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浏览/检索结果: 共3条，第1-3条 帮助 限定条件 发表日期：2018    专题：北京航空航天大学    第一署名单位    第一作者单位    通讯作者单位     已选(0)清除 条数/页：5101520253035404550556065707580859095100   排序方式：请选择作者升序作者降序题名升序题名降序发表日期升序发表日期降序提交时间升序提交时间降序 An intrusion detection system based on machine learning for CAN-Bus 期刊论文 Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST, 2018, 卷号: 221, 页码: 285-294 作者:  Tian, D.;  Li, Y.;  Wang, Y.;  Duan, X.;  Wang, C. 收藏  |  浏览/下载：11/0  |  提交时间：2019/12/30 Adaptive boosting  Artificial intelligence  Computer crime  Control system synthesis  Data handling  Data mining  Decision trees  Entropy  Intelligent systems  Intrusion detection  Learning algorithms  Learning systems  Mercury (metal)  Metadata  Security of data  Trees (mathematics)  CAN bus  Detection performance  Feature construction  GBDT  Gradient boosting  Intrusion Detection Systems  True positive rates  Vehicle control system  Network security   A Novel Intrusion Detection System Based on Advanced Naive Bayesian Classification 期刊论文 Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST, 2018, 卷号: 211, 页码: 581-588 作者:  Wang, Y.;  Li, Y.;  Tian, D.;  Wang, C.;  Wang, W. 收藏  |  浏览/下载：3/0  |  提交时间：2019/12/30 5G mobile communication systems  Classification (of information)  Computer crime  Learning systems  Mercury (metal)  Network security  Pattern recognition  Pattern recognition systems  Security of data  Wireless networks  Classification results  Detection performance  Intrusion Detection Systems  Machine learning models  Naive Bayesian classification  ReliefF  Relieff algorithms  True positive rates  Intrusion detection   Social and Economic Factors' Impact on Fire Safety Risks-Panel Data Model Based Analysis 会议论文 2018 5TH INTERNATIONAL CONFERENCE ON INDUSTRIAL ECONOMICS SYSTEM AND INDUSTRIAL SECURITY ENGINEERING (IEIS 2018), 2018-01-01 作者:  Ren, Hao;  Zhou, Chang;  Li, Anglin 收藏  |  浏览/下载：11/0  |  提交时间：2019/12/30 fire risk  socio-economic factors  panel data model