Approaches to Quantum Remote Memory Attestation

ABSTRACT In this article, we uncover flaws and pitfalls of a quantum‐based remote memory attestation procedure for Internet of things devices. We also show limitations of quantum memory that suggests the attestation problem for quantum memory is fundamentally different to the attestation problem for classical memory, even when the devices can perform quantum computation. The identified problems are of interest for quantum‐based security protocol designers in general, particularly those dealing with corrupt devices. Finally, we make use of the lessons learnt to design a quantum‐based attestation system for classical memory with improved communication efficiency and security.

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Publication Details

Journal
IET Quantum Communication
Published
2025-01-01
DOI
https://doi.org/10.1049/qtc2.70019
Citations
1
Primary Topic
Advanced Memory and Neural Computing
Type
article
Field-Weighted Citation Impact
0.73
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article

Approaches to Quantum Remote Memory Attestation

Rolando Trujillo-Rasúa, Jesse Laeuchli
1 citations
IET Quantum Communication
Advanced Memory and Neural Computing
0.73
article

Approaches to Quantum Remote Memory Attestation

Rolando Trujillo-Rasúa, Jesse Laeuchli
article en
1 citations

Abstract

ABSTRACT In this article, we uncover flaws and pitfalls of a quantum‐based remote memory attestation procedure for Internet of things devices. We also show limitations of quantum memory that suggests the attestation problem for quantum memory is fundamentally different to the attestation problem for classical memory, even when the devices can perform quantum computation. The identified problems are of interest for quantum‐based security protocol designers in general, particularly those dealing with corrupt devices. Finally, we make use of the lessons learnt to design a quantum‐based attestation system for classical memory with improved communication efficiency and security.

IET Quantum CommunicationVol. 6(1)
UNSW Sydney (AU), Universitat Rovira i Virgili (ES)
Openalex Percentile: Top 23%
Advanced Memory and Neural Computing
0.73
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