This reposity is the implementation of the Springer book chapter entiteled : " Classification of Malicious and Benign Binaries Using Visualization Technique and Machine Learning Algorithms ", DOI: 10.1007/978-3-030-87954-9_14
In this paper, we use visualization technique for both benign and malicious samples. So, a hybrid feature extraction method is implemented using local and global image features by combining DAISY and HOG features. Then a comparative study of machine learning algorithms leads us to a final efficient classifier that reaches an accuracy of 97,36% using Random Forest classification algorithm.
Cite this chapter as : Ben Abdel Ouahab I., Elaachak L., Bouhorma M. (2022) Classification of Malicious and Benign Binaries Using Visualization Technique and Machine Learning Algorithms. In: Baddi Y., Gahi Y., Maleh Y., Alazab M., Tawalbeh L. (eds) Big Data Intelligence for Smart Applications. Studies in Computational Intelligence, vol 994. Springer, Cham. https://doi.org/10.1007/978-3-030-87954-9_14
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