| Title | SPFA: SFA on Multiple Persistent Faults |
| Publication Type | Conference Paper |
| Year of Publication | 2020 |
| Authors | Engels, Susanne, Schellenberg, Falk, Paar, Christof |
| Conference Name | 2020 Workshop on Fault Detection and Tolerance in Cryptography (FDTC) |
| Keywords | Ciphers, Circuit faults, cyber physical systems, Encryption, Fault attack, Human Behavior, human factors, maximum likelihood estimation, Metrics, multiple fault diagnosis, persistent fault attack, pubcrawl, Random access memory, resilience, Resiliency, statistical fault analysis, Table lookup, Transient analysis |
| Abstract | For classical fault analysis, a transient fault is required to be injected during runtime, e.g., only at a specific round. Instead, Persistent Fault Analysis (PFA) introduces a powerful class of fault attacks that allows for a fault to be present throughout the whole execution. One limitation of original PFA as introduced by Zhang et al. at CHES'18 is that the adversary needs know (or brute-force) the faulty values prior to the analysis. While this was addressed at a follow-up work at CHES'20, the solution is only applicable to a single faulty value. Instead, we use the potency of Statistical Fault Analysis (SFA) in the persistent fault setting, presenting Statistical Persistent Fault Analysis (SPFA) as a more general approach of PFA. As a result, any or even a multitude of unknown faults that cause an exploitable bias in the targeted round can be used to recover the cipher's secret key. Indeed, the undesired faults in the other rounds that occur due the persistent nature of the attack converge to a uniform distribution as required by SFA. We verify the effectiveness of our attack against LED and AES. |
| DOI | 10.1109/FDTC51366.2020.00014 |
| Citation Key | engels_spfa_2020 |
SPFA: SFA on Multiple Persistent Faults