Conference proceeding
A Power Side-Channel Attack on Flash ADC
2023 IEEE International Symposium on Circuits and Systems (ISCAS), v 2023-, pp 1-5
21 May 2023
Abstract
In this paper, a monotonic power side-channel attack (PSA) is proposed to analyze the security vulnerabilities of flash analog-to-digital converters (ADC), where the digital output of a flash ADC is determined by characterizing the monotonic relationship between the traces of the power consumed and the applied input signals. A novel technique that leverages clock phase division is proposed to secure the power side channel information of a 4-bit flash ADC. The proposed technique adds randomness to decorrelate the input signal from the given power trace as the execution phase of each comparator depends on a thermometer code computed from the previous seven clock cycles. The monotonic PSA is executed on both a secured and unsecured ADC, with results indicating 1.9 bits of information leakage from an unprotected ADC and no data leakage from a protected ADC as the bit-wise accuracy is approximately 50% when secured. The monotonic PSA is more effective at attacking a flash ADC architecture than either a convolutional neural network based PSA or a correlation template PSA. The secured ADC core occupies approximately 2% more area than a non-secure ADC in a 65 nm process, and provides a sampling frequency of up to 500 MHz at a supply voltage of 1.2 V.
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1 citations in Scopus
Details
- Title
- A Power Side-Channel Attack on Flash ADC
- Creators
- Ziyi Chen - Drexel UniversityIoannis Savidis - Drexel University
- Publication Details
- 2023 IEEE International Symposium on Circuits and Systems (ISCAS), v 2023-, pp 1-5
- Publisher
- IEEE
- Resource Type
- Conference proceeding
- Language
- English
- Academic Unit
- Electrical and Computer Engineering
- Web of Science ID
- WOS:001038214600006
- Scopus ID
- 2-s2.0-85167724496
- Other Identifier
- 991021057566504721
InCites Highlights
Data related to this publication, from InCites Benchmarking & Analytics tool:
- Web of Science research areas
- Computer Science, Artificial Intelligence
- Computer Science, Information Systems
- Engineering, Electrical & Electronic