Behavior-based malware analysis is an important technique for automatically analyzing and detecting malware, and it
has received considerable attention from both academic and industrial communities. By considering how malware behaves, we can
tackle the malware obfuscation problem, which cannot be processed by traditional static analysis approaches, and we can also
derive the as-built behavior specifications and cover the entire behavior space of the malware samples. Although there have been
several works focusing on malware behavior analysis, such research is far from mature, and no overviews have been put forward to
date to investigate current developments and challenges. In this paper, we conduct a survey on malware behavior description and
analysis considering three aspects: malware behavior description, behavior analysis methods, and visualization techniques. First,
existing behavior data types and emerging techniques for malware behavior description are explored, especially the goals, prin-
ciples, characteristics, and classifications of behavior analysis techniques proposed in the existing approaches. Second, the in-
adequacies and challenges in malware behavior analysis are summarized from different perspectives. Finally, several possible
directions are discussed for future research.

关键词： Malware ,  behavior,   ,  Static ,  analysis,   ,  Dynamic ,  Analysis,   ,  Behavior ,  data ,  expression,   ,  Behavior ,  analysis,  Machine
learning,  Semantics-based analysis,  Behavior visualization,  Malware evolution