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. © 2011 IFIP International Federation for Information Processing.
CITATION STYLE
Zhao, J., Wen, Y., & Zhao, G. (2011). H-fuzzing: A new heuristic method for fuzzing data generation. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 6985 LNCS, pp. 32–43). https://doi.org/10.1007/978-3-642-24403-2_3
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