API2Vec: Learning Representations of API Sequences for Malware Detection
Lei Cui, Jiancong Cui, Yuede Ji, Zhiyu Hao, Lun Li, Zhenquan Ding
Abstract
Analyzing malware based on API call sequence is an effective approach as the sequence reflects the dynamic execution behavior of malware.Recent advancements in deep learning have led to the application of these techniques for mining useful information from API call sequences. However, these methods mainly operate on raw sequences and may not effectively capture important information especially for multi-process malware, mainly due to the API call interleaving problem.
Topics & Concepts
MalwareComputer scienceInterleavingSequence (biology)Process (computing)System callArtificial intelligenceMalware analysisMachine learningProgramming languageOperating systemGeneticsBiologyAdvanced Malware Detection TechniquesNetwork Security and Intrusion DetectionAnomaly Detection Techniques and Applications