{"title":"当机器学习遇到安全问题:一项调查","authors":"Zhenyu Guan, Liangxu Bian, Tao Shang, Jianwei Liu","doi":"10.1109/IISR.2018.8535799","DOIUrl":null,"url":null,"abstract":"Machine learning is one of the most prevalent techniques in recent decades which has been widely applied in various fields. Among them, the applications that detect and defend potential adversarial attacks using machine learning method provide promising solutions in cybersecurity. At the same time, machine learning algorithms and systems are vulnerable to multiple security threats. In this paper, we revisit certain literatures and present a comprehensive survey from two respects, application of machine learning on cybersecurity and reliability and security of machine learning system. We then overview security issues of mobile AI devices and propose two notable focus, which are worthy in-depth studies in future. Researchers can regard this survey as a navigating reference in both machine learning and cybersecurity fields.","PeriodicalId":201828,"journal":{"name":"2018 IEEE International Conference on Intelligence and Safety for Robotics (ISR)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"22","resultStr":"{\"title\":\"When Machine Learning meets Security Issues: A survey\",\"authors\":\"Zhenyu Guan, Liangxu Bian, Tao Shang, Jianwei Liu\",\"doi\":\"10.1109/IISR.2018.8535799\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Machine learning is one of the most prevalent techniques in recent decades which has been widely applied in various fields. Among them, the applications that detect and defend potential adversarial attacks using machine learning method provide promising solutions in cybersecurity. At the same time, machine learning algorithms and systems are vulnerable to multiple security threats. In this paper, we revisit certain literatures and present a comprehensive survey from two respects, application of machine learning on cybersecurity and reliability and security of machine learning system. We then overview security issues of mobile AI devices and propose two notable focus, which are worthy in-depth studies in future. Researchers can regard this survey as a navigating reference in both machine learning and cybersecurity fields.\",\"PeriodicalId\":201828,\"journal\":{\"name\":\"2018 IEEE International Conference on Intelligence and Safety for Robotics (ISR)\",\"volume\":\"24 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-08-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"22\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2018 IEEE International Conference on Intelligence and Safety for Robotics (ISR)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IISR.2018.8535799\",\"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 IEEE International Conference on Intelligence and Safety for Robotics (ISR)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IISR.2018.8535799","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
When Machine Learning meets Security Issues: A survey
Machine learning is one of the most prevalent techniques in recent decades which has been widely applied in various fields. Among them, the applications that detect and defend potential adversarial attacks using machine learning method provide promising solutions in cybersecurity. At the same time, machine learning algorithms and systems are vulnerable to multiple security threats. In this paper, we revisit certain literatures and present a comprehensive survey from two respects, application of machine learning on cybersecurity and reliability and security of machine learning system. We then overview security issues of mobile AI devices and propose two notable focus, which are worthy in-depth studies in future. Researchers can regard this survey as a navigating reference in both machine learning and cybersecurity fields.