HistoTrust: Ethereum-Based Attestation of a Data History Built with OP-TEE and TPM

Paulin, Dylan; Hennebert, Christine; Franco-Rondisson, Thibault; Jayles, Romain; Loubier, Thomas; Collado, Raphaël

doi:10.1007/978-3-031-08147-7_9

Cited by 2 publications

(5 citation statements)

References 16 publications

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“…Compared to a centralized solution based on digital certificates and PKI, the Ethereum-based solution offers a more refined management of security and privacy at the expense of performance. In [2], HistoTrust demonstrates that performance can meet the needs of a real-time usage when using a blockchain.…”

Section: Secure Data History With Trusted Hardwarementioning

confidence: 99%

“…In fact, the use of secure hardware components, as TPM and TEE, adds an overhead on the computing time to generate the attestation. The paper [2] presents a detailed study of the performance of HistoTrust according to the security level of the private key sk. On the one hand, on the blockchain side, a huge latency may be observed due to the time interval between two consecutive blocks.…”

Section: Attestation Of the Data Producedmentioning

confidence: 99%

“…When the production process involves AIs, implementing the means to trace events and audit the digital system is a requirement. The solution HistoTrust [2] aims to provide such a tool to ensure the protection of embedded AIs against malicious intentions and to enable the explainability of the AIs behavior. HistoTrust combines the probabilistic trust provided by AI with the deterministic trust provided by the blockchain.…”

Section: Introductionmentioning

confidence: 99%

“…HistoTrust has several objectives: (1) to protect the embedded NN from logical and physical attacks by ensuring the cyber robustness of the AI, (2) to protect the data produced by the embedded applications and processed by the NN in order to allow the explainability of the AI behavior, (3) to attest and trace the data produced in a blockchain in order to provide authentic non-repudiable attestations shared between the different stakeholders.…”

Section: Introductionmentioning

confidence: 99%

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HistoTrust: tracing AI behavior with secure hardware and blockchain technology

et al. 2023

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In areas of activity where the notion of accountability is strong, the adoption of artificial intelligence (AI) is limited by the opacity and lack of understanding of its behavior, all the more so in the embedded domain where neural networks are compressed and executed on microcontrollers. While the NIST introduced in 2021 several principles allowing the AI explainability, this paper introduces a novel scheme, HistoTrust, combining secure hardware and blockchain technology to bring trust in the traceability of AI behavior and allow its explainability. HistoTrust attests in an Ethereum ledger all the relevant data produced by a physical device, especially the heuristics inferred by AI. Thus, the audition of the ledger allows security verifications and AI behavior analysis.

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Section: Secure Data History With Trusted Hardwarementioning

confidence: 99%

Section: Attestation Of the Data Producedmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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HistoTrust: tracing AI behavior with secure hardware and blockchain technology

et al. 2023

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“…Works combining these two technologies are not very abundant, although some cases can be found. This is the case of [42], which introduces a design of an IoT node that incorporates ARM TrustZone for attestation; in addition, attested data are secured storage in a TPM. In the proposal [43], a secure logging system from end-to-end between embedded constraint devices and a remote database is implemented, and the architecture design combines a TEE with a TPM.…”

Section: Related Workmentioning

confidence: 99%

Secure Sensor Prototype Using Hardware Security Modules and Trusted Execution Environments in a Blockchain Application: Wine Logistic Use Case

et al. 2023

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The security of Industrial Internet of Things (IIoT) systems is a challenge that needs to be addressed immediately, as the increasing use of new communication paradigms and the abundant use of sensors opens up new opportunities to compromise these types of systems. In this sense, technologies such as Trusted Execution Environments (TEEs) and Hardware Security Modules (HSMs) become crucial for adding new layers of security to IIoT systems, especially to edge nodes that incorporate sensors and perform continuous measurements. These technologies, coupled with new communication paradigms such as Blockchain, offer a high reliability, robustness and good interoperability between them. This paper proposes the design of a secure sensor incorporating the above mentioned technologies—HSMs and a TEE—in a hardware device based on a dual-core architecture. Through this combination of technologies, one of the cores collects the data extracted by the sensors and implements the security mechanisms to guarantee the integrity of these data, while the remaining core is responsible for sending these data through the appropriate communication protocol. This proposed approach fits into the Blockchain networks, which act as an Oracle. Finally, to illustrate the application of this concept, a use case applied to wine logistics is described, where this secure sensor is integrated into a Blockchain that collects data from the storage and transport of barrels, and a performance evaluation of the implemented prototype is provided.

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HistoTrust: Ethereum-Based Attestation of a Data History Built with OP-TEE and TPM

Cited by 2 publications

References 16 publications

HistoTrust: tracing AI behavior with secure hardware and blockchain technology

HistoTrust: tracing AI behavior with secure hardware and blockchain technology

Secure Sensor Prototype Using Hardware Security Modules and Trusted Execution Environments in a Blockchain Application: Wine Logistic Use Case

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