Artificial diversification of a software program can be a versatile tool in a wide range of software engineering and security scenarios. For example, randomizing implementation aspects can increase the costs for attackers as it prevents them from benefiting of precise knowledge of their target. A promising angle for diversification can be having two runs of a program on the same input yield inherently diverse instruction traces. Inspired by on-stack replacement designs for managed runtimes, in this paper we study how to transform a C program to realize continuous transfers of control and program state among function variants as they run. We discuss the technical challenges toward such goal and propose effective compiler techniques for it that enable the re-use of existing techniques for static diversification with no modifications. We implement our approach in LLVM and evaluate it on both synthetic and real-world subjects.
2022, Proceedings of the 37th IEEE/ACM International Conference on Automated Software Engineering, Pages 1-5
Principled Composition of Function Variants for Dynamic Software Diversity and Program Protection (04b Atto di convegno in volume)
Priamo Giacomo, D'Elia Daniele Cono, Querzoni Leonardo
Gruppo di ricerca: Cybersecurity