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TSA: a tool to detect and quantify network side-channels

Published: 09 November 2022 Publication History
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  • Abstract

    Mobile applications, Internet of Things devices and web services are pervasive and they all encrypt the communications between servers and clients to not have information leakages. While the network traffic is encrypted, packet sizes and timings are still visible to an eavesdropper and these properties can leak information and sacrifice user privacy. We present TSA, a black box network side-channel analysis tool which detects and quantifies side-channel information leakages. TSA provides the users with the means to automate trace gathering by providing a framework in which the users can write mutators for the inputs to the system under analysis. TSA can also take as input traces directly for analysis if the user prefers to gather them separately. TSA is open-source and available as a Python package and a command-line tool. TSA demo, tool and benchmarks are available at https://github.com/kadron/tsa-tool.

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    Giovanni Cherubin, Konstantinos Chatzikokolakis, and Catuscia Palamidessi. 2019. F-BLEAU: Fast Black-box Leakage Estimation. CoRR abs/ 1902.01350 ( 2019 ). arXiv: 1902.01350 http://arxiv.org/abs/ 1902.01350
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    Tom Chothia, Yusuke Kawamoto, and Chris Novakovic. 2013. A Tool for Estimating Information Leakage. In Computer Aided Verification-25th International Conference, CAV 2013, Saint Petersburg, Russia, July 13-19, 2013. Proceedings (Lecture Notes in Computer Science, Vol. 8044 ), Natasha Sharygina and Helmut Veith (Eds.). Springer, 690-695. https://doi.org/10.1007/978-3-642-39799-8_47
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    Ismet Burak Kadron, Nicolás Rosner, and Tevfik Bultan. 2020. Feedback-Driven Side-Channel Analysis for Networked Applications. In Proceedings of the 29th ACM SIGSOFT International Symposium on Software Testing and Analysis.
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    Nicolás Rosner, Ismet Burak Kadron, Lucas Bang, and Tevfik Bultan. 2019. Profit: Detecting and Quantifying Side Channels in Networked Applications. In 26th Network and Distributed System Security Symposium, NDSS 2019, San Diego, California, USA, February 24-27, 2019.
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    Cited By

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    • (2024)Compositional Verification of First-Order Masking Countermeasures against Power Side-Channel AttacksACM Transactions on Software Engineering and Methodology10.1145/363570733:3(1-38)Online publication date: 14-Mar-2024
    • (2023)Fuzzing, Symbolic Execution, and Expert Guidance for Better TestingIEEE Software10.1109/MS.2023.323798141:1(98-104)Online publication date: 18-Jan-2023

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    cover image ACM Conferences
    ESEC/FSE 2022: Proceedings of the 30th ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering
    November 2022
    1822 pages
    ISBN:9781450394130
    DOI:10.1145/3540250
    This work is licensed under a Creative Commons Attribution 4.0 International License.

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    New York, NY, United States

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    Published: 09 November 2022

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    Author Tags

    1. Network traffic analysis
    2. Security and privacy
    3. Side-channel analysis
    4. Software testing

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    • (2024)Compositional Verification of First-Order Masking Countermeasures against Power Side-Channel AttacksACM Transactions on Software Engineering and Methodology10.1145/363570733:3(1-38)Online publication date: 14-Mar-2024
    • (2023)Fuzzing, Symbolic Execution, and Expert Guidance for Better TestingIEEE Software10.1109/MS.2023.323798141:1(98-104)Online publication date: 18-Jan-2023

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