A Statistical Model to Predict Success Rate of Ion Fault Injection Attacks for Cryptographic ICs

Fault injection attacks have posed serious threat to cryptographic integrated circuits (crypto-ICs). Heavy ion is one of the most powerful fault injection source due to its high energy and focused beam sizes. However, the ion has to strike on the certain transistor at the exact time instances. We choose the certain transistor among tens of thousands of transistors on the chip. And we choose the exact time instances during the whole decryption period. Only this kind of hit can cause a successful ion fault attack on crypto-ICs. The success rate is niche and often highly relies on experiences. This paper proposes a prediction model considering the ion density, crypto-ICs and the cryptographic algorithms. The model helps to indicate the appropriate Poisson intensity and beam spot size to maximize the success rate, so as to ease the ion fault injection test. Experimental results prove the feasibility of our model.