摘要
舰船物联网异常入侵行为复杂多变,当前方法存在舰船物联网异常入侵行为误识率高等不足,为了改善舰船物联网异常入侵行为识别效果,设计了基于证据理论的舰船物联网异常入侵行为方法。首先采用多个单一方法对物联网异常入侵行为进行识别,每一个识别结果作为一种证据,然后采用证据理论对单一方法的物联网异常入侵行为识别结果进行融合,最后对物联网异常入侵行为识别效果进行测试。本文方法能够对物联网异常入侵行为进行准确识别,降低了物联网异常入侵行为的误识率,验证了本文方法用于物联网异常入侵行为识别的有效性。
the abnormal intrusion behavior of the ship's Internet of things is complex and changeable, and the current method has a high error rate of abnormal invasion of the ship's IOT. In order to improve the recognition effect of the abnormal intrusion behavior of the ship's IOT, a method of abnormal intrusion behavior of the ship's Internet of things based on evidence theory is designed. First of all, a number of single methods are used to identify the abnormal intrusion behavior of the Internet of things. Each identification result is a kind of evidence, then the evidence theory is used to fuse the identification results of the unusually intrusion behavior of the Internet of things. Finally, the identification effect of the abnormal intrusion behavior of the Internet of things is tested. This method can accurately identify the abnormal intrusion behavior of the Internet of things, reduce the error rate of the abnormal intrusion behavior of the Internet of things, and verify the effectiveness of the method used in the identification of abnormal intrusion behavior in the Internet of things.
出处
《舰船科学技术》
北大核心
2018年第8X期106-108,共3页
Ship Science and Technology
关键词
物联网
异常入侵
行为识别
证据理论
Internet of things
anomaly intrusion
behavior recognition
evidence theory
