Abstract
Network forensics known as an extended phase of network security plays an essential role in dealing with cybercrime. The performance of a network forensics system heavily depends on the network attack detection solutions. Two main types of network attacks are network level and application level. Current research methods have improved the detection rate but this is still a challenge. We propose a Shannon entropy approach to this study to identify executable file content for anomaly-based network attack detection in network forensics systems. Experimental results show that the proposed approach provides high detection rate.
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Nguyen, K., Tran, D., Ma, W., Sharma, D. (2014). A New Approach to Executable File Fragment Detection in Network Forensics. In: Au, M.H., Carminati, B., Kuo, CC.J. (eds) Network and System Security. NSS 2015. Lecture Notes in Computer Science, vol 8792. Springer, Cham. https://doi.org/10.1007/978-3-319-11698-3_40
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DOI: https://doi.org/10.1007/978-3-319-11698-3_40
Publisher Name: Springer, Cham
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