sadat2307/MSciNLI huggingface dataset:
Domain: Security and privacy
Sentence 1: AnEAis,indeed, aprincipal(asoftware agent or code) that remotely performs attacks, collects attack data, and generates evaluation information from the attack data under the control of a legitimate RSEP evaluator.
Sentence 2: eAs conduct evaluations, collect and process evaluation data, and store the evaluation results into security pro.les ontheback-end service containers(TOEs).
Relationship: entailment
Domain: Security and privacy
Sentence 1: By doing so, we can encode each value in such a way that arbitrary parties can increase this value by exponentiating the signature, but can­not decrease the value without being able to take roots in the RSA group.
Sentence 2: we encode the signature on the value in a vector dimension as the distance from that value to the maximum value for that dimension, and then embed that distance as a root in the RSA group.
Relationship: entailment
Domain: Security and privacy
Sentence 1: With the addition of the subprotocol, the revised Rabin protocol can now be proven secure assuming it is computa- tionally infeasible to factor the product of two large primes.
Sentence 2: if Bob could cheat Alice with non-negligible proba- bility, he could also factor ra with non-negligible probability without any interaction with Alice at all.
Relationship: entailment
Domain: Security and privacy
Sentence 1: As before, C2 has a second role, which is to help the simulator answer decryp­tion queries (except on the challenge ciphertext), by way of the underlying IBE system.
Sentence 2: a crucial point to note is that, in the Boneh-Boyen IBE, C1 is based on a generator g that in the simulation is passed on unchanged to the adversary, and is independent of the target identity.3 In the KEM, this translates into a chain of maps C1 .. w .. C2 that are preserved in the simulation, and allow the challenge ciphertext to be constructed without cyclic dependencies.4 we have the following result, stated in the con­text of a .xed encoding for simplicity.
Relationship: entailment
Domain: Security and privacy
Sentence 1: 3.3 Proper Axioms in .-.-F IBLPs The application-speci.c information in an ASAC policy speci.cation is expressed by using .ve types of rules:  Aset of rules(AU X ) that de.ne the auxiliary predi­cates that appear in the axioms in .
Sentence 2: ;  A set of rules that specify permission-level assignments (PLA);  A set of rules that de.ne denial-level-assignments (DLA);  5an agent s status normally persists cf.
Relationship: entailment
Domain: Security and privacy
Sentence 1: De.ne the event DBox to hold when M. = M. The lemma states that for all but a negligible fraction, .4, of choices for {Ij }j.
Sentence 2: [m] we have E Pr[DBox] > 24m the tracing algorithm will implicate the PKG for all but a negligible fraction of choices of dummy at­tributes.
Relationship: entailment
Domain: Security and privacy
Sentence 1: By using a zero-knowledge scheme, an attacker could intercept the tra.c between the network and computer or between the computer and the device, but would not garner any useful information.
Sentence 2: finally, by hash­ing Commit(Presult), the tuple, and the nonce, T is creating an integrity check for S. the hash provides a means by which S can con.rm that the tuple was received by T , and the commitment has been forwarded through C intact.
Relationship: entailment
Domain: Security and privacy
Sentence 1: Also, it calculates the physical addresses of the mon­itored regions by simply using the constant o.set between the virtual addresses of the linear-mapped kernel region and their corresponding physical addresses.
Sentence 2: the physical address of the kernel symbol in a linear-mapped region can be calculated by subtracting the linear mapping o.set (i.e., 0xC0000000 ).
Relationship: entailment
Domain: Security and privacy
Sentence 1: HighRank, MinRank, direct, UOV, UOV-Reconciliation (UOV-R), and Rainbow-Band-Separation (RBS) attacks.
Sentence 2: we imposed the following conditions: (1) v1 = o2, (2) o2 ' = d2, and (3) v2 = o2 +o2 ' -d2.
Relationship: entailment
Domain: Security and privacy
Sentence 1: Our approach is based on a very small set of logic predi­cates, which are suitable for modeling the topology of net­works, and a set of derived predicates that express relevant properties of the modeled networks.
Sentence 2: the de­rived predicates introduced in this article formally express anomalous con.gurations of IP packets, which correspond to possible intrusion e.orts by a malicious user.
Relationship: entailment
Domain: Security and privacy
Sentence 1: By using this approach we avoid some well-known dif.culties in proving noninterference directly for the concrete machine.
Sentence 2: when frames allocated in low and high contexts share the same region, allocations in high contexts can cause variations in the precise pointer values returned for al­ 4 It would be interesting to describe an implementation of the memory manager in a still-lower-level concrete machine with no built-in Alloc instruction, but we leave this as future work.
Relationship: entailment
Domain: Security and privacy
Sentence 1: As a proof-of-concept, we present a new technique to break system authentication by designing a malicious VMM built atop a VMI [13] that pulls guest-OS state from the outside VMM and enriches the VMI with context-aware, reactive capability.
Sentence 2: unlike traditional VMI, our VMI requires access to only a small subset of the guest-OS states, but offers write-access to states in addition to read-access.
Relationship: entailment
Domain: Security and privacy
Sentence 1: JK KK H(S|F )= - Nj pij log2 pij (9) N j=1 i=1 where J is total number of branches made after the split caused by applying feature F on dataset S, pij is the prob­ability estimate for class i in branch j.
Sentence 2: h(S|F ) is the weighted sum of the entropy H(Sj ) in each branch j after a split.
Relationship: entailment
Domain: Security and privacy
Sentence 1: In this paper we propose a novel and practical identi.ca­tion and authentication model to be applied for eIDs, which keeps the advantages of user-centricity but allows for selec­tive disclosure possibilities to better protect citizens privacy compared to existing national eID solutions.
Sentence 2: it supports selective disclosure such that any service provider can still verify that the subset of revealed data has been certi.ed by a trusted authority.
Relationship: entailment
Domain: Security and privacy
Sentence 1: Towards Digital Video Steganalysis using Asymptotic Memoryless Detection Julien S. JainskyDeepa KundurDon R. Halverson Texas A&#38;M University Texas A&#38;M University Texas A&#38;M University julienj@tamu.edu deepa@ece.tamu.edu halverson@ece.tamu.edu ABSTRACT This paper studies the potential for passive steganalysis in correlated image frames using non-classical detection the­ory.
Sentence 2: an algorithm for digital video steganaly­sis, named MoViSteg for Motion-based Video Steganalysis, is developed that exploits the temporal correlation among individual image frames in video signals to enhance ste­ganalysis performance.
Relationship: entailment
Domain: Security and privacy
Sentence 1: Furthermore, it is well known that in order to create a secure system, system designers and developers need to consider security aspects on multiple abstraction layers, such as hardware, operating system, and application level.
Sentence 2: for designing secure embedded systems, a careful coordination and integration of applications, operating system, and the deployed hardware is mandatory, given the fact that the op­tions and opportunities of software and hardware are much more diverse than it is the case for the PC world.
Relationship: entailment
Domain: Security and privacy
Sentence 1: 9.3 Server performance To understand whether VE R SU M can support many clients, we measured the throughput that a VE RSUM server can achieve.
Sentence 2: we measured the throughput of three different types of requests that the VER SU M server supports: queries on the output ADS of the Bitcoin computation (proofTxnSpent), prefixes re­quested during the conflict resolution protocol (getPrefix), and DetermineNext proofs requested at the end of the conflict resolu­tion protocol (proofDetermineNext).
Relationship: entailment
Domain: Security and privacy
Sentence 1: The dynamic re-moduling techniques described in this paper may be adaptable for use with IPSec and TLS in long-lived systems, but this is a subject for further re­search.
Sentence 2: our re-moduling protocol relies on clearly distinguished, a priori, parent and child roles which do not exist, in general, between IPSec or TLS nodes.
Relationship: entailment
Domain: Security and privacy
Sentence 1: Notice that the parallel com­putation of Ab and Ay amounts to about 1.2 modular ex­ponentiations.
Sentence 2: the session-key computation of T-KEA takes about 2.2 exponentiations, which is, however, still in sharp contrast to the about 1.27 exponentiations of (H)MQV in such a scenario.
Relationship: entailment
Domain: Security and privacy
Sentence 1: 5) Separation of Concerns: A particular feature of MDSA is that it allows the separation of concerns between involved stakeholders.
Sentence 2: thanks to its model-merging concept, it allows for example unclassified, general-purpose Common Criteria change policy modeling and MDSA toolset development and the accreditation of platforms and unclassified services and components, while the application of the generic models and tools to specific (classified) systems during accreditation is done by cleared personnel.
Relationship: entailment
Domain: Security and privacy
Sentence 1: )= 1] Experiment 1 In this experiment we modify the way the chal­lenger constructs the challenge ciphertext.
Sentence 2: it con­structs the challenge ciphertext as jNs jjNs C = (((1+N)mf )·(r1), ((1+N)mf )·(r2)) (mod Ns+1) where both r1 and r2 are random elements from QR(N).
Relationship: entailment
Domain: Security and privacy
Sentence 1: On the contrary, when a is biased towards the dis­tance to old RBAC con.guration, the overall outlier rate is high, while the distance between the two RBAC con.g­urations is signi.cantly smaller.
Sentence 2: we .nd that the outlier rate corresponding to a = 1 is 41.1% and 87.7% lower than that corresponding to a = 0 on the EMR and synthetic datasets, respectively.
Relationship: entailment
Domain: Security and privacy
Sentence 1: Conversely, if p is a plan for C then it is a plan for G1 .···.Gc and there exists a work.ow expression of the form .1 .···..c for which p is a plan.
Sentence 2: p is a plan for C if and only if it is a plan for .1 .···..c for some .i .Gi, where .i is a Type 1 constraint and .1 .···..c represents the constraint set {.1,..., .c}.We call .1 .···..c a simple constraint expression.
Relationship: entailment
Domain: Security and privacy
Sentence 1: As we assume an originator has put limited trust on her col­laborating organizations based on pre-established relation­ships, we introduce a special type of administrative delega­tion, called Delegation of Delegation Authority (DoD), as another layer of authority decentralization to achieve dis­tributed role assignment.
Sentence 2: doD enables an originator to partially delegate the role assignment author­ity to trusted collaborating organizations or trusted individ­uals.
Relationship: entailment
Domain: Security and privacy
Sentence 1: proposed two approaches [40, 14] that use memory address-space randomization (ASR) to foil exploit attempts, and then automatically generate sig­natures through forensic analysis of the related exceptions.
Sentence 2: cOVERS [14] was the .rst to propose a novel construction of application-level signature which uses .eld length to characterize a bu.er over.ow vulnerability.
Relationship: entailment
Domain: Security and privacy
Sentence 1: With the adopted r key evolution, if si is removed from Rj ¯, the sink will not be able to correctly compute Kjr¯+1 .
Sentence 2: sj would r¯+1 r¯r compute Kj = F(Kj ||Rj ¯)while the sink would compute r¯+1 r¯r it as Kj = F(Kj ||Rj ¯{si}).
Relationship: entailment
Domain: Security and privacy
Sentence 1: Table 2-1, Learning Dimensions and selected attributes Dimension Dialectic Mode Style Grasping (Perceiving) Experience Appre­hension Direct apprehension of immediate comprehensive experience Concrete Experience Compre­hension Indirect comprehension of symbolic representations of experience Abstract Conceptualization Transforming (Processing) Experience Intension Intentional reflection Reflective Observation Extension Extensional action Active Experimentation The grasping, or perceiving, dimension exists between the dialectic of Concrete Experience (CE) and Abstract Conceptualization (AC).
Sentence 2: the grasping dimension represents two different methods for perceiving, or taking in materials i.e.
Relationship: entailment
Domain: Security and privacy
Sentence 1: In all cases the fitness function takes the form of Algorithm 2, augmented with an additional term to measure the likelihood of an attack being executed.
Sentence 2: since all individuals have a fixed length of 30 instructions and it takes 11 instructions to describe the attack, there are up to 19 instructions denoting introns with respect to the malicious code (effective NOPs).
Relationship: entailment
Domain: Security and privacy
Sentence 1: 4.1 Attacker and User models In this scenario where the user is willing to move while a certain degree of uncertainty about his precise location is retained, it is necessary to clearly de.ne what are the assumptions made on both the user and the adversary side.
Sentence 2: it is important to de.ne the capabilities of the user in terms of the movement and the adversary in terms of the number of location responses he might obtain.
Relationship: entailment
Domain: Security and privacy
Sentence 1: In ad­ dition, by gaining more followers, Twitter criminal accounts can evade existing detection approaches such as Twitter Rules and break through Twitter s Follow Limit Policy 1 , while maintaining their high visibility.
Sentence 2: accord­ ing to Twitter Rules [8], a Twitter account can be consid­ ered to be spamming, and thus be suspended by Twitter, if it has a small number of followers compared to the amount of accounts that it follows.
Relationship: entailment
Domain: Security and privacy
Sentence 1: The building blocks are general enough to be used in other protocols for forecasting and benchmarking, as well as in other applications.
Sentence 2: the division protocols pre­sented in this work, to the best of our knowledge, are the .rst attempt to perform division in secure multi-party computa­tion as well as to perform computations on .oating point numbers.
Relationship: entailment
Domain: Security and privacy
Sentence 1: Backlisted fraction: Measures the amount of IP address space we blacklist , as a fraction of total IP address space.
Sentence 2: blacklisting fraction for any one netblock and held out IP address (one experiment) is the ratio of the size of the union of the clusters that contain the B - 1 mali­cious IP addresses to the total size of that netblock.
Relationship: entailment
Domain: Security and privacy
Sentence 1: In our vision of a true Web SSO system, a user should log into her IdP once and gain access to all websites that she has an account with, without being prompted to login again on each website.
Sentence 2: when accessing N RPs using one IdP, the user should provide her credential exactly once to the IdP, consent at most N times (one for each RP if the consent was not recorded for future use), and should perform a logout process only once from the IdP.
Relationship: entailment
Domain: Security and privacy
Sentence 1: The reason why we use a XOR gate is that its output can serve as an indicator of whether gate i switches or not.
Sentence 2: if we assume that the original section of the dual circuit represents the status as of clock cycle t, and the dual section represents that of clock cycle t + 1, we claim that the output signal of the XOR gate i '' is 1 if and only if gate i switches from clock cycle t to t + 1.
Relationship: entailment
Domain: Security and privacy
Sentence 1: Using Hall s matching theo­rem, any schedule should have at least d+ 1 tokens in the duration of [ti(j-d),t(N) + .].
Sentence 2: at least d+1 (N) tokens should be scheduled after ti(j-d) at t.As DLP do not have dummy tokens for fi after ti(j-d), DLP uses exactly d+ 1 tokens during [ti(j-d),t(N) + .].
Relationship: entailment
Domain: Security and privacy
Sentence 1: To address that, we propose a key technique called re­turn indirection, which is inspired by the nature of return­oriented programming: namely it requires the attacker to supply return addresses of his choice to pinpoint and execute various gadgets.
Sentence 2: during the attack, these re­turn addresses need to be pre-populated by the attacker (and therefore not saved from previous call instructions).
Relationship: entailment
Domain: Security and privacy
Sentence 1: Maliciousness For monitoring the malicious score of each AS and, at the same time, convey the idea of maliciousness as related to the magnitude of activity, each AS bubble is formed by a set of overlapping circles that continuously shift their po­sition, both horizontally and vertically, with offsets propor­tional to the AS s maliciousness score.
Sentence 2: the wider bubble vibrates , the more the AS is rogue.
Relationship: entailment
Domain: Security and privacy
Sentence 1: For a set of authorizations cai.caki, i = 1, ,n, we use (cai.caki)- to denote any set of authorizations obtained by reversing the sign of a subset or all of the authorizations in cai.caki.
Sentence 2: for each specific authorization cai.caki, (cai.caki)- has (2n+1-1) possibilities, considering there are (n+1) concepts in cai.caki, i = 1, ,n. we use ca- to denote the authorization having the same components as ca except that ca and ca- have the opposite sign.
Relationship: entailment
Domain: Security and privacy
Sentence 1: In this context, ensuring prover privacy with respect to Man-in-the-Middle (MIM) adver­saries in authentication and distance-bounding protocols is no longer su.cient.
Sentence 2: in any authentication pro­tocol insiders such as veri.ers and the managing back-end server can potentially forward users data to governmental agencies or to other third parties.
Relationship: entailment
Domain: Security and privacy
Sentence 1: BLADE s design principle, unconsented-content execution pre­vention, is motivated by a fundamental practice in the way browsers handle web stream content.
Sentence 2: when receiving data content from a web server, browsers handle the content they receive in either of two basic ways: supported .le types (e.g., html, jpeg, pdf) and unsupported .le types (e.g., exe, zip).
Relationship: entailment
Domain: Security and privacy
Sentence 1: For example, if an administrator chooses to place a server behind a .rewall as part of a strategy, it may involve additional cost as well as bring down the response-time of the system; or if he/she chooses the countermeasure of temporarily increasing the access privileges needed to access a server host before it is patched, the server might have to deny requests from clients without higher privileges for the time being.
Sentence 2: the administrator may prefer to include some countermea­sures over others in his/her strategy, based on factors such 1We abuse notation here by using the mapping .
Relationship: entailment
Domain: Security and privacy
Sentence 1: 2 Overview of Amazon EC2 The Amazon Elastic Compute Cloud (EC2) is an Infrastructure­as-a-Service cloud provider where users can rent virtualized servers (called instances) on an hourly base.
Sentence 2: each user is allowed to run any pre-installed virtual machine image (called Amazon Machine Image, or AMI ) on this ser­vice.
Relationship: entailment
Domain: Security and privacy
Sentence 1: Since, the columns of the master matrix is permuted ran­domly during the code generation, the t-marked positions in the blocks of Ms+1,2s+2t and Ms+1,2s+1 are masked with that permutation.
Sentence 2: the traitor coalition will not be able to di.erentiate a t-marked position in block Ms+1,2s+2t from a t -marked position in block Ms+1,2s+1.
Relationship: entailment
Domain: Security and privacy
Sentence 1: Internal structure of SALSA The SALSA design tool allows application designers to specify mission/application logic, and the contract governing interactions among participating organizations.
Sentence 2: the designer can specify the follows: - workflow domains that may represent organizations - task specifications (e.g., inputs, outputs, invocation method for the underlying component) in each workflow domain, and - control logic and data flow among tasks.
Relationship: entailment
Domain: Security and privacy
Sentence 1: We start our simulation of the IND-CPA game by running a regular instance of DistKG(1., t, e), except that for server T£ we cheat without A noticing, and this results in a sim­ulation that provides g a as Tl s contribution to the jointly computed public key pk.
Sentence 2: for party T£ we choose t R values slj .
Relationship: entailment
Domain: Security and privacy
Sentence 1: It is important to observe that we do not allow key-dependent queries to the decryption oracle.
Sentence 2: note that if we allowed such queries then one could query the decryp­tion oracle with the function g(s)= Encs(s)and obtain s (this is possible even if one restricts the functions in Cto be deterministic, as we could de.ne the function g(s)to be the encryption of s with the random coins set to a .xed string, say all zeros).
Relationship: entailment
Domain: Security and privacy
Sentence 1: Unlike previous measurements and analy­ses [35, 23], we measure a large number of disjoint incom­ing/outgoing routes to/from a bottleneck link.
Sentence 2: we gather all visible links 1-hop before/after the bot­tleneck link, and this additional information helps us infer the link types at AS boundary without much ambiguity.3 Fig.
Relationship: entailment
Domain: Security and privacy
Sentence 1: Clearly, unlike a wireline medium, the wireless physical channel cannot be abstracted using simple per-link parameters.
Sentence 2: from a network­ing standpoint, there is a need to model wireless  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 profit or commercial advantage and that copies bear this notice and the full citation on the first page.
Relationship: entailment
Domain: Security and privacy
Sentence 1: More precisely, we in­cluded the top 1000 most popular websites published by Alexa[2], over20,000pro.les of theMySpace[4] social net­work, and the results of ad-hoc queries on popular search engines.
Sentence 2: we queried Google and Yahoo with various combinations of terms such as porn, free down­load, warez, online game, ringtones, and torrents.
Relationship: entailment
Domain: Security and privacy
Sentence 1: 3.3.3 The Meta-policy Speci.cation (ACC) The rules in ACC, that de.ne the predicate access/4,are policy rules about policies (i.e., meta-policy rules).
Sentence 2: di.erent access policies can be expressed as holding with respect to any number of factors e.g., di.erent ob jects, priv­ ileges, status levels, con.ict resolution strategies, system­situated factors, and times.
Relationship: entailment
Domain: Security and privacy
Sentence 1: First, he formalizes a fragment of UML in which only a simpli.ed version of sequence diagrams of UML 1.5 is included.
Sentence 2: while his work is based on formalized parts of UML that we do not consider, our work is based on STAIRS which provides a more in depth formal­ization of UML 2.0 interactions than what is considered in J¨urjens work.
Relationship: entailment