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A Lightweight Privacy-Aware Continuous Authentication Protocol-PACA

Published:02 September 2021Publication History
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Abstract

As many vulnerabilities of one-time authentication systems have already been uncovered, there is a growing need and trend to adopt continuous authentication systems. Biometrics provides an excellent means for periodic verification of the authenticated users without breaking the continuity of a session. Nevertheless, as attacks to computing systems increase, biometric systems demand more user information in their operations, yielding privacy issues for users in biometric-based continuous authentication systems. However, the current state-of-the-art privacy technologies are not viable or costly for the continuous authentication systems, which require periodic real-time verification. In this article, we introduce a novel, lightweight, <underline>p</underline>rivacy-<underline>a</underline>ware, and secure <underline>c</underline>ontinuous <underline>a</underline>uthentication protocol called PACA. PACA is initiated through a password-based key exchange (PAKE) mechanism, and it continuously authenticates users based on their biometrics in a privacy-aware manner. Then, we design an actual continuous user authentication system under the proposed protocol. In this concrete system, we utilize a privacy-aware template matching technique and a wearable-assisted keystroke dynamics-based continuous authentication method. This provides privacy guarantees without relying on any trusted third party while allowing the comparison of noisy user inputs (due to biometric data) and yielding an efficient and lightweight protocol. Finally, we implement our system on an Apple smartwatch and perform experiments with real user data to evaluate the accuracy and resource consumption of our concrete system.

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            cover image ACM Transactions on Privacy and Security
            ACM Transactions on Privacy and Security  Volume 24, Issue 4
            November 2021
            295 pages
            ISSN:2471-2566
            EISSN:2471-2574
            DOI:10.1145/3476876
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            Copyright © 2021 ACM

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            New York, NY, United States

            Publication History

            • Published: 2 September 2021
            • Accepted: 1 May 2021
            • Revised: 1 March 2021
            • Received: 1 March 2020
            Published in tops Volume 24, Issue 4

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