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Towards Efficient Control-Flow Attestation with Software-Assisted Multi-level Execution Tracing

Authors: Dimitris Papamartzivanos; Sofia Anna menesidou; Panagiotis Gouvas; Thanassis Giannetsos;

Towards Efficient Control-Flow Attestation with Software-Assisted Multi-level Execution Tracing

Abstract

In the face of an increasing attack landscape, it is necessary to cater for efficient mechanisms to verify software and device integrity for detecting run-time modifications in nextgeneration systems-of-systems. In this context, remote attestation is a promising defense mechanism that allows a third party, the verifier, to ensure a remote device’s configuration integrity and behavioural execution correctness. However, most of the existing families of attestation solutions suffer from the lack of softwarebased mechanisms for the efficient extraction of rigid control-flow information. This limits their applicability to only those cyberphysical systems equipped with additional hardware support. This paper proposes a multi-level execution tracing framework capitalizing on recent software features, namely the extended Berkeley Packet Filter and Intel Processor Trace technologies, that can efficiently capture the entire platform configuration and control-flow stacks, thus, enabling wide attestation coverage capabilities that can be applied on both resource-constrained devices and cloud services. Our goal is to enhance run-time software integrity and trustworthiness with a scalable tracing solution eliminating the need for federated infrastructure trust.

Keywords

Tracing, Remote Attestation, Extended Berkeley Packet Filter, Intel Processor Trace, Control-flow Integrity

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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
1
Average
Average
Average
Green