TEE-Based Evidence Security
Cloud-hosted cybercrime reporting systems increasingly depend on automated analytics to process sensitive digital evidence, creating new challenges for protecting data during computation. Traditional encryption safeguards information at rest and in transit but leaves evidence exposed while it is being processed. This research proposes a privacy-preserving architecture that leverages Confidential Computing and Trusted Execution Environments (TEEs) to secure digital evidence throughout the processing lifecycle. By integrating remote attestation, hardware-isolated execution, and secure key management, the proposed design enhances confidentiality, preserves forensic integrity, and strengthens trust in cloud-based digital evidence processing.
THE CHALLENGE
Cloud-hosted cybercrime reporting systems increasingly process sensitive digital evidence using automated analytics. While encryption protects data at rest and in transit, evidence remains vulnerable during computation, creating risks of memory inspection, privileged insider access, and hypervisor-level attacks. The challenge was to design a secure architecture that protects digital evidence throughout the processing lifecycle without compromising forensic integrity or auditability.
OUR SOLUTION
We proposed a privacy-preserving architecture built on Confidential Computing and Trusted Execution Environments (TEEs). The solution integrates hardware-isolated execution, remote attestation, and attestation-driven key release to ensure that decrypted evidence exists only within trusted execution environments. The architecture also incorporates secure provenance logging and minimal trusted computing boundaries to strengthen confidentiality, maintain chain of custody, and support forensic investigations.
THE RESULTS
The proposed architecture demonstrates how confidential computing can significantly reduce exposure to host-level attacks while preserving forensic integrity and auditability. The research establishes a practical framework for protecting digital evidence during computation and provides a foundation for future implementation, evaluation, and adoption in secure cloud-hosted cybercrime reporting systems.
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