sadat2307/MSciNLI huggingface dataset:
Domain: Security and privacy
Sentence 1: The main e.ect is in­deed to fragment the original clusters into a high number of smaller clusters.
Sentence 2: after the insertion of m = 20 data points, i.e., when 20% of the data is controlled by the attacker, the selected number of clusters increases from 4 to about 7-14 clusters depending on the considered method.
Relationship: entailment
Domain: Security and privacy
Sentence 1: Since request packets contain no input from the capability-granting destination to allow distinctions between desired and undesired requests, the best the network can do is provide an equal level of service to all requesters.
Sentence 2: each requester should receive a 1 share of the available nm +ng request channel ., regardless of whether that node is an attacker with a high request rate or a legitimate node with a low request rate.
Relationship: entailment
Domain: Security and privacy
Sentence 1: Since a MCB path has some desired patterns, e.g., typically con­taining a sinkhole point of network transmission routines such as a send library call, it makes sense to choose paths that likely reach these sinkholing routines.
Sentence 2: to expand such limited small number of sinkholing routines to a larger hit surface, we introduce the concept of Function Containers to assist directed exploration.
Relationship: entailment
Domain: Security and privacy
Sentence 1: Certain design guidelines that aim to protect the privacy of both raters and ratees have been proposed in the literature.
Sentence 2: while [13] proposes to limit the number of possible reputation values in order to hamper an adversary s ability to re-identify oth­erwise anonymous ratees, [15] proposes to compute a ratee s reputation only after multiple ratings for the ratee have been collected.
Relationship: entailment
Domain: Security and privacy
Sentence 1: It is worth mentioning that even though, strictly speak­ing, XACML v2 considers a four-valued decision set, some combining algorithms distinguish the case where Indeterminate is obtained from a permit rule and the case where Indeterminate is obtained from a deny rule; however, such a distinction is not explicit.
Sentence 2: the seman­tics of decision Indeterminate might change according to the e.ect of the policy that returned it.
Relationship: entailment
Domain: Security and privacy
Sentence 1: Furthermore, the recoding mechanism must satisfy a natural simulation requirement: namely, we can generate rk given just pk0, pk1 (and neither of the two secret keys), if we are allowed to program pktgt .
Sentence 2: there are three ways of generating the pair (pktgt , rk) that are (statistically) indistinguishable: (1) given pktgt , generate rk using the secret key sk0; (2) given pktgt , generate rk using the secret key sk1;and (3) generate rk without either secret key, by programming the output public key pk tgt .
Relationship: entailment
Domain: Security and privacy
Sentence 1: Addressing such issues in an appropriate way presents a major challenge for research and industry.
Sentence 2: we can observe that current e-health solutions and standards mainly focus on network security and access control policies, however, they do not address the client platform security ap­propriately [26], i.e., the security of the software and hard­ ware that is used by health professionals locally.
Relationship: entailment
Domain: Security and privacy
Sentence 1: Realizing this space has legal as well as technical dimensions that need to go hand in hand.
Sentence 2: we have argued for a geoprocessing license model which does not license data but its use, an ontology of geoprocessing, which distinguishes actions and purposes and allows machines to compare them against a license, as well as a permission service which allows users to issue processing requests for private data of citizens and (semi-)automatically grants processing rights.
Relationship: entailment
Domain: Security and privacy
Sentence 1: Command Name Code Description CMD ERROR 0x200 + 0 General Error CMD SUCCESS 0x200 + 1 Cmd Successful CMD GET NODE INFO 0x500 + 0 Get node information CMD GET NODE SUCCESSOR 0x500 + 1 Get node successor CMD GET NODE PREDECESSOR 0x500 + 2 Get node predecessor CMD UPDATE PREDECESSOR 0x600 + 1 Update predecessor info CMD UPDATE SUCCESSOR 0x600 + 2 Update successor info CMD LOOKUP NODE 0x600 + 2 Perform a lookup CMD LOOKUP FEDERATION 0x600 + 2 Federation participation CMD PKI MESSAGE 0x800 + 0 PKI Data Packet of processing PKS messages.
Sentence 2: when a message is received via the PKS network, the Respon­der Engine unwraps the PKI message embedded in the rawBytes .eld.
Relationship: entailment
Domain: Security and privacy
Sentence 1: We believe that to achieve ef.cient execution of a broad range of functionalities, the available options for parallelizing the execution should not be either too narrow or unnecessarily too .exible.
Sentence 2: the parallelism offered by Sharemind and SEPIA will allow for ef.cient execution of many functionalities, but can be very limiting for other applications and operations.
Relationship: entailment
Domain: Security and privacy
Sentence 1: One of the inno­vations introduced in our work is the de.nition of a di.erent representation model: buckets are represented implicitly by storing the hierarchical partition overlying the histogram, whose representation can be accomplished more e.ciently than the explicit representation of bucket boundaries.
Sentence 2: the hierarchy adopted for determining the structure of a histogram is also used as a basis for representing it, thus introducing surprising e.ciency in terms of both space con­sumption and accuracy of estimations.
Relationship: entailment
Domain: Security and privacy
Sentence 1: Since one the most important concerns in the IoT is energy­e.ciency, we consider the Bell Laboratories Layered Space-Time (BLAST) multi-antenna scheme [16].
Sentence 2: the Vertical BLAST (VBLAST) architecture [17, 18] has been implemented in our experiments in order to keep the com­plexity and power consumption as low as possible.
Relationship: entailment
Domain: Security and privacy
Sentence 1: This can be achieved by exploiting a vulnerable deputy [15, 10, 17], or by malicious colluding applications [37, 5].
Sentence 2: privilege esca­lation attacks have been utilized to send unauthorized text messages [10], to trigger malicious downloads [24, 29], to change the WiFi settings [17], or to perform context-aware voice recording [37].
Relationship: entailment
Domain: Security and privacy
Sentence 1: However, we found that the linking process can be exploited to launch a serious login CSRF attack, without any malicious app running on the user s device.
Sentence 2: in our attack, the adversary uses the 3 URL arguments collected from his own device to build a URL: db-://1/connect?oauth_token &#38;oauth_token_ secret &#38; uid , where oauth_token , oauth_token _secret , and uid are the adversary s Dropbox credentials, and APP_ID identifies the PlainText app.
Relationship: entailment
Domain: Security and privacy
Sentence 1: A Tale of Two Kernels: Towards Ending Kernel Hardening Wars with Split Kernel Anil Kurmus Robby Zippel IBM Research Zurich, SwitzerlandIBM Research Zurich, Switzerland kur@zurich.ibm.com zip@zurich.ibm.com  ABSTRACT Software security practitioners are often torn between choosing per­formance or security.
Sentence 2: oS kernels are sensitive to the smallest performance regressions.
Relationship: entailment
Domain: Security and privacy
Sentence 1: In this paper, we propose a privacy preserving protocol that assesses signal quality and combines this with a linear classi.er used to decide whether the measured signal is of high enough quality or not.
Sentence 2: the protocol computes a frame based Signal-To-Noise Ratio (SNR) from the original signal and a .ltered version of the signal itself; evaluates the mean and the variance of the SNRs obtained and computes the overall signal SNR.
Relationship: entailment
Domain: Security and privacy
Sentence 1: On validating B s integrity, specifically, A will compute the checksum of B s code stored in the physical storage (using a secure cryptographic hash function) and compare with the true value pre-computed and injected to A s code by D (with cooperation of P in case of A being GC).
Sentence 2: gC will validate-then-activate GC-agent, which will do the same with GG (which may do the same with other modules in a more refined model).
Relationship: entailment
Domain: Security and privacy
Sentence 1: This prob­lem has then been solved by means of specialized search heuristics speci.cally tailored to the considered clustering algorithm.
Sentence 2: we have considered greedy opti­mization approaches in which the attacker aims to maxi­mize the objective function by adding one attack sample at a time, i.e., |A ' | = m = 1.
Relationship: entailment
Domain: Security and privacy
Sentence 1: , mju ) and a proof p vouching for the correctness of y.
Sentence 2: when F consists of all linear functions, such MACs or sig­natures have been constructed under the name of linearly homomorphic MACs or signatures [1, 19, 9, 7, 15, 17, 2, 3, 4, 11, 12].
Relationship: entailment
Domain: Security and privacy
Sentence 1: 4.2 SSH Command Attestation We have added human attestation to the Dropbear 0.52 [1] SSH client/server suite so that each ssh command carries an attestation signature and the server veri.es the signature before launching the command.
Sentence 2: for every enter key, we send the signature to the server for human veri.cation.
Relationship: entailment
Domain: Security and privacy
Sentence 1: This test established a baseline of the number of connections per second each cipher suite could handle without any puzzles or denial of service countermeasures.
Sentence 2: (for the FVDS-based cipher suite, FVDS signatures from Section 3.1 were used for client authentication but the FVDS-puzzle protocol of Section 3.2 was not used.)
Relationship: entailment
Domain: Security and privacy
Sentence 1: Kolb had this to say about the interplay among the different learning styles; This, the structural model of learning can be likened to a musical instrument and the process of learning to a musical score that depicts a succession and combination of notes played on the instrument over time Since each Information Assurance Class contains students utilizing each learning style, Kolb s model indicates that moving the class through each quadrant should optimize learning.
Sentence 2: optimizing the learning process requires the appropriate succession and combination of learning activities.
Relationship: entailment
Domain: Security and privacy
Sentence 1: First, is it possible to make an involuntary localization of a random LBSN user by exploiting the public available information only?
Sentence 2: without hacking into the services and using only the client side information that is publicly available through the unmodi.ed app of LBSNs, could we accurately localize a random online user of no priori knowledge?
Relationship: entailment
Domain: Security and privacy
Sentence 1: Based on this observa­tion, we devised a search heuristic that considers only k-1 potential attack samples, being k the actual number of clus­ters found by the single-linkage hierarchical clustering at a given dendrogram cut.
Sentence 2: we only considered the k-1 points lying in between the connections that have been cut to separate the k given clusters from the top of the hierarchy, highlighted in our example in the leftmost plot of Fig.
Relationship: entailment
Domain: Security and privacy
Sentence 1: OncetheoptimalLPPM o.ersthe maximal location privacy for a given user pro.le, loosening the service-quality constraint does not signi.cantly change the LPPM s underlying function f, and thus there is no reduction in service quality.
Sentence 2: there is no need to sacri.ce the service quality, because doing so does not increase the user s location privacy.
Relationship: entailment
Domain: Security and privacy
Sentence 1: We provide a tool for a workflow designer to specify a data access policy for each task.
Sentence 2: each task has its associated data access policy that has a series of the following triples, : [{Data object, field name, permission}, { }, ]  declares that this is a data access control assignment for task n. The permission in this statement can either be read-only, full-control, no-access, etc.
Relationship: entailment
Domain: Security and privacy
Sentence 1: From this collection of observations he should not be able to increase the precision of his knowledge on the real position up to some de.ned and .xed parameter chosen by the user.
Sentence 2: if the user decides he wants to obfuscate his position up to a radius of 5 Kms, then an adversary should not be able to reduce this area any further by making multiple location requests.
Relationship: entailment
Domain: Security and privacy
Sentence 1: [10] discussed the security of the original Rainbow Rainbow(K; v1, o1, o2) with two lay­ers and the .nite .eld with 256 elements, K = GF (256).
Sentence 2: rainbow(GF (256); 31, 19, 24) has 100-bit against direct attacks, UOV-Reconciliation attack, Rainbow-Band-Separation attack and UOV attack.
Relationship: entailment
Domain: Security and privacy
Sentence 1: Image Integrity Informally, the OS, programs, and data making up the customer s image must have the contents intended by the customer at the time of each instance launch.
Sentence 2: the sequence of management operations image installation, image customization, and instance launch given an image have the same effect on instance launches (i.e., cause the same image to boot upon instance launch) as they would have if the customer were executing these operations on a trusted exclusive platform.
Relationship: entailment
Domain: Security and privacy
Sentence 1: To simplify our proofs later, we will assume an ideal PUF, meaning that there is no predictable connection between the challenges and responses.
Sentence 2: assume an observer has knowledge of (Ci,Ri) and another challenge Ci' , where Ci and Ci ' di.er in only a single bit, the observer can predict the corresponding Ri ' with only negli­gible probability.
Relationship: entailment
Domain: Security and privacy
Sentence 1: Moreover, obligations, in the sense of provisional authorizations, can be understood under a gen­eral interpretation of can .
Sentence 2: for a principal p .P to do action a on resource r at time t the can requires a willingness by the party that controls access to r to allow access on the basis of p s promise to perform an act at some time point t. such that t. >t.
Relationship: entailment
Domain: Security and privacy
Sentence 1: While an ideal PUF is assumed to produce random mappings, we employ the hash function in this way to add to the entropy of the system.
Sentence 2: if Ri and Rj (the responses produced by two di.erent PUF pollings) di.er by only a single bit, H(Ri) and H(Rj ) will have a Hamming distance of 128 bits on average.
Relationship: entailment
Domain: Security and privacy
Sentence 1: We remind the reader that the attacker s goal in this case is to manip­ulate some samples to have them clustered according to a desired criterion, without a.ecting signi.cantly the normal system operation.
Sentence 2: we assume here that the attacker can manipulate samples corresponding to the digit 3 in order to have them clustered together with the cluster corresponding to the digit 6 , while preserving the initial clusters.
Relationship: entailment
Domain: Security and privacy
Sentence 1: A few weaknesses of the system, such as permission re-delegation [21] and capability leaks [27], are revealed by researchers.
Sentence 2: a recent blog [16] from Leviathan Security Group describes the malicious activities that could be performed by an app without any permissions, including reading from SD card, accessing a list of installed apps, getting some device and system information (GSM and SIM vendor ID, the Android ID and kernel version) and pinging through a Linux Shell.
Relationship: entailment
Domain: Security and privacy
Sentence 1: It has been shown that RP and .P coincide [11, 13].
Sentence 2: for ex- Recall that for a program P a quantitative policy is a ample for the modulo program above under the assumption natural number N which limits the cardinality of .P to N. of uniform distribution on the input there are 4 equivalence a program violates a quantitative policy if classes each having probability 1 4 .
Relationship: entailment
Domain: Security and privacy
Sentence 1: 3.2 Test Results After the installation and user enrollment issues were worked out, the resulting test of PGP Desktop for Macintosh on a departmental MacBook was successful.
Sentence 2: iTSG determined that policy settings were appropriately enforced, whole disk recovery tokens (WDRT) were generated for Mac users and were successfully used by ITSG to gain access to an encrypted drive, and the PGP software was compatible with other standard departmental software including Adobe Creative Design Standard, Microsoft Office, Parallels Desktop, VMware Fusion, iPhoto, and iMovie.
Relationship: entailment
Domain: Security and privacy
Sentence 1: An environment pattern can be empty, denoted by f, which is most general; every state matches f.We say that e1 is subsumed by e2,i.
Sentence 2: : the set of all environment states that match e1 is a sub­set of the set that match e2.subsume(e2,e1), i.: {s|e1(s)}.{s|e2(s)}.
Relationship: entailment
Domain: Security and privacy
Sentence 1: Namely, with overwhelming prob­ability, the output s of Sinj describes an injective function fs that F -1 inverts correctly on all values in the image of fs.
Sentence 2: ltdf there is only a negligible probability (over the choice of s)that fs(·) is not injective or that F -1 (t, ·) ltdf incorrectly computes fs -1(·) for some input.
Relationship: entailment
Domain: Security and privacy
Sentence 1: An attacker successfully forges a signature if he/she is able to ensure the forged group-g signature elements lie on any ng one-way chains from the set Gg; the forged group-(g - 1) signature elements lie on ng-1 one-way chains from the set Gg-1 that are distinct from previously chosen one-way chains; and so on.
Sentence 2: the number of ways to forge a signature is rng rnr-1 +(r - 1)ng ··· ng ng-1 rn1 +(r - 1)(ng + ng-1 + ·· · + n2) n1 } g rng g-1 rni +(r - 1) nj j=i+1 = .
Relationship: entailment
Domain: Security and privacy
Sentence 1: The plan p satis.es constraint (.,s,s 1), for example, if the same user is assigned to both steps by p,and satis.es constraint (.c ,s,s 1) if di.erent users are assigned to s and s 1 .
Sentence 2: these represent, respectively, binding-of-duty and separation-of-duty constraints.
Relationship: entailment
Domain: Security and privacy
Sentence 1: Timestamping Using Time-Lock Puzzles.
Sentence 2: given an ß­sound time-lock puzzle (Gen, Sol, Ver), we can envision (Sol, Ver) as de.ning a timestamping scheme that is ß-sound against documents in the distribution generated by Gen. when Bob receives a document D at time T and wants to timestamp it for duration d, he treats D as the puz­zle and solves it for parameter N such that Time(S)= N ·poly(n)= d to obtain the timestamp S. The ß-soundness of the time-lock puzzle guarantees that no adversary running in parallel time less than ß · ParTime(Sol) can convince the veri.er to accept a valid timestamp.
Relationship: entailment
Domain: Security and privacy
Sentence 1: Second, attacks that leverage existing native code, like return-oriented program­ming (ROP) [31], require control-.ow hijacking, which Vir­tual Ghost explicitly prevents as well.
Sentence 2: virtual Ghost enforces Control Flow Integrity (CFI) [3] on kernel code in order to ensure that the compiler instrumentation of kernel code is not bypassed.
Relationship: entailment
Domain: Security and privacy
Sentence 1: Let X be distributed according to proba­bility distribution f. Then the probability that the anoma­lousness exceeds a is no greater than 2-a .
Sentence 2: pf (Af (x) = a) = 2-a Note that for univariate and multivariate Gaussians, this de.nition agrees with the typical de.nitions of anomalous­ness, which are either based on the z-score or Mahalanobis distance.
Relationship: entailment
Domain: Security and privacy
Sentence 1: This technique requires three pre-processed" secret­shared values, say ([u], [v], [w]), unknown to the adversary A, such that w = u · v. Given such a shared multiplication triple, and shared inputs of a multiplication gate, say [x]and [y], the multi­plication gate is securely evaluated using the equation [x · y] = (x - u)· (y - v)+ [v]· (x - u)+ [u]· (y - v)+ [u · v].
Sentence 2: the parties compute the sharings of (x - u)and (y - v), and publicly reconstruct the same.
Relationship: entailment
Domain: Security and privacy
Sentence 1: Since voice call records only contain limited information, such as call time, originating/terminating numbers, country codes and call durations, we explore the relationship among partiesparticipating inthecalls(i.e., whocallswhom ) for the fraud detection task.
Sentence 2: we advance the no­tion of voice call graphs for representing the call records.
Relationship: entailment
Domain: Security and privacy
Sentence 1: 4.2 Overview The main insight of our work is embodied in subject certi.cate policies (SCPs), which bind a policy key pair (i.e., a policy pub­lic key and a policy private key)to parameters governing and pro­tecting the usage of a domain s certi.cates.
Sentence 2: sCPs provide information such as CAs authorized to sign certi.cates for a domain, minimum security levels for TLS parameters, and how certain TLS handshake errors should be handled, as well as which of these requirements also must be respected by certi.cates issued to subdomains.
Relationship: entailment
Domain: Security and privacy
Sentence 1: Furthermore, we show that the circumvention of copy protections is embedded in an active ecosystem, describing its actors and interdependencies.
Sentence 2: the main contributions of this work are:  We collected more than 43, 900 download links and performed automated and manual analysis on more than 23, 100 (3, 551 unique) resulting real-world crack downloads, providing deep insights into how cracks and keygens are used to spread malware.
Relationship: entailment
Domain: Security and privacy
Sentence 1: Also, while it is possible to go through these 2, 437 apps one by one, we .nd that we can still signi.cantly reduce the number of apps that need to be analyzed.
Sentence 2: in­stead of analyzing each app, we opt to analyze each unique path our system detects (as such paths represent the ac­tual behavior of concern).
Relationship: entailment
Domain: Security and privacy
Sentence 1: We evaluate the system on a dataset of 3.4 million benign and 8,282 mali­cious webpages, which has been acquired over a period of 5 months.
Sentence 2: we study the detection performance as well as the learning process over time for di.erent fea­tures and learning methods, such as anomaly detection and classi.cation approaches.
Relationship: entailment
Domain: Security and privacy
Sentence 1: How­ever, depending on the way two parties interact with each other, one s private information may .ow to others in vari­ous forms, which are not always controlled by access control policies.
Sentence 2: the di.erent behaviors of a negoti­ation participant may be exploited to infer sensitive infor­mation, even if credentials containing that information are never directly disclosed.
Relationship: entailment
Domain: Security and privacy
Sentence 1: Since in Twitter, legitimate users tend to follow those accounts that share more useful infor­mation, it is relatively weird that these dummies has close relationships with criminal accounts while sharing little in­formation, but they have many followers.
Sentence 2: we extract intriguing dummy accounts, who post fewer than 5 tweets4 and whose follower numbers are at the top 10­percentile.
Relationship: entailment