• English
  • Deutsch
  • Log In
    Password Login
    Research Outputs
    Fundings & Projects
    Researchers
    Institutes
    Statistics
Repository logo
Fraunhofer-Gesellschaft
  1. Home
  2. Fraunhofer-Gesellschaft
  3. Konferenzschrift
  4. Automatic extraction of secrets from the transistor jungle using laser-assisted side-channel attacks
 
  • Details
  • Full
Options
2021
Conference Paper
Title

Automatic extraction of secrets from the transistor jungle using laser-assisted side-channel attacks

Abstract
The security of modern electronic devices relies on secret keys stored on secure hardware modules as the root-of-trust (RoT). Extracting those keys would break the security of the entire system. As shown before, sophisticated side-channel analysis (SCA) attacks, using chip failure analysis (FA) techniques, can extract data from on-chip memory cells. However, since the chip's layout is unknown to the adversary in practice, secret key localization and reverse engineering are onerous tasks. Consequently, hardware vendors commonly believe that the ever-growing physical complexity of the integrated circuit (IC) designs can be a natural barrier against potential adversaries. In this work, we present a novel approach that can extract the secret key without any knowledge of the IC's layout, and independent from the employed memory technology as key storage. We automate the - traditionally very labor-intensive - reverse engineering and data extraction process. To that end, we de monstrate that black-box measurements captured using laser-assisted SCA techniques from a training device with known key can be used to profile the device for a later key prediction on other victim devices with unknown keys. To showcase the potential of our approach, we target keys on three different hardware platforms, which are utilized as RoT in different products.
Author(s)
Krachenfels, T.
Kiyan, T.
Tajik, S.
Seifert, J.-P.
Mainwork
30th USENIX Security Symposium 2021. Proceedings  
Conference
USENIX Security Symposium 2021  
Link
Link
Language
English
Fraunhofer-Institut für Sichere Informationstechnologie SIT  
  • Cookie settings
  • Imprint
  • Privacy policy
  • Api
  • Contact
© 2024