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共 557 条记录，以下是181-190 订阅

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Developing A Compelling Vision for Winning the Cybersecurity Arms Race 20

Developing A Compelling Vision for Winning the Cybersecurity...

引用

10th acm conference on data and application security and privacy (CODASPY)

作者： Bertino, Elisa Singhal, Anoop Srinivasagopalan, Srivathsan Verma, Rakesh Purdue Univ W Lafayette IN 47907 USA NIST Gaithersburg MD 20899 USA AT&T Cybersecur Austin TX USA Univ Houston Houston TX USA

ISBN: (纸本)9781450371070

In cybersecurity there is a continuous arms race between the attackers and the defenders. In this panel, we investigate three key questions regarding this arms race. First question is whether this arms race is winnable. Second, if the answer to the first question is in the affirmative, what steps we need to take to win this race. Third, if the answer to the first question is negative, what is the justification for this and what steps can we take to improve the state of affairs and increase the bar for the attackers significantly.

关键词： Attacker attacks threats security advanced persistent threat data integrity

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CREPE: A privacy-Enhanced Crash Reporting System 20

CREPE: A Privacy-Enhanced Crash Reporting System

引用

10th acm conference on data and application security and privacy (CODASPY)

作者： Satvat, Kiavash Shirvanian, Maliheh Hosseini, Mahshid Saxena, Nitesh Univ Illinois Chicago IL 60680 USA Visa Res Foster City CA USA Univ Alabama Birmingham Birmingham AL USA

ISBN: (纸本)9781450371070

Software crashes are nearly impossible to avoid. The reported crashes often contain useful information assisting developers in finding the root cause of the crash. However, crash reports may carry sensitive and private information about the users and their systems, which may be used by an attacker who has compromised the crash reporting system to violate the user's privacy and security. Besides, a single bug may trigger loads of identical reports which excessively consumes system resources and overwhelms application developers. In this paper, we introduce CREPE, a security-concerned crash reporting solution, that effectively reduces the number of submitted crash reports to mitigate the security and privacy risk associated with the current implementation of the crash reporting system. Similar to the currently deployed systems, CREPE aggregates and categorizes the crashes based on their root cause. On top of that, the server marks the crash categories in which sufficient reports have been received as "saturated" and informs the clients periodically through software updates. On the client, CREPE engages the reporting application in categorizing each crash to only submit reports belonging to non-saturated categories. We evaluate CREPE using one year of data from Mozilla crash reporting system containing 38,834,383 reports of Firefox crashes. Our analysis suggests that we can significantly reduce the number of submitted reports by bucketing 100 most frequent crash signatures at the client. This helps to preserve the security and the privacy of a significant portion of users whose data has not been shared with the server due to the redundancy of their crash data with previously submitted reports.

关键词： Crash Reporting Crash Report privacy Crash Report security Browser privacy

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AuthPDB: Authentication of Probabilistic Queries on Outsourced Uncertain data 20

AuthPDB: Authentication of Probabilistic Queries on Outsourc...

引用

10th acm conference on data and application security and privacy (CODASPY)

作者： Zhang, Bo Dong, Boxiang Sun, Haipei Wang, Wendy Hui Stevens Inst Technol Hoboken NJ 07030 USA Montclair State Univ Montclair NJ USA

ISBN: (纸本)9781450371070

Query processing over uncertain data has gained much attention recently. Due to the high computational complexity of query evaluation on uncertain data, the data owner can outsource her data to a server that provides query evaluation as a service. However, a dishonest server may return cheap (and incorrect) query answers, hoping that the client who has weak computational power cannot catch the incorrect results. To address the integrity issue, in this paper, we design AuthPDB, a framework that supports efficient authentication of query evaluation for both all-answer and top-k queries on outsourced probabilistic databases. Our empirical results on real-world datasets demonstrate the effectiveness and efficiency of AuthPDB.

关键词： data security data outsourcing integrity verification probabilistic database

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IoT Expunge: Implementing Verifiable Retention of IoT data 20

IoT Expunge: Implementing Verifiable Retention of IoT Data

引用

10th acm conference on data and application security and privacy (CODASPY)

作者： Panwar, Nisha Sharma, Shantanu Gupta, Peeyush Ghosh, Dhrubajyoti Mehrotra, Sharad Venkatasubramanian, Nalini Augusta Univ Augusta GA 30912 USA Univ Calif Irvine Irvine CA 92717 USA

ISBN: (纸本)9781450371070

The growing deployment of Internet of Things (IoT) systems aims to ease the daily life of end-users by providing several value-added services. However, IoT systems may capture and store sensitive, personal data about individuals in the cloud, thereby jeopardizing user-privacy. Emerging legislation, such as California's CalOPPA and GDPR in Europe, support strong privacy laws to protect an individual's data in the cloud. One such law relates to strict enforcement of data retention policies. This paper proposes a framework, entitled IoT Expunge that allows sensor data providers to store the data in cloud platforms that will ensure enforcement of retention policies. Additionally, the cloud provider produces verifiable proofs of its adherence to the retention policies. Experimental results on a real-world smart building testbed show that IoT Expunge imposes minimal overheads to the user to verify the data against data retention policies.

关键词： Internet of Things smart building user privacy data deletion verification

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Session details: Session 6 Hardware and Device security/privacy 21

Session details: Session 6 Hardware and Device Security/Priv...

引用

proceedings of the Eleventh acm conference on data and application security and privacy

作者： Ziming Zhao University at Buffalo

No abstract available.

ISBN: (纸本)9781450381437

No abstract available.

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GAN-Leaks: A Taxonomy of Membership Inference Attacks against Generative Models 20

GAN-Leaks: A Taxonomy of Membership Inference Attacks agains...

引用

acm SIGSAC conference on Computer and Communications security (acm CCS)

作者： Chen, Dingfan Yu, Ning Zhang, Yang Fritz, Mario CISPA Helmholtz Ctr Informat Secur Saarbrucken Germany Univ Maryland College Pk MD 20742 USA Max Planck Inst Informat Saarbrucken Germany

ISBN: (纸本)9781450370899

Deep learning has achieved overwhelming success, spanning from discriminative models to generative models. In particular, deep generative models have facilitated a new level of performance in a myriad of areas, ranging from media manipulation to sanitized dataset generation. Despite the great success, the potential risks of privacy breach caused by generative models have not been analyzed systematically. In this paper, we focus on membership inference attack against deep generative models that reveals information about the training data used for victim models. Specifically, we present the first taxonomy of membership inference attacks, encompassing not only existing attacks but also our novel ones. In addition, we propose the first generic attack model that can be instantiated in a large range of settings and is applicable to various kinds of deep generative models. Moreover, we provide a theoretically grounded attack calibration technique, which consistently boosts the attack performance in all cases, across different attack settings, data modalities, and training configurations. We complement the systematic analysis of attack performance by a comprehensive experimental study, that investigates the effectiveness of various attacks w.r.t. model type and training configurations, over three diverse application scenarios (i.e., images, medical data, and location data).

关键词： Membership inference attacks deep learning generative models privacy-preserving machine learning

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A Baseline for Attribute Disclosure Risk in Synthetic data 20

A Baseline for Attribute Disclosure Risk in Synthetic Data

引用

10th acm conference on data and application security and privacy (CODASPY)

作者： Hittmeir, Markus Mayer, Rudolf Ekelhart, Andreas SBA Res Vienna Austria

ISBN: (纸本)9781450371070

The generation of synthetic data is widely considered as viable method for alleviating privacy concerns and for reducing identification and attribute disclosure risk in micro-data. The records in a synthetic dataset are artificially created and thus do not directly relate to individuals in the original data in terms of a 1-to-1 correspondence. As a result, inferences about said individuals appear to be infeasible and, simultaneously, the utility of the data may be kept at a high level. In this paper, we challenge this belief by interpreting the standard attacker model for attribute disclosure as classification problem. We show how disclosure risk measures presented in recent publications may be compared to or even be reformulated as machine learning classification models. Our overall goal is to empirically analyze attribute disclosure risk in synthetic data and to discuss its close relationship to data utility. Moreover, we improve the baseline for attribute disclosure risk from the attacker's perspective by applying variants of the RadiusNearestNeighbor and the EnsembleVote classifiers.

关键词： privacy-Preserving data Mining Synthetic data Machine Learning

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Session details: Session 3: privacy 21

Session details: Session 3: Privacy

引用

proceedings of the Eleventh acm conference on data and application security and privacy

作者： Maribel Fernandez King's College London

No abstract available.

ISBN: (纸本)9781450381437

No abstract available.

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Renyi Differentially Private ADMM for Non-Smooth Regularized Optimization 20

Renyi Differentially Private ADMM for Non-Smooth Regularized...

引用

10th acm conference on data and application security and privacy (CODASPY)

作者： Chen, Chen Lee, Jaewoo Univ Georgia Athens GA 30602 USA

ISBN: (纸本)9781450371070

In this paper we consider the problem of minimizing composite objective functions consisting of a convex differentiable loss function plus a non-smooth regularization term, such as L-1 norm or nuclear norm, under Renyi differential privacy (RDP). To solve the problem, we propose two stochastic alternating direction method of multipliers (ADMM) algorithms: ssADMM based on gradient perturbation and mpADMM based on output perturbation. Both algorithms decompose the original problem into sub-problems that have closed-form solutions. The first algorithm, ssADMM, applies the recent privacy amplification result for RDP to reduce the amount of noise to add. The second algorithm, mpADMM, numerically computes the sensitivity of ADMM variable updates and releases the updated parameter vector at the end of each epoch. We compare the performance of our algorithms with several baseline algorithms on both real and simulated datasets. Experimental results show that, in high privacy regimes (small.), ssADMM and mpADMM outperform baseline algorithms in terms of classification and feature selection performance, respectively.

关键词： differential privacy convex optimization ADMM regularization

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Post-Quantum TLS Without Handshake Signatures 20

Post-Quantum TLS Without Handshake Signatures

引用

acm SIGSAC conference on Computer and Communications security (acm CCS)

作者： Schwabe, Peter Stebila, Douglas Wiggers, Thom Max Planck Inst Secur & Privacy Bochum Germany Radboud Univ Nijmegen Nijmegen Netherlands Univ Waterloo Waterloo ON Canada

ISBN: (纸本)9781450370899

We present KEMTLS, an alternative to the TLS 1.3 handshake that uses key-encapsulation mechanisms (KEMs) instead of signatures for server authentication. Among existing post-quantum candidates, signature schemes generally have larger public key/signature sizes compared to the public key/ciphertext sizes of KEMs: by using an IND-CCA-secure KEM for server authentication in post-quantum TLS, we obtain multiple benefits. A size-optimized post-quantum instantiation of KEMTLS requires less than half the bandwidth of a size-optimized post-quantum instantiation of TLS 1.3. In a speed-optimized instantiation, KEMTLS reduces the amount of server CPU cycles by almost 90% compared to TLS 1.3, while at the same time reducing communication size, reducing the time until the client can start sending encrypted application data, and eliminating code for signatures from the server's trusted code base.

关键词： Post-quantum cryptography key-encapsulation mechanisms Transport Layer security NIST PQC

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