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ACM Transactions on Privacy and Security is a peer-reviewed journal published by ACM, covering Advanced Malware Detection Techniques, Network Security and Intrusion Detection, Privacy-Preserving Technologies in Data. Over its lifetime it has published 350 papers, which have received 5,738 citations.
| Publisher | ACM |
|---|---|
| Reference style | Numbered (ACM) Numbered — [1], [2] in the text [1] Ada Smith, Ben Jones, and Cara Lee. 2023. A representative article title. ACM Transactions on Privacy and Security 12, 3, Article 45 (2023).
Formats any DOI in ACM Transactions on Privacy and Security style. No sign-up. |
| Publishes research in | Advanced Malware Detection Techniques Network Security and Intrusion Detection Privacy-Preserving Technologies in Data Cryptography and Data Security Security and Verification in Computing |
| ISSN | 2471-2566 |
| Citation impact (2-yr) | 3.38 |
| h-index | 38 |
| i10-index | 154 |
| Top institutions publishing here | Purdue University West Lafayette |
| Journal website | tops.acm.org |
| You get | A submission-ready PDF and the editable LaTeX source — ready to submit. |
Citations each year’s papers have accumulated so far — the most recent years are still building up.
As Android has become increasingly popular, so has malware targeting it, thus motivating the research community to propose different detection techniques. However, the constant evolution of the Android ecosystem, and of malware itself, makes it hard to design robust tools that can operate for long periods of time without the need for modifications or costly…
Private set intersection (PSI) allows two parties to compute the intersection of their sets without revealing any information about items that are not in the intersection. It is one of the best studied applications of secure computation and many PSI protocols have been proposed. However, the variety of existing PSI protocols makes it difficult to…
Images perturbed subtly to be misclassified by neural networks, called adversarial examples , have emerged as a technically deep challenge and an important concern for several application domains. Most research on adversarial examples takes as its only constraint that the perturbed images are similar to the originals. However, real-world application of these ideas often requires…
We present a new approach to static analysis for security vetting of Android apps and a general framework called Amandroid. Amandroid determines points-to information for all objects in an Android app component in a flow and context-sensitive (user-configurable) way and performs data flow and data dependence analysis for the component. Amandroid also tracks inter-component communication…
We propose new privacy attacks to infer attributes (e.g., locations, occupations, and interests) of online social network users. Our attacks leverage seemingly innocent user information that is publicly available in online social networks to infer missing attributes of targeted users. Given the increasing availability of (seemingly innocent) user information online, our results have serious implications…
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