Detection and Correction of Malicious and Natural Faults in Cryptographic Modules

Abstract

Today's electronic systems must simultaneously fulfill strict requirements on security and reliability. In particular, their cryptographic modules are exposed to faults, which can be due to natural failures (e.g., radiation or electromagnetic noise) or malicious faultinjection attacks. We present an architecture based on a new class of error-detecting codes that combine robustness properties with a minimal distance. The new architecture guarantees (with some probability) the detection of faults injected by an intelligent and strategic adversary who can precisely control the disturbance. At the same time it supports automatic correction of low-multiplicity faults. To this end, we discuss an efficient technique to correct single errors while avoiding full syndrome analysis. We report experimental results obtained by physical fault injection on the SAKURA-G FPGA board.

Error control scheme for malicious and natural faults in cryptographic modules

“…4. We can now calculate e i = s j g i = 14 and the corre- 13,14,13,12,4,15,14,4,11,3] We have successfully corrected the single error.…”

Towards Secure Composition of Integrated Circuits and Electronic Systems: On the Role of EDA

“…To integrate FIA detection into the same DFX infrastructure seems only logical. However, distinguishing between natural and malicious faults is non-trivial [59], and the responses should be different: fastest possible recovery and resumption of regular operation upon a natural fault, but re-keying or even discontinuation of service upon a tampering attempt. Therefore, future security-aware DFX infrastructures should enable such distinction.…”

Hardware Security For and Beyond CMOS Technology

“…Countermeasures include detection of faults at runtime, e.g., see [20], and hardening against fault injection at design and manufacturing time, e.g., see [21,22]. Note that distinguishing between natural and malicious faults is non-trivial [23], which imposes practical challenges for recovery at runtime.…”