{"title":"基于行为模式的操作系统内核运行时完整性检查","authors":"Xinyue Feng, Qiusong Yang, Lin Shi, Qing Wang","doi":"10.1109/QRS.2018.00015","DOIUrl":null,"url":null,"abstract":"Kernel rootkits pose a serious threat to system security by tampering with the state of operating system inconspicuously. To ensure operating system kernel integrity, Virtual Machine Monitor (VMM) based approaches have been proposed. Most of these approaches use snapshot-based or event-triggered techniques. However, snapshot-based techniques have been suffering from missing transient attacks or significant performance overhead, while event-triggered methods are facing with heavy workload as integrity checking might be triggered by any suspicious actions. In this paper, we propose a novel solution which is a behavior-triggered integrity checking approach named BehaviorKI. By analyzing attacking processes, BehaviorKI can extract a set of behavior patterns which characterize malicious behaviors. BehaviorKI will trigger integrity checking with kernel invariants when a malicious behavior pattern detected. In this way, our approach can alleviate the performance burden by reducing the frequent kernel integrity checking. The experiment results show that Be-haviorKI outperforms existing snapshot-based and event-triggered approaches.","PeriodicalId":114973,"journal":{"name":"2018 IEEE International Conference on Software Quality, Reliability and Security (QRS)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":"{\"title\":\"BehaviorKI: Behavior Pattern Based Runtime Integrity Checking for Operating System Kernel\",\"authors\":\"Xinyue Feng, Qiusong Yang, Lin Shi, Qing Wang\",\"doi\":\"10.1109/QRS.2018.00015\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Kernel rootkits pose a serious threat to system security by tampering with the state of operating system inconspicuously. To ensure operating system kernel integrity, Virtual Machine Monitor (VMM) based approaches have been proposed. Most of these approaches use snapshot-based or event-triggered techniques. However, snapshot-based techniques have been suffering from missing transient attacks or significant performance overhead, while event-triggered methods are facing with heavy workload as integrity checking might be triggered by any suspicious actions. In this paper, we propose a novel solution which is a behavior-triggered integrity checking approach named BehaviorKI. By analyzing attacking processes, BehaviorKI can extract a set of behavior patterns which characterize malicious behaviors. BehaviorKI will trigger integrity checking with kernel invariants when a malicious behavior pattern detected. In this way, our approach can alleviate the performance burden by reducing the frequent kernel integrity checking. The experiment results show that Be-haviorKI outperforms existing snapshot-based and event-triggered approaches.\",\"PeriodicalId\":114973,\"journal\":{\"name\":\"2018 IEEE International Conference on Software Quality, Reliability and Security (QRS)\",\"volume\":\"15 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-07-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"7\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2018 IEEE International Conference on Software Quality, Reliability and Security (QRS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/QRS.2018.00015\",\"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 Software Quality, Reliability and Security (QRS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/QRS.2018.00015","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
BehaviorKI: Behavior Pattern Based Runtime Integrity Checking for Operating System Kernel
Kernel rootkits pose a serious threat to system security by tampering with the state of operating system inconspicuously. To ensure operating system kernel integrity, Virtual Machine Monitor (VMM) based approaches have been proposed. Most of these approaches use snapshot-based or event-triggered techniques. However, snapshot-based techniques have been suffering from missing transient attacks or significant performance overhead, while event-triggered methods are facing with heavy workload as integrity checking might be triggered by any suspicious actions. In this paper, we propose a novel solution which is a behavior-triggered integrity checking approach named BehaviorKI. By analyzing attacking processes, BehaviorKI can extract a set of behavior patterns which characterize malicious behaviors. BehaviorKI will trigger integrity checking with kernel invariants when a malicious behavior pattern detected. In this way, our approach can alleviate the performance burden by reducing the frequent kernel integrity checking. The experiment results show that Be-haviorKI outperforms existing snapshot-based and event-triggered approaches.