{"title":"内部异常检测系统的发展趋势","authors":"Minkyu Kim, Kihwan Kim, Hoonjae Lee","doi":"10.23919/ICACT.2018.8323761","DOIUrl":null,"url":null,"abstract":"Recently, industrial and national infrastructure suffered economic losses due to internal leaks caused by insider leaks and key data leaks. As a result, many companies applying not only physical external and internal penetration methods, but also software, machine learning, and other methods to detect people's abnormal behaviour. This paper surveys trends and forecasts of the intrusion detection techniques by categorizing into basic software and machine learning technique.","PeriodicalId":228625,"journal":{"name":"2018 20th International Conference on Advanced Communication Technology (ICACT)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":"{\"title\":\"Development trend of insider anomaly detection system\",\"authors\":\"Minkyu Kim, Kihwan Kim, Hoonjae Lee\",\"doi\":\"10.23919/ICACT.2018.8323761\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Recently, industrial and national infrastructure suffered economic losses due to internal leaks caused by insider leaks and key data leaks. As a result, many companies applying not only physical external and internal penetration methods, but also software, machine learning, and other methods to detect people's abnormal behaviour. This paper surveys trends and forecasts of the intrusion detection techniques by categorizing into basic software and machine learning technique.\",\"PeriodicalId\":228625,\"journal\":{\"name\":\"2018 20th International Conference on Advanced Communication Technology (ICACT)\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-02-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2018 20th International Conference on Advanced Communication Technology (ICACT)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.23919/ICACT.2018.8323761\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 20th International Conference on Advanced Communication Technology (ICACT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.23919/ICACT.2018.8323761","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Development trend of insider anomaly detection system
Recently, industrial and national infrastructure suffered economic losses due to internal leaks caused by insider leaks and key data leaks. As a result, many companies applying not only physical external and internal penetration methods, but also software, machine learning, and other methods to detect people's abnormal behaviour. This paper surveys trends and forecasts of the intrusion detection techniques by categorizing into basic software and machine learning technique.