sadat2307/MSciNLI huggingface dataset:
Domain: Security and privacy
Sentence 1: Customer-centric Energy Usage Data Management and Sharing in Smart Grid Systems Gaurav Lahoti* University of Illinois at Urbana-Champaign Urbana, IL lahoti2@illinois.edu  ABSTRACT A recent study revealed that .ne-grained energy usage data could potentially leak sensitive information about an elec­tricity customer.
Sentence 2: a number of online service providers utilizing such data have emerged and im­proved e.ectiveness of smart grid technologies (for instance, demand-response aggregators), and therefore sharing of data is getting popular.
Relationship: contrasting
Domain: Security and privacy
Sentence 1: The Repairable File Service assumes an administrator has already iden­ti.ed the process that started the intrusion; it then uses the log to identify .les that potentially have been contaminated by that pro­cess.
Sentence 2: backTracker begins with a process, .le, or .le­name that has been affected by the intrusion, then uses the log to track back to the source of the intrusion.
Relationship: contrasting
Domain: Security and privacy
Sentence 1: With PaX ASLR in place, such exploits must guess the seg­ment o.sets from a search space of either 40 bits (if stack and libc o.sets are guessed concurrently) or 25 bits (if se­quentially).
Sentence 2: our return-to-libc technique uses addresses placed by the target program onto the stack.
Relationship: contrasting
Domain: Security and privacy
Sentence 1: The future of computers is leaning towards: more personalized hardware to match user habits; less distributed systems; more generalized content, more specific cryptology; smart card identification; biological security; more peripherals and accessories; smaller architecture; biometric technology; expanded civic/social uses; and medical potential.
Sentence 2: with visually impaired persons, the greater concern with the technological advances is the lack of security in these devices when accessing the Internet away from home.
Relationship: contrasting
Domain: Security and privacy
Sentence 1: If R0, R1, S, Z, g, and h are not formed correctly, it could potentially mean that the security properties for the TPM/host do not hold.
Sentence 2: it is su.cient if the plat­form/host (i.e., owner of the TPM) veri.es the proof that R0, R1, g, and h are computed correctly once.
Relationship: contrasting
Domain: Security and privacy
Sentence 1: For ex­ample, the messages used to measure the overhead of the SQL server .lter have the .rst byte equal to 0x4 to force the .lter to check if the remaining bytes in the message are di.erent from zero.
Sentence 2: the messages sent to the stunnel .lter have no % characters because the .l­ter stops processing the message bytes when it .nds a valid format speci.er.
Relationship: contrasting
Domain: Security and privacy
Sentence 1: As we can quickly reach from the source proof to the destination proof us­ing larger links, we observe better performance with increased link  (a) Provenance Generation (b) Sequential Veri.cation (c) Sparse Veri.cation Figure 1: Time Required in Different Operations for Block Hash Chain (a) Provenance Generation (b) Sequential Veri.cation (c) Sparse Veri.cation Figure 2: Time Required in Different Operations for Bloom Filter (a) Provenance Generation (b) Sequential Veri.cation (c) Sparse Veri.cation   Figure 3: Time Required in Different Operations for Multi-link Chain size.
Sentence 2: if the distance between the source and destination Space Requirement: Space requirement does not vary with link proof is less than the link size, we cannot utilize the bene.t of using size for this scheme, as we do not need any extra storage for the multi-link chain.
Relationship: contrasting
Domain: Security and privacy
Sentence 1: For example, ifb is very large, viruses can all 100 1400 1200 1000 800 600 400 200 500 1000 1500 2000 25003000350~  4o0o~  1 3500 I 10 I 3000 I t 1 2500 l I000 I  2000 1500 1000 l t  500 ~ = ~ ....... 500 1000 1500 2000 25'00 y Figure S: Orbits for various predatory rates (upper figure) and predator multiplication rates (lower figures) with other param- eters fixed as (xo,Yo) = (100,1),r = 2. be eliminated rapidly, but at the same time there will be an outbreak of predators, degrading the network.
Sentence 2: a smaller b will allow viruses to dominate the network.
Relationship: contrasting
Domain: Security and privacy
Sentence 1: While for a small initial matrix the brute force approach tends to be quite fast, for larger matrices it becomes increasingly unlikely to .nd a viable parameter vector that actually results in a state transition.
Sentence 2: since no heuristic knowledge about the model is used, there is of course no guarantee that even fre­quent state transitions gain progress towards .nding the desired right leakage, so the overall success of this heuristic is largely ran­dom.
Relationship: contrasting
Domain: Security and privacy
Sentence 1: 4.3 JavaMOP versus AspectJ Aspect Oriented Programming (AOP) is well known for best spec­ifying security concerns, due to its modularity and the its ability to seperate concerns and crosscut them where needed.
Sentence 2: as shown in [28] , using AspectJ becomes a hard task when it is used to specify event-history based speci.cations, or moreover when used to enforce speci.cations on certain objects of classes (parametrized speci.cations).
Relationship: contrasting
Domain: Security and privacy
Sentence 1: This de.nition of logs is very broad and encompasses many data sources such as tcpdump packet capture .les, Snort alert logs, Apache access and er­ror logs, Linux authentication logs, etc.
Sentence 2: it does not cover other log .les such as the Linux kernel log for which the format is more permissive, and Dpkg logs, for which each event can span several lines.
Relationship: contrasting
Domain: Security and privacy
Sentence 1: In par­ticular, if the device has a strong entropy source (the device can repeatedly sample from the uniform distribution over a large set of values), running the protocol never weakens the device s cryptographic keys.
Sentence 2: if the device has a weak or biased entropy source, running the protocol can dramatically strengthen the device s keys by ensuring that its keys incorporate su.cient randomness.
Relationship: contrasting
Domain: Security and privacy
Sentence 1: To demonstrate this weakness, we created a scenario with the following steps: Create file 1 with two encrypted 4-KB blocks, C1 and C2  Create a backup B1  Update C2 with C2  An attacker can take a disk image dump B2 and analyze B1 and B2  We gained access to the original source of AON-ext3cow.
Sentence 2: we were unable to retrofit the environment to conduct our experiments on the actual system.
Relationship: contrasting
Domain: Security and privacy
Sentence 1: However, the IdP can enforce the generation of a new certi.­cate and may automatically import it into the UA.
Sentence 2: this can be achieved on the .y and without any user interaction by using HTML5 in combination with the -Tag.12 since the au­tomated deleting of the generated certi.cates is not possible, this feature should be used carefully regarding the key storage of the browser.
Relationship: contrasting
Domain: Security and privacy
Sentence 1: National opinion polls (off­line and on-line questionnaires) have sought to capture users perceptions to help direct privacy pro­tection advancements.
Sentence 2: the results from these surveys have done little more than identify the importance of computer privacy for users (Harris &#38; Westin, 1998) and have substantiated privacy advocates perceptions of data usage.
Relationship: contrasting
Domain: Security and privacy
Sentence 1: Modeling and veri.cation of systems is essential to ver­ify that a given a CPS satis.es functional correctness and meets the expected criteria.
Sentence 2: two shortcomings ex­ist: 1) representation of the concurrent and distributed in­teractions within a CPS while capturing the discrete 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: contrasting
Domain: Security and privacy
Sentence 1: Gray Risk: from disclosure to patch the software user waits forthe vendorto issue apatch.Wecall the riskexposure aris­ingfrom this periodthe Gray Risk because the public is awareof this riskbut has notyetreceivedremediation from the software vendor/originator.
Sentence 2: through the information in the disclo­sureofthe vulnerability the user can assess his individual risk and mightimplement othersecurity mechanismsuntil apatch is avail­able.
Relationship: contrasting
Domain: Security and privacy
Sentence 1: One notable research e.ort in this direction is Flicker [20], which is a system that uses the late launch capability to run a secure veri.able workload.
Sentence 2: the late launch ca­pability, provided by both Intel [11] and AMD [1], incurs signi.cant overhead (in the magnitude of hundreds of mil­liseconds) on every context switch to the isolated environ­ment.
Relationship: contrasting
Domain: Security and privacy
Sentence 1: [15] utilized a similar Flush-Reload side channel (a special case of our NFA-based framework) in a cross-VM context to break AES keys.
Sentence 2: to the best of our knowledge, memory deduplication across VMs is not commonly used in many IaaS clouds (e.g., EC2), which limits the applicability of the Flush-Reload side-channel attack in those settings.
Relationship: contrasting
Domain: Security and privacy
Sentence 1: China jinli71@gmail.com Duncan S. Wong Department of Computer Science, City University of Hong Kong, Hong Kong duncan@cityu.edu.hk ABSTRACT Attribute-based encryption (ABE) has been widely studied re­cently to support .ne-grained access control of shared data.
Sentence 2: anony­mous ABE, which is a relevant notion to ABE, further hides the receivers attribute information in ciphertexts because many at­tributes are sensitive and related to the identity of eligible user­ s. in existing anonymous ABE work, a user knows whether the attributes and the policy match or not only after re­peating decryption attempts.
Relationship: contrasting
Domain: Security and privacy
Sentence 1: Battista Biggio Università di Cagliari Piazza d Armi 09123, Cagliari, Italy battista.biggio@diee.unica.it Davide Ariu Università di Cagliari Piazza d Armi 09123, Cagliari, Italy  davide.ariu@diee.unica.it Ignazio Pillai Università di Cagliari Piazza d Armi 09123, Cagliari, Italy pillai@diee.unica.it Marcello Pelillo Università Ca Foscari di Venezia Via Torino, 155 30172 Venezia-Mestre pelillo@dais.unive.it Samuel Rota Bulò FBK-irst Via Sommarive, 18 38123, Trento, Italy  rotabulo@fbk.eu Fabio Roli Università di Cagliari Piazza d Armi 09123, Cagliari, Italy  roli@diee.unica.it ABSTRACT Clustering algorithms have been increasingly adopted in se­curity applications to spot dangerous or illicit activities.
Sentence 2: they have not been originally devised to deal with deliberate attack attempts that may aim to subvert the clustering process itself.
Relationship: contrasting
Domain: Security and privacy
Sentence 1: Recall from section2 that once a subject joins the group, authorization information such as subject join time and object add time are available instantaneously to the TRM subject join time is provisioned at the TRM on successful join andobjectaddtimeisavailable via super­distribution.
Sentence 2: subject leave time and object remove time are only available at refresh times from the CC.
Relationship: contrasting
Domain: Security and privacy
Sentence 1: t Thereforeweneedtomodifythemaintehnialpart.The fator(log2e)i2omesfromLemma8usedintheproofof Lemma3(morepreisely,itisusedtoobtain(27)).We willnowproveanalternativeinequality(Lemma6).First, reallthat(intheproofofLemma5)weinfatprovedsome­thingstrongerthanthestatementofthelemma.Namelywe provedproperty(26).
Sentence 2: eMMA6.LetS1,...,S1beasequeneofrandomvari­ablessuhthatforeveryjwehaveISjI:a(forsome a?0)andP1,, =P-1,,Then,forevery TE[0.5,1), -­ () m 1(H(T)-1)+1 PSj?Tla:2,(35) j=1 whereH(T):=-Tlog2T-(1-T)log2(1-T)isthebinary entropyfuntion ThislemmaisinomparablewithLemma8.Ononehand itisweakersineitappliesonlywhen(26)issatisfedand forT?1i2(also,forTnotmuhgreaterthan1i2itgives aworsebound).forourpurposes(Tloseto1)it isstrongerthanLemma8.
Relationship: contrasting
Domain: Security and privacy
Sentence 1: Figure 1: Artifacts of the WebID Identi.cation Approach: Certi.cate, URI, and Pro.le Command line tools like OpenSSL1 and keytool 2 enable users to create a WebID certi.cate fast and securely.
Sentence 2: these tools are primarily intended for technically experienced computer users that are familiar with using command line interfaces.
Relationship: contrasting
Domain: Security and privacy
Sentence 1: While they have the added developmental complexity of having to deal with writing the SMM handler in legacy 16 bit assembly, they expend little effort to conceal their memory footprint as the chipset handles the memory access redirection once SMRAM has been closed and locked by the handler.
Sentence 2: in order to provide similar stealth, a VMBR will likely have a larger code footprint.
Relationship: contrasting
Domain: Security and privacy
Sentence 1: Moreover, although as discussed above the specific allegations about messages that Moldow edited (to remove profanity and delete offensive statements) reveal conduct that is plainly protected by section 230, the complaint makes general allegations that Moldow participates in the editing of messages; it is possible for an editor to be so closely involved in the creation of content that he becomes liable as an information provider.
Sentence 2: new Jersey law also requires a defamation plaintiff to make very allegations that are sufficiently specific to identify the defamatory words, their utterer, and the facts and circum­stances of their publication; general allegations that a defendant published defamatory matter are simply not sufficient to withstand a motion to dismiss.
Relationship: contrasting
Domain: Security and privacy
Sentence 1: 3.3 Policy Composition and AnomalyAnalysis The access control policies in our model can be uniformly speci.ed both at the EHR-instance level within di.erent origin domains and at the aggregation level within a vir­tual composite EHR.
Sentence 2: bringing in both positive and negative policies raises problems of possible con.icts, and the .exibility in data selection may result in issues of policy overlap.
Relationship: contrasting
Domain: Security and privacy
Sentence 1: In the previous section, 512 entries per hash table (h) with the substring length (k) of 5 and 7 bytes showed the best performance in Table 1: Block Select Memory Con.guration for XC2VP70 Number of Entry (h) 512 1K 2K 4K 8K 16K Single Block Width in bits 36 9 2 18 4 Table 2: Performance Comparison of Pattern Matching Techniques Description Input Device Throughput Logic Cells Bits (Gbps) / Char State Tables[4] 64 Altera 10.1 15 EP20k400E Pre-decoded CAMs [15] 32 Virtex2 6000 9.7 3.56 Granidt [14] 32 VirtexE 1000 2.2 15.2 Parallel Comparators [6] 32 Altera EP20K 2.9 10.6 TBT 32 VirtexII Pro 2.0 terms of the memory consumption and utilization.
Sentence 2: implementing both 5 and 7 bytes wide hash tables requires two memory blocks in parallel, since the single block width of XC2VP70 with 512 entries is 4.5 bytes as shown in Table 1.
Relationship: contrasting
Domain: Security and privacy
Sentence 1: Finally, some schemes [26] require all par­ties to agree on the same public parameters, such as the common discrete log group, which makes any changes to the security pa­rameter or signcryption scheme quite dif.cult.
Sentence 2: we observe that practical signature and en­cryption schemes such as OAEP [4], OAEP+ [25], and PSS-R [5], are built from trapdoor permutations (TDPs) such as RSA, and are analyzed in the random oracle (RO) model.
Relationship: contrasting
Domain: Security and privacy
Sentence 1: Anomaly­based systems are used todetect unknown attacks,but usuallygen­eratefalsepositives[8,42].
Sentence 2: signature-basedsystems are typically moreprecise,but cannot detect attacksfor which theydo 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 madeordistributedforpro.t or commercial advantage and that copies bearthisnoticeand thefull citation onthe .rstpage.Tocopy otherwise,to republish, topost on servers or to redistribute tolists, requiresprior speci.c permissionand/or afee.
Relationship: contrasting
Domain: Security and privacy
Sentence 1: In a related work, [17, 18] use multiple implicit factors (from user context) to determine how to explicitly authenticate a user.
Sentence 2: our work is di.erent from these approaches since in addition to allowing an app devel­oper to selectively invoke an authenticating module based on the type of an app, we delegate IA tasks to an app and not to the device.
Relationship: contrasting
Domain: Security and privacy
Sentence 1: Thus, the process of reproducing identical results, without having access to the datasets, is di.cult to be achieved.
Sentence 2: since the URL sources used in this study rep­resent the browsing patterns of a wide range of users, the chances of having special cases in the dataset is likely to be low, and similar results should be reproduced with other URL datasets if a similar solution is recreated as described in this paper.
Relationship: contrasting
Domain: Security and privacy
Sentence 1: The signal handler overhead experiences the most kernel overhead, with the majority of the extra instructions exe­cuted occurring on the kernel side.Because the signal is de­livered while the application is in a compartment, the kernel must use the longer XOM save routines shown in Figure 2 to save every register.In addition, when the kernel popu­lates the sigcontext structure, the kernel requires more in­structions to copy the larger encrypted register values.The additional instructions and larger data structures also result in an increase in cache misses.
Sentence 2: finally, the xom fork benchmark actually has negative overhead.Fork is already a long operation in IRIX, so the overhead imposed by XOM negligible.The majority of the extra instructions in fork are actually due to the ex­tra xom alloc() system call that is used to allocate a new Register Key Table entry.in this case more favor­able behavior in the L1 cache makes up for the additional instructions and L2 cache misses.
Relationship: contrasting
Domain: Security and privacy
Sentence 1: A naïve approach would be to associate each pseudonym with a randomly generated IP addresses in the network and route based on IP addresses within the ISP.
Sentence 2: this approach requires routers to maintain routing tables that are proportional to the num­ber of actively used pseudonyms, with the random address alloca­tion preventing the use of aggregation of routing table entries.
Relationship: contrasting
Domain: Security and privacy
Sentence 1: Note thatour concrete constructionhas twodi.erentiden­ti.ersforagiven .le: theciphertextfor a .leisstored under a .le pointer that is revealed during the search operation, butthe .leinformationintheindexisstoredin Td under the output of a pseudo-random function on the .le.
Sentence 2: the scheme s operations immediately reveal to an adversary the correlation between these values, so in our leakage de­scription, we do not distinguish between these two types of .le identi.ers.
Relationship: contrasting
Domain: Security and privacy
Sentence 1: For example, Microsofts Royalty-Free Sender ID Patent License Agreement terms were a barrier to any Linux Debian package that wished to implement Sender ID or include Sender ID support [5].
Sentence 2: microsoft changed the licence terms of relevant patents to the Mi­crosoft Open Speci.cation Promise, which is widely seen to be compatible to the GPL [12].
Relationship: contrasting
Domain: Security and privacy
Sentence 1: As such, they can be shown to 3-wise independent but not 4-wise independent, e.g., 1212 1212 z1,1z2,2 =(x )(x )=(x )(x )= z1,2z2,1 .
Sentence 2: 1x12x21x22x1 by exploiting the geometry of the de­pendencies, the next lemma establishes that the elements of z are still su.ciently independent.
Relationship: contrasting
Domain: Security and privacy
Sentence 1: In particular, if the inter-packet delay, in arriving tra.c, is large enough, to allow the receiving host to process each packet before the arrival of a new one, then, even a large burst may not intro­duce signi.cant delays into the tra.c .ow.
Sentence 2: a 2 Notice that since all our communication is within the cloud boundaries, no charges apply on the attacker.
Relationship: contrasting
Domain: Security and privacy
Sentence 1: The scenario comprisestwo parties: Alice,who hasapoint a = i=0 , {ai}N-1 and Bob, who has the description of the region S. Alice wants to check if a .S, without disclosing any knowledge of the coordinates of a to Bob, and without getting any knowledge of the description of S. The clear-text algorithm for solving the posed problem consistsinchecking thepositionof thepointwithrespectto each of the hyperplanes: if a .Sm,.m =1,...,K, which canbe checkedby computing the inner productbetween the point and the normal vector of each plane and adding the corresponding o.sets, then thepoint lies inside S. The time e.ciency of this algorithm can be optimized: once a hyper­plane that leaves thepoint outsideof thebounded regionis found, the algorithm stops without computing the remain­ing scalar products (in such a case, this algorithm is the most e.cient one also for the two-dimensional point inclu­sion problem in convex polygons of small area).
Sentence 2: a direct implementation of this stop-test is notpossible in our scenario, as it would leak too much information about the position of the point w.r.t.
Relationship: contrasting
Domain: Security and privacy
Sentence 1: The most common data anonymization technique is k-anonymity [20], it is also used in location anonymization [10] along with some variants [3], where is known as cloaking: here Charlie is provided with k possible Alice s locations including the true location so that, when there is no further informa­tion available to Charlie, the probability he can associate Alice to a speci.c location is 1/k (Alice s location is said to be k-anonymous).
Sentence 2: as already note in [4] and [9], if Charlie knows that the landscape is not neutral, so that some user locations are more likely than others (e.g.
Relationship: contrasting
Domain: Security and privacy
Sentence 1: SVM treats each data instance (i.e., trip) to be independent and tries to classify it as a user or sybil trip based on the at­tribute values.
Sentence 2: there is an additional restriction in our scenario that states that only one user trip can exist in a set of k trips reported to the LBS at one given time (because k-1 trips are sybil trips).
Relationship: contrasting
Domain: Security and privacy
Sentence 1: An example is given in the following: public class Storage{ public void QueryDatabase(SQLStat query, Token token){ if(!this.checkToken(token)) return; else { /* Do the database query task and return result*/ } } } With the above token mechanism, even if the JavaScript code in the malicious main frame can still access the Query-Database interface, its invocation cannot lead to an actual database query.
Sentence 2: if the call is initiated by the Liv­ingSocial web pages which have the valid token from the child frame, the invocation is legitimate, and will lead to a query.
Relationship: contrasting