With the increasing number and types of malicious codes and the development of code confusion technology, malicious code detection becomes more and more difficult. The traditional malicious code monitoring technology has been unable to realize the accurate identification of malicious code, which leads to the increasing risk of the computer system being threatened by malicious code. Based on the current development trend of malicious code, this paper proposes a malicious code monitoring technology through data mining and machine learning, which can realize a more accurate identification of malicious code and create better conditions for the detection and killing of malicious code.

Ye Zhang. Research on Malicious Code Detection Techniques Based on Data Mining and Machine Learning. Academic Journal of Computing & Information Science (2024), Vol. 7, Issue 1: 72-77. https://doi.org/10.25236/AJCIS.2024.070111.

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