A Survey of Machine Learning Approaches for Malware Detec-tion

At present, due to the rapid evolution of malicious code and the rapid progress of science and technology, the security of information system has been put forward higher requirements. This research systematically reviews the current detection technologies for malicious code, from classical machine learning algorithms to some existing mature algorithms, and introduces machine learning, deep learning, and other technologies on this basis. In addition, malicious code detection technology based on large-scale language modeling (LLMS) is also studied. This study focuses on the advantages, limitations, and problems in practical applications of various detection techniques, and compares traditional methods, machine learning, and deep learning methods, and looks forward to future work.