H-Fuzzing: A New Heuristic Method for Fuzzing Data Generation

Abstract : How to efficiently reduce the fuzzing data scale while assuring high fuzzing veracity and vulnerability coverage is a pivotal issue in program fuzz test. This paper proposes a new heuristic method for fuzzing data generation named with H-Fuzzing. H-Fuzzing achieves a high program execution path coverage by retrieving the static information and dynamic property from the program. Our experiments evaluate H-Fuzzing, Java Path Finder (JPF) and random fuzzing method. The evaluation results demonstrate that H-Fuzzing can use fewer iterations and testing time to reach more test path coverage compared with the other two methods.
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Erik Altman; Weisong Shi. 8th Network and Parallel Computing (NPC), Oct 2011, Changsha,, China. Springer, Lecture Notes in Computer Science, LNCS-6985, pp.32-43, 2011, Network and Parallel Computing. 〈10.1007/978-3-642-24403-2_3〉
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Jinjing Zhao, Yan Wen, Gang Zhao. H-Fuzzing: A New Heuristic Method for Fuzzing Data Generation. Erik Altman; Weisong Shi. 8th Network and Parallel Computing (NPC), Oct 2011, Changsha,, China. Springer, Lecture Notes in Computer Science, LNCS-6985, pp.32-43, 2011, Network and Parallel Computing. 〈10.1007/978-3-642-24403-2_3〉. 〈hal-01593032〉

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