Behavioral Detection of Scanning Worm in Cyber Defense
作者: Mohammad M. RasheedMunadil K. Faaeq
作者单位: Scientific Information and Technology Transfer Center, Ministry of Science & Technology;;School of Business Management, College of Business, University Utara Malaysia
出版社: Springer International Publishing,   2018
ISBN: 978-3-030-02682-0
来源数据库: Springer Nature Book
DOI: 10.1007/978-3-030-02683-7_16
关键词: Worm detectionMalwareCyber defenseNetwork security
原始语种摘要: Abstract Conficker worm spread in November 2008, it was targeting Microsoft Windows operating system that has once infected 15 million hosts. The worm system defense must be automatically detection. Before we defend against worm, we must get the worm strategy by analysis of worm behavior. So therefore, we propose Behavioral Scanning Worm Detection (BSWD) for detecting Internet worm behavior that uses TCP and UDP scanning attack. We selected four different worms for validation of worm behavioral detection. The BSWD corrected results detected the MSBlaster worm behavior more than 99%, the behavior of Sesser, Dabber, Protoride behavior more than 97% of correction. Our algorithm result recognizes the worms’ behavior in one minute.
全文获取路径: Springer Nature 

  • worms 蠕虫动物
  • defend 防御
  • attack 侵蚀
  • selected 被选
  • defense 防备
  • automatically 自动地
  • security 可靠性
  • result 成果
  • behavior 行为
  • detecting 检测