sadat2307/MSciNLI huggingface dataset:
Domain: Security and privacy
Sentence 1: Although we have seen successes in controlled datasets or for popular entities that appear on many web contexts, the general problem of arbitrary entity 90 80 70 60 50 40 30 20 10 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 # ofpositive results (a) Number of positive results in each successful attack 70 60 50 40 30 20 10 0  1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 41 43 45 Rank (b) Rank of the .rst positive result in each successful attack Figure 6: Results of successful smart tireless attacks with seed attribute tuple  extraction is still far from being solved.
Sentence 2: diver­sity of web documents and limited evidences (e.g.
Relationship: entailment
Domain: Security and privacy
Sentence 1: We verify that these bits are perfectly secret (Eve obtains no information about them) by measuring the mutual information between the signal that reaches Eve s antenna and the signals that reach the antennas of the ter­minals.
Sentence 2: we ensure that Eve cannot learn anything about the shared secrets, even if she has access to corrupted packets that get discarded by the lower layers of her device.
Relationship: entailment
Domain: Security and privacy
Sentence 1: The inputs from the HTML form are directly supplied to procedure process-form, and hence the application is vul­nerable to SQL injection attacks.
Sentence 2: a malicious user can supply the string John OR 1=1 -- for the user­name, and not-needed for the password as inputs, and check thedisplay option, which will maketheprogramissue the SQL query(along Path 1): SELECT * from phonebook WHERE username= John OR 1=1 -- AND password= not-needed This contains the tautology 1=1, and given the injected OR operator, the SELECT condition always evaluates to true.
Relationship: entailment
Domain: Security and privacy
Sentence 1: Si randomly permutes the ordered  II i set 1~'-~ ,Pi ,vi IH=I.
Sentence 2: the server S~ selects a permutation ~r~ on N elements uni-formly at random, and sets (c~*~),/z~),y} ~)) = (~=,0)), fi~=,O))~,(i))).
Relationship: entailment
Domain: Security and privacy
Sentence 1: Security based Survivability Risk Analysis with Hyunsang Youn Department of Electrical and Computer Engineering, Sungkyunkwan University, Suwon, Republic of Korea +82-31-290-7220 wizehack@gmail.com  Extended HQPN Cheolhyun Park Department of Electrical and Computer Engineering, Sungkyunkwan University, Suwon, Republic of Korea +82-31-290-7220 pch851130@naver.com Eunseok Lee Department of Electrical and Computer Engineering, Sungkyunkwan University, Suwon, Republic of Korea +82-31-290-7220 leees@skku.edu ABSTRACT Analysis of software survivability in the early development phase is very important to validate and specify software architecture.
Sentence 2: quantitative evaluation of survivability is very useful to determine the architecture and to estimate the risk.
Relationship: entailment
Domain: Security and privacy
Sentence 1: Their goal is to solve some communica­tionproblem f : L.W, where L.Xt is the set of legal or promise inputs, by sending messages to each other.
Sentence 2: f is a partial function on Xt .A protocol P speci.es the rules for the players to to send messages to each other for every input in the domain Xt, and notjustthepromise inputs.
Relationship: entailment
Domain: Security and privacy
Sentence 1: The sum­mary of a function f is a set of pairs (pred I O P), denoting the condition (pred) under which a conceptual operation (OP) is au­thorized by f. The analysis in Algorithm 2 is .ow-and context­sensitive.
Sentence 2: it respects the control-.ow of each function, and precisely models call-return semantics.
Relationship: entailment
Domain: Security and privacy
Sentence 1: Its output is a message m, which is the subset of Lto disclose in the next message, subject to m nS = Ø (i.e., no duplicate disclosures can be made).
Sentence 2: when m = Ø, it is called a failure mes­sage, which means that a party terminates the negotiation, forwhateverreason.
Relationship: entailment
Domain: Security and privacy
Sentence 1: In contrast, this paper studied the use of inter­user correlation models to address this problem.
Sentence 2: we exploited structural similarities between two sources of inter-user correlations (the contact graph and the social network) and devel­oped techniques to leverage such structural similarities to deduce mapping between nodes in the contact graph with that in the so­cial network, thereby de-anonymizing the contact graph (and thus the underlying mobility trace).
Relationship: entailment
Domain: Security and privacy
Sentence 1: That is, log qlog N · (log log q + log n)  0, which holds for the pa­rameter settings in the statement of the theorem.
Sentence 2: this scheme maintains security as long as q = 2n 1-d for some d> 0, thus supporting as many as N = 1-d/ logO(1) nn users.
Relationship: entailment
Domain: Security and privacy
Sentence 1: Indeed if F1 is a cryp­tographic function such that F1(K, C)= C', with K a key, C an encrypted text and C' a decrypted text, then it is very unlikely that another cryptographic function F2 veri­.es F2(K, C)= C'.
Sentence 2: the pair ((K, C),C') identi.es F1 with overwhelming probability.
Relationship: entailment
Domain: Security and privacy
Sentence 1: In order to allow sites to match .eld reads and writes, we model these using getter and setter methods.
Sentence 2: we model a .eld read using a call to method getf, which takes the name of the .eld as an argument, and we model a .eld write using a call to a method setf, which takes the name of a .eld and the new value as arguments.
Relationship: entailment
Domain: Security and privacy
Sentence 1: ForwardTraceability: The schemeprovidesforward untraceability if a strong attacker misses M3 just once in a single successful authentication session after com­promising Ti s secret.
Sentence 2: if the attacker cannot  - Server Reader Tag Ti [(ui, ti)new , (ui, ti)old, Di] [ti] r1 .R {0, 1}l r1 - - - .
Relationship: entailment
Domain: Security and privacy
Sentence 1: Equations 2 and 3 can also be used to design criteria for adaptive transitions.
Sentence 2: an adaptive transition is secure when  N B(T ) - N log(T + 1) - log .j = log(T + 1) + log.N+1 j=1 Here .N+1 is the number of possible new predictions for epoch number N +1.
Relationship: entailment
Domain: Security and privacy
Sentence 1: As such, vik = vn in the second step of the procedure in De.nition 4.6, and this node is not deleted in the second step either (since only nodes vij for 1 = j< k are eligible to be deleted).
Sentence 2: vn is always the second last element in the output of A(p), with the last element being the system call number.
Relationship: entailment
Domain: Security and privacy
Sentence 1: Speci.cally, the NBUE property says [ ][] (1) (1) (1) E Y(r) - z|Y(r) >z= E Y(r).
Sentence 2: similarly, by treating the attack events as a stationary point pro­cess with all attack inter-arrival times having a common marginal distribution, the NBUE property implies that for any z= 0, (1) (1) (1) E[Y(r) - z|Y(r) >z] = E[Y(r)] for i= 1. i+1 i+1 i the expected waiting time for the ith attack is greater than the expected extra-waiting time under the condition that the (i+ 1)th attack has not arrived within time z.
Relationship: entailment
Domain: Security and privacy
Sentence 1: Since such information .ow errors in both servers can be resolved anywhere along the corresponding paths, the corresponding mediator placement can resolve both errors.
Sentence 2: if the merged HIFM mediator is ((u, v)l) this can be mapped to respective mediators ((u1, v1)l1) and ((u2, v2)l2) for the web servers.
Relationship: entailment
Domain: Security and privacy
Sentence 1: This is because the BrightKite graph is highly clustered and it is easy to spread the malware onto nodes that are highly connected.
Sentence 2: with the BrightKite graph and the original activity events, the malware can infect hundreds of nodes after one day, regardless of the click probability, but irrespective of the activity model used, only a few can be infected after one day under the Erdos-Renyi social graph.
Relationship: entailment
Domain: Security and privacy
Sentence 1: Figure 15 shows the effectiveness of de-anonymization when we use different social networks.
Sentence 2: for the Infocom06 dataset we constructed social networks (from DBLP publication database) based on co-authorship information from year 2003, 2004, ··· , 2009 (note that Infocom06 dataset is a mobility trace col­lected from the Infocom conference conducted in 2006).
Relationship: entailment
Domain: Security and privacy
Sentence 1: 4.2 Solving the Correlation Issues in M-GLC As pointed out in [4], one of the major issues in M-GLC is the correlations in the system of linear equations.
Sentence 2: two types of correlations have been studied: (i) collinearity, where gates have the same ratio of Kij values as appearing in Equation (5); and (ii) insu.cient controllabil­ity, where no enough equations can be obtained due to the lack of controllability over the circuit.
Relationship: entailment
Domain: Security and privacy
Sentence 1: All these characteristics of Future Internet systems have a major impact on software design and on the enforcement of role-based access control policies: -the strongly dynamic and open nature of Future Inter­net systems forces the global architecture that includes and coordinates all software modules to be distributed and adap­tive -enforcement mechanisms for RBAC policies need to be tailored to distributed and adaptive software architectures.
Sentence 2: it must be capable of handling architectural changes (e.g., a resource hosted by a node is moved to an­other node) in order to maintain the enforced policy.
Relationship: entailment
Domain: Security and privacy
Sentence 1: In this talk I will begin with a brief look at current trends in the technology scenery and some of the key security issues that are impacting on business and society.
Sentence 2: i will describe the notion that I refer to as increasing threat velocity, with more and more attacks and their dynamic nature, an evolving set of bad guys with different motives and sophisticated easy to use tools readily available for ordinary users to conduct severe attacks.
Relationship: entailment
Domain: Security and privacy
Sentence 1: We claim that Eµ~.B I(X,Y )~µ(p(X,Y);X|Y)= I(X,Y )~µ¯(p(X,Y);X|Y).
Sentence 2: (3) the average amount of information revealed by p with respect to the di.erent distributions µ ~ .B is smaller or equal to the amount of information revealed with respect to ¯µ the concavity works in the right direction.
Relationship: entailment
Domain: Security and privacy
Sentence 1: In this paper, we identify the short­comings of existing solutions and propose ways to overcome their limitations.
Sentence 2: we propose to combine the SCAP components with the trusted computing mechanisms to get their synergy to work -that is: 1) to ensure the cor­rect operation of the SCAP tool and the results it produce by using trusted computing techniques, and 2) to use the SCAP framework for better interpretation of the software stack report sent by the remote platform in traditional re­mote attestation protocol.
Relationship: entailment
Domain: Security and privacy
Sentence 1: MPEG-21 does little to de.ne the scope and form of IPMP tools.
Sentence 2: mPEG-21 does not de.ne a programming or commu­nications interface between MPEG-21 terminals and IPMP tools, and it is unclear how IPMP tool implementors could construct tools to work with any MPEG-21 implementation.
Relationship: entailment
Domain: Security and privacy
Sentence 1: Note that while we focus on Tresor as a case study, the techniques we employ generalize to any com­bination of CPU-bound disk encryption scheme, IA32-based OS, and DMA-capable hardware bus.
Sentence 2: while incorporating OS-speci.c knowledge would greatly simplify the attack and would clearly be desirable should this infor­mation be con.rmed for a particular target we show that OS-speci.c details are not required, and that the attack is equally applicable to Windows, Mac OS X, and Linux with­out apriori knowledge of which OS is deployed on the tar­get.
Relationship: entailment
Domain: Security and privacy
Sentence 1: As discussed in [14], however, doing so necessitates a slight change in the UC framework itself.
Sentence 2: when considering the multi-session extension of FG KE one needs to augment the basic UC model with a no­tion of session-state corruption which is intended to capture the same sort of attacks modeled by the Reveal oracle in the de.nition of AKE-security.
Relationship: entailment
Domain: Security and privacy
Sentence 1: For each state s and each input symbol x, 8(s,x) = 8~(x) ifx e Xs 8(s,x) = 8(~(s),x) ifx ~ E~ and s :~ So, ~(so, x) = s~ ifx ~ ~]s0.
Sentence 2: if there is a transition from s labeled x, it defines the following state.
Relationship: entailment
Domain: Security and privacy
Sentence 1: The value Info(PXY ) contains relevant information about the certi.cate PXY , shared by the servers X and Y ,which is similar to the information contained in standard public­key certi.cates.
Sentence 2: info(PXY ) has to minimally contain the identity strings IX and IY , inception and expira­tion dates, details about the encryption and authentication algorithms employed, certi.cate and key unique identi.ers (in case of multiple keys), and the identity of the creator of the certi.cate.
Relationship: entailment
Domain: Security and privacy
Sentence 1: Automatic Web Services Composition in Trust-aware Communities Fahima Cheikh Institut de Recherche en Informatique de Toulouse, 118, route de Narbonne 31062 Toulouse, France cheikh@irit.fr ABSTRACT The promise of Web Service Computing is to utilize Web ser­vices as fundamental elements for realizing distributed ap­plications/solutions.
Sentence 2: when no available service can satisfy client request, (parts of ) available services can be composed and orchestrated in order to satisfy such a request.
Relationship: entailment
Domain: Security and privacy
Sentence 1: Typed code can still interact with previously untyped code, and we need to control such interactions.
Sentence 2: it should not be possible for previously untyped code to con­sume values of type Any(READ, ) or produce values of type Any( , WRITE) if READ or WRITE are non-.. Fortunately, a simple set of constraints in our core discipline (omitted here) suf.ce to eliminate such .ows.
Relationship: entailment
Domain: Security and privacy
Sentence 1: Once the sink acquires drj , it veri.es all authentication tags involving that value.
Sentence 2: to verify drj , the sink must compute: Hjr using Kjr and {Kqr,drq}sq .Rr j {Hqr}sq .Sr using {Kqr,drq} and {Kpr ,dpr }sp .T r where jj S Tjr = { sl .Sr Rlr} j By Tjr wedenotetheset of sensorsthathaveatleast oneco­authenticatorin common with sj at round r. As an example, Figure 1 shows a network where the colored sensors are the onesinvolvedin the authentication of a value sensedby sj at round r. An arrowbetweensp and sq means that sq .
Relationship: entailment
Domain: Security and privacy
Sentence 1: Changes to these PinUP policies canbe made,butevery change requiresper-use user authentication (similartothe administrative interfacesoftheOSXoperatingsys­tem).
Sentence 2: userprocessesdonothavethe abilitytomod­ify PinUP policy.We detail the implementation of the PinUP sys­tem in an extended technical report [7], and defer design issues to that text.
Relationship: entailment
Domain: Security and privacy
Sentence 1: It is important to investigate the relationships between landmark and arbitrary window models because they enable us to draw on the rich experience of research on the large­.ow problem over landmark windows [10,14,17,18,23,29 31] for designing arbitrary-window algorithms.
Sentence 2: we are interested in knowing whether and to what extent we can leverage existing landmark-window algorithms to build arbitrary-window ones.
Relationship: entailment
Domain: Security and privacy
Sentence 1: Moreover it is possible to pick up the parameters in such a way, that one ore both of numerical knapsacks of dimension m are injective.
Sentence 2: having for example a = 1, b= 2, we will two consequent numerical knapsacks of dimension m=4 too: A = (21, 25, 29, 37, 38) =4 (22, 23, 31, 35, 39) = B.
Relationship: entailment
Domain: Security and privacy
Sentence 1: Some manufacturers have already considered the solution of using non-volatile memory as an enhanced caching mecha­nism for the hard disk.
Sentence 2: samsung and Seagate have released prototype hybrid hard drive (HHD) that may contain 256 MB of .ash memory in addition to the tra­ditional hard disk platters.1 These drives are marketed to work with the Microsoft Windows Vista operating system, which includes ReadyDrive , an OS component allowing use of a hard drive s .ash memory as an extended read/write cache.
Relationship: entailment
Domain: Security and privacy
Sentence 1: This knowl­edge on pointers can help obtain a big picture of the entire kernel object graph and bene.t security analysis on this graph (e.g., ker­nel rootkit detection).
Sentence 2: our goal is not to reverse engineer the kernel data structure de.nitions as REWARDS [22] and Howard [29], although our technique can be combined with these techniques to improve the quality of data structure reverse engineering.
Relationship: entailment
Domain: Security and privacy
Sentence 1: For this reason, we can also de.ne the Jensen-Shannon divergence as: DKL(p1||p¯) + DKL(p2||p¯) JS(p1,p2)= 2 where p¯=(p1 + p2)/2.
Sentence 2: the Jensen-Shannon divergence is the average of the KL-divergences to the av­erage distribution.
Relationship: entailment
Domain: Security and privacy
Sentence 1: instead of (×), which implies that such a user would have the ability to make use of an identity system regard­less of the identity management architecture adopted by the RP or the SP.
Sentence 2: this integration model is designed to resolve the incompatibility situation that may occur if the IdP is Liberty-enabled and the RP is CardSpace-enabled, or vice versa.
Relationship: entailment
Domain: Security and privacy
Sentence 1: STATUS The majority of our e.ort so far has gone into the de­sign and implementation of the Breeze language and the ISA, with accompanying formal speci.cations, interpreters and simulators.
Sentence 2: we have already de.ned a Coq semantics for the ISA, from which we can extract an executable simulator; we will use this simulator to cross­validate our FPGA-based implementation of the Safe hard­ware.
Relationship: entailment
Domain: Security and privacy
Sentence 1: Others include exploration of less drastic approaches about what to do when a container misbehaves (e.g., merely suspend its access to its key, rather than revoking its certi.­cate), providing for inter-container communication (our goal had been isolation), and exploring more thoroughly the e.ec­tiveness of our enforcement measurements against actively malicious code.
Sentence 2: (it is rumored that DTRace may have a TOCTOU issue.)
Relationship: entailment
Domain: Security and privacy
Sentence 1: The goal was to design cryptosystems in such a way that the encryption operation commuted with the operations on plaintexts.
Sentence 2: the desired property was to be able to construct an encryption scheme such that you would obtain the same result by multiplying two plaintexts and then encrypting the result, or, by .rst encrypting two plaintexts and then multiplying their corre­sponding ciphertexts.
Relationship: entailment
Domain: Security and privacy
Sentence 1: We optimize for this block size by dividing the input malware set so each node works on 2,048 mal­ware samples at a time because 64MB = 32KB × 2048.
Sentence 2: each MAP task is given 2,048 samples (si,si+1, ··· si+2047) and generates a single .le containing all .ngerprints.
Relationship: entailment
Domain: Security and privacy
Sentence 1: To determine whether a userset X satis.es a term f under a con.guration (U,UR), we .rst compute the syntax tree T of f. When constructing T, an 1CF term (i.e., a term of the form f or f+,where f is a unit term, see De.nition 7) is treated as a unit and is not further decomposed.
Sentence 2: the leaves in T correspond to sub-terms of f that are 1CF terms and the inner nodes correspond to binary operators connecting these sub-terms.
Relationship: entailment
Domain: Security and privacy
Sentence 1: INSECURITY OF SPLITTING THE PRI- VATE KEY MULTIPLICATIVELY We show that splitting the joint private key d multiplica- tively renders our protocol insecure.
Sentence 2: if d is split multiplicatively, the cosigner can create multisignatures on his own without the help of the primary signer, That is, the cosigner is able to use the three keys available to him-- partial private key d2, partial public key el, and the joint public key e--to compute dl.
Relationship: entailment
Domain: Security and privacy
Sentence 1: 5.2 Modelling Delegation and Revocation in SMV We have also modelled delegation and revocation policies as discussed in section 2.3.
Sentence 2: we can handle two kinds of delegation: We can delegate all the access rights required to execute a task (task delegation) and secondly, we can delegate single access rights irrespective of delegating a corresponding task.
Relationship: entailment
Domain: Security and privacy
Sentence 1: Figure1: Con.ckerMutexCheckingLogic  While this mutex checking helps Con.cker to avoid double in­fections, we can also use this fact to against it.
Sentence 2: if we can deliberately craft the same mutex names on a clean machine, then thismachine canbeimmunefromfutureCon.ckerinfection.This is aperfect example of malware vaccines.
Relationship: entailment
Domain: Security and privacy
Sentence 1: Each such R3 is surely anchored , therefore the O(1) keys for it can be obtained in constant time from one of the four structures AL(v), AR(v), AT (v), AB(v).
Sentence 2: we .rst index to the appropriate Vj data structure for left-and right­anchored rectangles (and Hj for top-and bottom­anchored rectangles) and then retrieve the right keys from it in constant time (as in [4]).
Relationship: entailment
Domain: Security and privacy
Sentence 1: In the future, the authors believe that information security risk assessments should focus not just on identifying risks, but also on quantifying them.
Sentence 2: information security risks should be characterized in Financial terms, as annualized loss expectations Once risks are identified and quantified, the resulting data should be reported (by the information risk management professionals, in a way that respects their ethical obligation to protect the privacy of those they treat) to the information risk equivalent of a public health service.
Relationship: entailment
Domain: Security and privacy
Sentence 1: If the other client devices can be of.ine at different times or do not have any secure means of communicating directly with each other (except through storing and retrieving data on the untrusted server itself), then the user s data can be vulnerable to a replay attack by a malicious third-party server.
Sentence 2: a second client device retrieving data from the server would have no way of knowing if the data on the server is in fact the latest version.
Relationship: entailment
Domain: Security and privacy
Sentence 1: 3.2.3 Effect of Scanning Rate: While we have shown that even at 350 scans per second tele­scopes of reasonable size can be successfully used to infer the ac­tual infection evolution (at least during the early stages), we are also interested in evaluating the impact of scanning rate on this accuracy.
Sentence 2: we consider two aspects, namely, (i) the impact of varying the scanning rate and (ii) the impact of scanning rate inhomogeneity which has been observed particularly for band­width limited worms (e.g., UDP worms like Witty [15]).
Relationship: entailment