DitDetector: Bimodal Learning based on Deceptive Image and Text for Macro Malware Detection
Yan Jia, Ming Wan, Xiangkun Jia, Lingyun Ying, Purui Su, Zhanyi Wang
Abstract
Macro malware has always been a severe threat to cyber security although the Microsoft Office suite applies the default macro-disabling policy. Among the defense solutions at different stages of the attack chain, document analysis is more targeted through detecting malicious documents with macro malware. It is effective, especially with machine learning methods, but still faces problems handling malware variants, supporting file formats, and attack countermeasures with advanced attack techniques (e.g., Excel 4.0 macro and remote template injection).
Topics & Concepts
MalwareMacroComputer scienceSuiteComputer securityProgramming languageHistoryArchaeologyAdvanced Malware Detection TechniquesNetwork Security and Intrusion DetectionAnomaly Detection Techniques and Applications