Georg Sigl
2 indexed papers
Publications per year
Top categories
Frequent co-authors
Research Timeline
This paper proposes training a single neural network using EM traces collected from multiple probe positions to detect cryptographic leakage across a larger area of a target device, validated by cross-lab testing.
The paper develops a quantitative scoring system, CRESS, to consistently and comparably rate the severity of novel hardware reverse engineering attack scenarios, proving it is more expressive than industry standards like CVSS.
Papers
CRESS: Quantifying Vulnerabilities of Attack Scenarios in Hardware Reverse Engineering
The paper develops a quantitative scoring system, CRESS, to consistently and comparably rate the severity of novel hardware reverse engineering attack scenarios, proving it is more expressive than ind…