Abstract
Artificial immune system(AIS) is an efficient solution for network security. In this paper, an artificial immune system approach for malware detection is proposed, which is referred to AISMD. In AISMD, the method to build the profile of benign executables in computer systems is given. Based on the built model of benign executable, the detectors are generated to detect malware. Experimental results show that AISMD is an efficient method to build the profile of benign executable and extract the characteristics of the executable, and has better detecting ability than that of the previous techniques.
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Zeng, J., Tang, W. (2014). An Artificial Immune System Approach for Malware Detection. In: Pan, L., Păun, G., Pérez-Jiménez, M.J., Song, T. (eds) Bio-Inspired Computing - Theories and Applications. Communications in Computer and Information Science, vol 472. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-45049-9_91
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DOI: https://doi.org/10.1007/978-3-662-45049-9_91
Publisher Name: Springer, Berlin, Heidelberg
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Online ISBN: 978-3-662-45049-9
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