Abstract
Adversarial malware examples refer to the malwares that can evade the malware detector. Researching adversarial malware examples can help us find the vulnerability of malware detector and improve the defense ability of cyberspace. Considering the huge market share of android system, adversarial malware examples of android are studied in this paper. And an algorithm is proposed to find universal adversarial perturbations of malware. Such perturbation can be inserted the different malwares to generate adversarial examples. Then the effectiveness of algorithm is verified in the experiment. And three classic android malware detectors are used as targets. Experimental results show that universal adversarial perturbations for different machine learning models can be discovered via the proposed algorithm.
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Hou, R., Xiang, X., Zhang, Q., Liu, J., Huang, T. (2021). Universal Adversarial Perturbations of Malware. In: Cheng, J., Tang, X., Liu, X. (eds) Cyberspace Safety and Security. CSS 2020. Lecture Notes in Computer Science(), vol 12653. Springer, Cham. https://doi.org/10.1007/978-3-030-73671-2_2
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DOI: https://doi.org/10.1007/978-3-030-73671-2_2
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