Countermeasures Optimization in Multiple Fault-Injection Context. Boespflug, E., Ene, C., Mounier, L., & Potet, M. In 2020 Workshop on Fault Detection and Tolerance in Cryptography (FDTC), pages 26–34. IEEE. bibtex @InProceedings{boespflug20countermeasures,
author = {Boespflug, Etienne and Ene, Cristian and Mounier, Laurent and Potet, Marie-Laure},
booktitle = {2020 Workshop on Fault Detection and Tolerance in Cryptography (FDTC)},
date = {2020},
title = {Countermeasures Optimization in Multiple Fault-Injection Context},
organization = {IEEE},
pages = {26--34},
comment = {* context: fault injection as a (security) attack vector
* understand *countermeasures check points* (CCPs) as important
countermeasure
* i.e., where program checks safety conditions at runtime
* focus on optimization
* rather than on low overhead, as usual in literature
* formal descriptions
* programs, execution, modification, injection and detection
* multi-fault injection
* can be extended, e.g., by duplicating CCPs
* i.e., one for true, one for false branch
* e.g.::
condition = calculate_condition()
if condition:
if not condition:
injection_detected()
do_something()
else
if condition:
injection_detected()
* \# now, I think, if branches are attacked, there is a safety net
* code is being instrumented to contain CCPs
* algorithm to optimize (i.e., reduce) number of CCPs
* experiment
* using Lazart
* input: LLVM code, fault model, security property
* dynamic symbolic execution
* for single faults as example, 20% - 80% of CCPs can be
removed (optimized)},
file = {:boespflug20countermeasures - Countermeasures Optimization in Multiple Fault-Injection Context.pdf:PDF},
groups = {fault tolerance},
timestamp = {2021-03-16},
}
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