform one string into the other; and LevAvg (S) represents the average Levenshtein distance between a set of strings S. In layman s terms, our .tness function is the average di.erence between MTurk user s answers and Antigate worker s answers, divided by the consistency of their answers.
Relationship: entailment
Domain: Security and privacy
Sentence 1: However, the possibility remains open that Bob might be able to send a square y for which he does not know any square roots of y, and thereby gain an advantage.
Sentence 2: although no such algorithms are known to exist, it could be possible that there are both a polynomial-time algorithm that, given m, produces a square root y with high probabil- ity, and a polynomial-time algorithm that, given m, y, and z such that z 2 = y mod m, factors m with high probability.
Relationship: entailment
Domain: Security and privacy
Sentence 1: Although the precision and recall of this initial detection attempt are not high, the approach can still constitute one line of defense in a suite of techniques, especially given that the data collection needed for the detection is extremely lightweight.
Sentence 2: our models can be used by enterprise IT administrators and anti-malware vendors to identify a small pool of vulnerable devices, e.g., to deploy more expensive analysis techniques on them or to provide training to their users.
Relationship: entailment
Domain: Security and privacy
Sentence 1: Given the impossibility mentioned above when the set of functions is too rich, it makes sense to even investigate the minimal notion of KDI-security with respect to just a single function, as we may at least hope that even an abusive im­plementation that encrypts its own key will only do so in one form, rather than encrypting many copies of the key in many di.erent forms (e.g., it may encrypt the key itself or a hash of the key, but not multiple, arbitrary functions of the key).
Sentence 2: negative results obtained in this minimalistic setting imply impossibility of stronger notions of KDI security.
Relationship: entailment
Domain: Security and privacy
Sentence 1: The Deny-overrides RCA is similar to the Permit-overrides RCA, except that the preference is D > P > NA.The IN is also treated similarly as uncertainty.
Sentence 2: if IN is from a permit rule, we have D > P > IN > NA,and if IN is from a deny rule, we have D > IN> P > NA.
Relationship: entailment
Domain: Security and privacy
Sentence 1: Attacking and Defending Lightweight PHY Security Schemes for Wireless Communications Nicholas Kolokotronis Alexandros Katsiotis Nicholas Kalouptsidis Department of Informatics and Department of Informatics and Department of Informatics and Telecommunications Telecommunications Telecommunications University of Peloponnese University of Athens University of Athens 22100 Tripolis, Greece 15784 Athens, Greece15784 Athens, Greecenkolok@uop.gr akats@di.uoa.gr kalou@di.uoa.gr ABSTRACT This paper investigates the security o.ered by PHY schemes that are well oriented towards jointly providing security and protection form channel errors.
Sentence 2: we focus on constructions that were recently proposed in the literature, whose security relies on the secrecy of parameters de.ning the encoding/decoding process of convolutional codes.
Relationship: entailment
Domain: Security and privacy
Sentence 1: Some de.nitions in the literature, we believe, have made inappropriate choices with respect to these ingredients, and in some, critical is­sues have been ignored.
Sentence 2: we argue that it is impor­tant in non-deterministic systems to base the de.nition of security on the effect of actions on agents history of actions and observa­tions, whereas some de.nitions in the literature have considered only their effect on single observations.
Relationship: entailment
Domain: Security and privacy
Sentence 1: Correlating among these logs could pro­vide insight into the reasoning and decision making process of the employees as it identi.es a minimum value the em­ployees placed on the resources.
Sentence 2: the market provides information that enables a cost-bene.t analysis to gain insight into why resources are accessed while a tradi­tional access log can only show what resources are accessed.
Relationship: entailment
Domain: Security and privacy
Sentence 1: [3] demonstrate that thresholds for anomalousness can be established for a common multivariate Gaussian model of typical behavior.
Sentence 2: power systems researchers proposed to calculate the measurement residual (i.e., the di.erence between the vector of observed measurements and the vector of estimated measurements), and use its 2-norm to detect the presence of bad measure­ments [3].
Relationship: entailment
Domain: Security and privacy
Sentence 1: Categories and Subject Descriptors In this paper, we explore the general security risks asso­ciated with the use of virtual server images from the public K.6.5 [Management of Computing and Information catalogs of a cloud service provider.
Sentence 2: we fo-Systems]: Security and Protection cus our investigation to the security problems of the public images available on the Amazon EC2 service.
Relationship: entailment
Domain: Security and privacy
Sentence 1: This question can be addressed by developing a vulnem- bilit~l model for each network element, and by introducing the novel concept of "survivability measure" -a metric for capturing the diversity in the vulnerability to attacks of dif- farent network elements.
Sentence 2: we can identify, for each network element s, the set of attacks A, that the net- work element is vulnerable to.
Relationship: entailment
Domain: Security and privacy
Sentence 1: 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' X', also  or X= equally likely whether Y = Y ' Y '.
Relationship: entailment
Domain: Security and privacy
Sentence 1: of Electrical and Computer Engineering North Carolina State University {bmrogers, schhabr, solihin}@ncsu.edu Abstract In today s digital world, computer security issues have become increasingly important.
Sentence 2: researchers have proposed designs for secure processors which utilize hardware-based mem­ory encryption and integrity veri.cation to protect the privacy and integrity of computation even from sophisticated physical attacks.
Relationship: entailment
Domain: Security and privacy
Sentence 1: In addition to social network defense systems, SynchroTrap also borrows insight from previous work on botnet detection [21 23,43, 47], as some attackers use botnets to control malicious accounts.
Sentence 2: botMiner [21] and BotSniffer [22]detect the bots that respond to commands in a similar way.
Relationship: entailment
Domain: Security and privacy
Sentence 1: We reveal the value of B to the .rst player (the second player already knows this value).
Sentence 2: we condition the game G(Y ,X |V1)TV1 on the value of B, and consider the game G(Y ,X |V1)TV1 |B = G(Y ,X |V1,B)TV1 , with parameters (k, d - 1, P(Y |V1,B)TV1 , P(X|V1,B)TV1 ) (see Subsection 6.1).
Relationship: entailment
Domain: Security and privacy
Sentence 1: call the pair (Tup(I),P)a dictionary.Let P[QS = s] denote the probability that the query QS outputs s.Then query QS is perfectly private with respect to QV if for ev­ery probability distribution and for all answers s, v to the queries QS, QV respectively, P[QS = s]= P[QS = s|QV = v].
Sentence 2: the query QS is perfectly private with re­spect to QV if the adversary s belief about the answer to QS does not change even after seeing the answer to QV .
Relationship: entailment
Domain: Security and privacy
Sentence 1: Also, we give a direct construction of a PIC scheme in section 6 which handles both repeated queries and rejected queries.
Sentence 2: even if a user has a query blocked because it is inference-enabling, they can 4Notationally this means that O (polylog m)= O (1) continue to make future queries and retrieve database entries so long as these queries are not inference-enabling.
Relationship: entailment
Domain: Security and privacy
Sentence 1: In particular, 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.
Sentence 2: we used two techniques to re.ne the obfuscated mobility trace: (i) using Viterbi decoding [31] to deduce the location of user u at time t (this algorithm is quadratic in the number of states = number of location identi.ers) and (ii) using Kalman .ltering [31] for both backward and forward smoothing to deduce the location of user u at time t (this algorithm is cubic in the number of states = number of location identi.ers).
Relationship: entailment
Domain: Security and privacy
Sentence 1: S selects a random record RJc5, s), decrypts the ciphertext (c1, c2, c3, c4, c5)by using .1, .1 .2 3 c .2.
Sentence 2: it computes R := c5/(c ), and then sends 4 (rec:sid, ., R, P ) to FACOT.
Relationship: entailment
Domain: Security and privacy
Sentence 1: the ad­versary opens a reader-adversary session sid and an adversary­prover session sid * that are related in the sense that the time-critical responses will be the same), the MITM adver­sary will then be queried by the reader with a challenge bit c and will expect a response bit r. However, in the Go-Early strategy, the adversary .rst queries the prover in session sid * with a random bit c * , receiving r * in response, and will use this response to answer to the reader subsequently, in ses­sion sid.
Sentence 2: if c = c * , then the adversary wins the round by forwarding r = r * , else, if c = c * , it guesses the correct response with probability 2 1 , totaling a success probability of 4 3 per round.
Relationship: entailment