AppPoet: Large Language Model based Android malware detection via multi-view prompt engineering

arXiv:2404.18816v1 Announce Type: new
Abstract: Due to the vast array of Android applications, their multifarious functions and intricate behavioral semantics, attackers can adopt various tactics to conceal their genuine attack intentions within legitimate functions. However, numerous feature engineering based methods suffer from a limitation in mining behavioral semantic information, thus impeding the accuracy and efficiency of Android malware detection. Besides, the majority of existing feature engineering based methods are weakly interpretive and fail to furnish researchers with effective and readable …

android android malware applications array arxiv attack attackers can conceal cs.cr cs.se detection engineering feature functions language large large language model malware malware detection mining prompt semantic semantics tactics vast