Remote Attestation with Software Updates in Embedded Systems

This paper presents RASUES, a remote-attestation-based scheme designed to incorporate software updates in embedded systems. Our approach has two primary aims: to extend remote attestation specifications to account for software updates, and to leverage Remote Attestation (RA) to validate the integrity of the update process itself. We extend the RATS RFC 9334 specification with an update procedure that accounts for the expected state before and after the update. We demonstrate the feasibility of our design by implementing the main functionality of RASUES on a TPM-based hardware platform. We evaluate the latency of our prototype and analyze its security properties, showing that the approach has acceptable overhead and can provide added security under the stated assumptions.

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Publication Details

Published
2024-09-30
DOI
https://doi.org/10.1109/cns62487.2024.10735526
Citations
4
Primary Topic
Advanced Malware Detection Techniques
Type
article
Field-Weighted Citation Impact
1.40
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article

Remote Attestation with Software Updates in Embedded Systems

Mikael Asplund, Ahmad B. Usman
4 citations
Advanced Malware Detection Techniques
1.40
article

Remote Attestation with Software Updates in Embedded Systems

Mikael Asplund, Ahmad B. Usman
article en
4 citations

Abstract

This paper presents RASUES, a remote-attestation-based scheme designed to incorporate software updates in embedded systems. Our approach has two primary aims: to extend remote attestation specifications to account for software updates, and to leverage Remote Attestation (RA) to validate the integrity of the update process itself. We extend the RATS RFC 9334 specification with an update procedure that accounts for the expected state before and after the update. We demonstrate the feasibility of our design by implementing the main functionality of RASUES on a TPM-based hardware platform. We evaluate the latency of our prototype and analyze its security properties, showing that the approach has acceptable overhead and can provide added security under the stated assumptions.

Linköping University (SE)
Openalex Percentile: Top 18%
Advanced Malware Detection Techniques
1.40
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