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See detailShadObf: A C-source Obfuscator based on Multi-objective Optimization Algorithms
Bertholon, Benoit UL; Varrette, Sébastien UL; Martinez, S.

in Proc. of the 16th Intl. Workshop on Nature Inspired Distributed Computing (NIDISC 2013), part of the 27th IEEE/ACM Intl. Parallel and Distributed Processing Symposium (IPDPS 2013) (2013, May)

The Development of the new Cloud Computing paradigm as lead to a reorganisation in the order of the priorities of security issues. When running a private code on a Public Cloud or on any remote machine ... [more ▼]

The Development of the new Cloud Computing paradigm as lead to a reorganisation in the order of the priorities of security issues. When running a private code on a Public Cloud or on any remote machine, its owner have no guarantees that the code cannot be reverse engineered, understood and modified. One of the solution for the code owner in order to protect his intellectual property is to obfuscate his algorithms. The Obfuscation of source code is a mechanism to modify a source code to make unintelligible by humans even with the help of computing resources. More precisely, the objective is to conceal the purpose of a program or its logic without altering its functionality, thus preventing the tampering or the reverse engineering of the program Obfuscation is usually performed by applying transformations to the initial source code, but it reveals many open questions: what transformation should be chosen? In which order should the obfuscator apply them? How can we quantify the obfuscation capacity of a given program? In order to answer these questions, we propose here SHADOBF, an obfuscation framework based on evolutionary heuristics designed to optimize for a given input C program, the sequence of transformations that should be applied to the source code to improve its obfuscation capacity. This last measure involves the combination of well known metrics, coming from the Software Engineering area, which are optimized simultaneously thanks to Multi Objective Evo- lutionary Algorithms (MOEAs). We have validated our approach over a classical matrix multiplication program – experiments on other applications is still in progress. Some experiments, presented here, has been performed on some basic but representative examples to valid the feasibility of the method. [less ▲]

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