Abstract
While quantum key distribution (QKD) is a theoretically secure way of growing quantum-safe encryption keys, many practical implementations are challenged due to various open attack vectors, resulting in many variations of QKD protocols. Side channels are one such vector that allows a passive or active eavesdropper to obtain QKD information leaked through practical devices. This paper assesses the feasibility and implications of extracting the raw secret key from far-field radiated emissions from the single-photon avalanche diodes used in a BB84 QKD quad-detector receiver. Enhancement of the attack was also demonstrated through the use of deep-learning model to distinguish radiated emissions due to the four polarized encoding states. To evaluate the severity of such side-channel attack, multi-class classification based on raw-data and pre-processed data is implemented and assessed. Results show that classifiers based on both raw-data and pre-processed features can discern variations of the electromagnetic emissions caused by specific orientations of the detectors within the receiver with an accuracy higher than 90%. This research proposes machine learning models as a technique to assess EM information leakage risk of QKD and highlights the feasibility of side-channel attacks in the far-field region, further emphasizing the need to utilise mechanisms to avoid electromagnetic radiation information leaks and measurement-device-independent QKD protocols.
Original language | English |
---|---|
Article number | 78 |
Journal | EPJ Quantum Technology |
Volume | 11 |
DOIs | |
Publication status | Published - 18 Nov 2024 |
Keywords
- Electromagnetic security
- Information leakage
- Quantum communication
- Quantum key distribution
- Side channel attack
- Single-photon avalanche diode
- Single-photon detector
Fingerprint
Dive into the research topics of 'Electromagnetic side-channel attack risk assessment on a practical quantum-key-distribution receiver based on multi-class classification'. Together they form a unique fingerprint.Datasets
-
Radiated-emissions records of the quasi- QKD receiver measure - main spectral component
Pantoja, J. (Creator) & Donaldson, R. J. (Contributor), Heriot-Watt University, 7 May 2024
DOI: 10.17861/3db4374a-d394-42ce-b4ba-3e4612220817
Dataset