Computer worms are characterized by rapid propagation and intrusive network disruption. In this work, we analyze the network behavior of five Internet worms: Sasser, Slammer, Eternal Rocks, WannaCry, and Petya. Through this analysis, we use a deep neural network to successfully classify network traces of these worms along with normal traffic. Our hybrid approach includes a visualization that allows for further analysis and tracing of the network behavior of detected worms.
CITATION STYLE
AL-Maksousy, H. H. L., & Weigle, M. C. (2019). Hybrid Intrusion Detection System for Worm Attacks Based on Their Network Behavior. In Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST (Vol. 259, pp. 225–234). Springer Verlag. https://doi.org/10.1007/978-3-030-05487-8_12
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