ACM Transactions on

Privacy and Security (TOPS)

Latest Articles

Hybrid Private Record Linkage: Separating Differentially Private Synopses from Matching Records

Private record linkage protocols allow multiple parties to exchange matching records, which refer to the same entities or have similar values, while keeping the non-matching ones secret. Conventional protocols are based on computationally expensive cryptographic primitives and therefore do not scale. To address these scalability issues, hybrid... (more)

A General Framework for Adversarial Examples with Objectives

Images perturbed subtly to be misclassified by neural networks, called adversarial examples, have emerged as a technically deep challenge and an... (more)

Database Audit Workload Prioritization via Game Theory

The quantity of personal data that is collected, stored, and subsequently processed continues to grow rapidly. Given its sensitivity, ensuring privacy... (more)

GPLADD: Quantifying Trust in Government and Commercial Systems A Game-Theoretic Approach

Trust in a microelectronics-based system can be characterized as the level of confidence that a system is free of subversive alterations made during system development, or that the development process of a system has not been manipulated by a malicious adversary. Trust in systems has become an... (more)

DADS: Decentralized Attestation for Device Swarms

We present a novel scheme called Decentralized Attestation for Device Swarms (DADS), which is, to the best of our knowledge, the first to accomplish decentralized attestation in device swarms. Device swarms are smart, mobile, and interconnected devices that operate in large numbers and are likely to be part of emerging applications in... (more)


About TOPS

ACM TOPS publishes high-quality research results in the fields of information and system security and privacy.  Studies addressing all aspects of these fields are welcomed, ranging from technologies, to systems and applications, to the crafting of policies.

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Forthcoming Articles
Resilient Privacy Protection for Location-based Services through Decentralization

Location-based Services (LBSs) provide valuable services, with convenient features for mobile users. However, the location and other information disclosed through each query to the LBS erodes user privacy. This is a concern especially because LBS providers can be honest-but-curious, collecting queries and tracking users whereabouts and infer sensitive user data. This motivated both centralized and decentralized location privacy protection schemes for LBSs: anonymizing and obfuscating LBS queries to not disclose exact information, while still getting useful responses. Decentralized schemes overcome disadvantages of centralized schemes, eliminating anonymizers, and enhancing users control over sensitive information. However, an insecure decentralized system could create serious risks beyond private information leakage. More so, attacking an improperly designed decentralized LBS privacy protection scheme could be an effective and low-cost step to breach user privacy. We address exactly this problem, by proposing security enhancements for mobile data sharing systems. We protect user privacy while preserving accountability of user activities, leveraging pseudonymous authentication with mainstream cryptography. We show our scheme can be deployed with off-the-shelf devices with an experimental result on automotive testbed.

Analytical Models for the Scalability of Dynamic Group-Key Agreement Protocols and Secure File Sharing Systems

Dynamic group key agreement protocols are cryptographic primitives to provide secure group communications in decentralized and dynamic networks. Such protocols provide additional operations to update the group key while adding new participants into the group and removing existing participants from the group without re-executing the protocol from the beginning. However, the lack of scalability emerges as one of the most significant issues of dynamic group key agreement protocols when the number of participants in the group increases. For instance, frequent participant join requests for large groups may cause an effect similar to a Distributed Denial of Service (DDoS) attack and violate the system availability due to the increase in group key update time. Therefore, analyzing the scalability of dynamic group key agreement protocols is crucial to detect conditions where the system becomes unavailable. In this paper, we propose an analytical performance model to evaluate the scalability of dynamic group key agreement protocols by using queueing models. We also extend our performance model for evaluating the scalability of secure file sharing systems that utilize group key agreement protocols. Moreover, we present a demonstrative use case to show the applicability of our performance model on an example group key agreement protocol and a secure file sharing system.

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