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DISARM: Target Electronic Device Informed Mitigation of Software Runtime Side-Channel Vulnerabilities

arXiv Security Archived Jun 19, 2026 ✓ Full text saved

arXiv:2606.19807v1 Announce Type: new Abstract: Program runtime or timing attacks exploit variations in a program's execution times to extract sensitive information from the program (e.g. encryption keys, sensitive variable data, intellectual property). State-of-the-art solutions to runtime side-channel attacks attempt to balance the execution time of the sensitive code for different control flow paths to eliminate the timing leakage. However, during the mitigation process, most techniques do no

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    Computer Science > Cryptography and Security [Submitted on 18 Jun 2026] DISARM: Target Electronic Device Informed Mitigation of Software Runtime Side-Channel Vulnerabilities Tasneem Suha, Tanzim Mahfuz, Rima Asmar Awad, Prabuddha Chakraborty Program runtime or timing attacks exploit variations in a program's execution times to extract sensitive information from the program (e.g. encryption keys, sensitive variable data, intellectual property). State-of-the-art solutions to runtime side-channel attacks attempt to balance the execution time of the sensitive code for different control flow paths to eliminate the timing leakage. However, during the mitigation process, most techniques do not consider the underlying hardware or device on which the target program is supposed to run on. This can lead to over-fixing (unnecessary extra operations), under-fixing (not solving the imbalance properly), and even failures. We propose DISARM, a joint hardware-software methodology (unlike any existing solution) for mitigating runtime side-channel vulnerabilities that utilizes timing values from real embedded devices to generate targeted software fixes. We implement DISARM to support C, C++, and Java source codes and validate it across 22 standard benchmarks. DISARM outperforms state-of-the-art solutions such as PENDULUM and DifFuzzAR in terms of execution time overhead, code size overhead, and correctness on five different embedded or edge devices. Subjects: Cryptography and Security (cs.CR) Cite as: arXiv:2606.19807 [cs.CR]   (or arXiv:2606.19807v1 [cs.CR] for this version)   https://doi.org/10.48550/arXiv.2606.19807 Focus to learn more Submission history From: Tasneem Suha [view email] [v1] Thu, 18 Jun 2026 05:22:38 UTC (6,890 KB) Access Paper: HTML (experimental) view license Current browse context: cs.CR < prev   |   next > new | recent | 2026-06 Change to browse by: cs References & Citations NASA ADS Google Scholar Semantic Scholar Export BibTeX Citation Bookmark Bibliographic Tools Bibliographic and Citation Tools Bibliographic Explorer Toggle Bibliographic Explorer (What is the Explorer?) Connected Papers Toggle Connected Papers (What is Connected Papers?) Litmaps Toggle Litmaps (What is Litmaps?) scite.ai Toggle scite Smart Citations (What are Smart Citations?) Code, Data, Media Demos Related Papers About arXivLabs Which authors of this paper are endorsers? | Disable MathJax (What is MathJax?)
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    arXiv Security
    Category
    ◬ AI & Machine Learning
    Published
    Jun 19, 2026
    Archived
    Jun 19, 2026
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