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A Digital Forensic Methodology for Encryption Key Recovery from Black-Box IoT Devices
Congratulations to Muhammad Rusyaidi Zunaidi and co-authors Asanka Sayakkara, and Mark Scanlon on the publication of A Digital Forensic Methodology for Encryption Key Recovery from Black-Box IoT Devices in Proceedings of the 12th International Symposium on Digital Forensics and Security.
Co-authors: Asanka Sayakkara, and Mark Scanlon.
AI-generated summary of the contribution: This paper introduces a novel digital forensic methodology for recovering encryption keys from black-box IoT devices using electromagnetic side-channel analysis (EM-SCA). The proposed approach leverages machine learning techniques to enhance the digital forensic process, reducing the key space necessary for brute-force decryption and mitigating investigative roadblocks. This automated, adaptable system preserves the integrity of forensic evidence and ensures wide applicability within the evolving IoT landscape. The methodology is designed to be efficient, accurate, and non-invasive, making it a valuable tool for investigators facing the complexities of encrypted device analysis. By leveraging EM-SCA, the proposed approach can recover encryption keys from black-box IoT devices, providing a significant breakthrough in digital forensic investigations. The methodology is tailored to adapt to the diverse range of IoT device architectures, ensuring broad applicability and efficiency in processing and accuracy in key extraction. The design incorporates cross-device portability, drawing insights from studies that have demonstrated the potential of EM-SCA in gathering forensically useful insights from IoT devices.