Please use this identifier to cite or link to this item:
https://hdl.handle.net/10356/151844
Title: | On evaluating fault resilient encoding schemes in software | Authors: | Breier, Jakub Hou, Xiaolu Liu, Yang |
Keywords: | Engineering::Computer science and engineering::Data::Data encryption | Issue Date: | 2021 | Source: | Breier, J., Hou, X. & Liu, Y. (2021). On evaluating fault resilient encoding schemes in software. IEEE Transactions On Dependable and Secure Computing, 18(3), 1065-1079. https://dx.doi.org/10.1109/TDSC.2019.2897663 | Journal: | IEEE Transactions on Dependable and Secure Computing | 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 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. | URI: | https://hdl.handle.net/10356/151844 | ISSN: | 1545-5971 | DOI: | 10.1109/TDSC.2019.2897663 | Schools: | School of Computer Science and Engineering | Rights: | © 2021 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. The published version is available at: https://doi.org/10.1109/TDSC.2019.2897663 | Fulltext Permission: | open | Fulltext Availability: | With Fulltext |
Appears in Collections: | SCSE Journal Articles |
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