On Evaluating Fault Resilient Encoding Schemes in Software

Abstract

Cryptographic implementations are often vulnerable against physical attacks, fault injection analysis being among the most popular techniques. On par with development of attacks, the area of countermeasures is advancing rapidly, utilizing both hardware-and software-based approaches. When it comes to software encoding countermeasures for fault protection and their evaluation, there are very few proposals so far, mostly focusing on single operations rather than cipher as a whole. In this paper we propose an evaluation framework that can be used for analyzing the effectivity of software encoding countermeasures against fault attacks. We first formalize the encoding schemes in software, helping us to define what properties are required when designing a fault protection. Based on these findings, we develop an evaluation metric that can be used universally to determine the robustness of a software encoding scheme against bit flip faults and instruction skips. We provide a way to select a code according to user criteria and also a dynamic code analysis method to estimate the level of protection of assembly implementations using encoding schemes. Finally, we verify our findings by implementing a block cipher PRESENT, protected by encoding scheme based on anticodes, and provide a detailed evaluation of this implementation using different codes.

SNIFF: Reverse Engineering of Neural Networks with Fault Attacks

“…For the protected implementation, there is a register precharge (see e.g. Section 5.1 of [38]) of both input registers and the output register (3 × 1 clk cycle), followed by the operand loading (2 × 1 clk cycle) and table look-up (2 clk cycles), resulting into 7 clock cycles. Regarding the area overhead, as stated in [38], in case the codeword size is ≤ 8 bits, there is a fixed table size of 65 kB per binary operation (e.g.…”

“…Implementation level techniques aim at detecting changes in the intermediate data. Detection can be achieved by using various encoding techniques, ranging from simple ones such as parity [37], to sophisticated codes that can be customized to protect against specific fault models [38]. Another approach is performing the computation several times and comparing the result.…”

Classical and Physical Security of Symmetric Key Cryptographic Algorithms

“…Therefore, researchers try to design a countermeasure which is capable of protecting against both [SMG16; BH17]. Ways to find efficient codes and to evaluate the encoding-protected cipher implementations are studied in [BHL19].…”

Chaotic neural network model for SMISs reliability prediction based on interdependent network SMISs reliability prediction by chaotic neural network

“…It is worth noting that we can obtain appropriate estimates of N , m , r by using BDS statistics. Brock et al 46 made several important asymptotic distributions, and the mathematical statistics results showed that when, the asymptotic distribution can be well approximated by a finite sequence and that can represent correlation of sequences. Moreover, the selection of time delay is independent of the value of embedded dimension m .…”

“…Compared with multimodel synthesis methods, fault data fusion methods have improved the prediction accuracy. Fault data fusion methods 42–46 can be divided into two categories: (1) Taking hardware correlation failure as the main manifestation of systems failure, a system impact model is established for software correlation failure, which is then converted into systems failure and comprehensively evaluated. (2) Taking software correlation failure as the main manifestation of system failure, a system impact model is established for hardware correlation failure, which is then converted into system failure and comprehensively evaluated.…”