Algorithm-Agnostic System for Measuring Susceptibility of Cryptographic Accelerators to Power Side Channel Attacks

Many digital devices, from secure enclaves to generic processors, often handle encryption of sensitive data. Protecting this sensitive data is a significant challenge, with potential vulnerabilities extending from bugs in both software and hardware. One major class of vulnerabilities under active research is the use of Power Side Channels (PSCs), which involve precisely measuring the power consumption of a device over time. However, current research is fairly disjoint, without a standardized set of tools for quantifying protection techniques. This leads to the motivation of this project: to create a standardized baseline system for evaluating power side channels and their defenses. This project makes several contributions to the power side channel community. First, it enables calibration of Signal to Noise Ratio (SNR) measurements to a common baseline, and thus easier comparison between various defense techniques. Second, it proposes a method of measuring SNR that requires a constant number of samples, as compared to some techniques that keep sampling until some reference amount of information is leaked. Third, it includes a case study of AES cores which yields a better understanding of how a PSC amplification technique (specifically using many identical cores in parallel) affects the PSC’s signal “strength” and thus time to successfully extract the secret data. Finally, it makes public an ecosystem for quickly starting power side channel research without the significant effort of implementing everything from scratch before any research can begin.

Name thesis:degree_name

Master

Department dc:contributor.department

Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science

Grantor dc:publisher

Massachusetts Institute of Technology

Year dc:date.issued

2022

Author dc:creator

• John, Brandon

Advisors dc:contributor.advisor

• Yan, Mengjia
• Chetwynd, Brendon

Statement dc:rights

• In Copyright - Educational Use Permitted
• Copyright MIT

Licence dc:rights.uri

• http://rightsstatements.org/page/InC-EDU/1.0/

Handle dc:identifier.uri

https://hdl.handle.net/1721.1/144741

OAI identifier oai:identifier

oai:dspace.mit.edu:1721.1/144741