Kiho Choi, Hyeongrae Kim, Daejin Park, Jeonghun Cho
{"title":"基于签名的控制流监控的自动多线程代码生成","authors":"Kiho Choi, Hyeongrae Kim, Daejin Park, Jeonghun Cho","doi":"10.1109/ICAIIC.2019.8668997","DOIUrl":null,"url":null,"abstract":"Signature-based control flow monitoring is a representative technique for detecting control flow errors in run time. However, it is very inefficient and time consuming to manually insert the monitoring code into a monitor-target application. In particular, for performance improvements of control-flow monitoring, implementing a monitoring code that operates in multi-thread makes things more complicated. In this paper, we propose an automatic code-generation framework that automatically translate an application into the control-flow monitorable application. In the proposed framework, the applied technique for control-flow monitoring is based on separate signature-based control-flow monitoring (SSCFM) technique that is able to expect performance improvements in multi-threaded or multi-core environments by separating the signature update and the signature verification on the thread level. The proposed framework automatically analyzes a monitor-target application and generates a SSCFM-applied application based on the analysis results. We anticipate that our automatic multi-thread code generation framework for control flow monitoring lessens the burden in runtime control-flow monitoring field.","PeriodicalId":273383,"journal":{"name":"2019 International Conference on Artificial Intelligence in Information and Communication (ICAIIC)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Automatic Multi-Thread Code Generation for Monitoring Signature-based Control Flow\",\"authors\":\"Kiho Choi, Hyeongrae Kim, Daejin Park, Jeonghun Cho\",\"doi\":\"10.1109/ICAIIC.2019.8668997\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Signature-based control flow monitoring is a representative technique for detecting control flow errors in run time. However, it is very inefficient and time consuming to manually insert the monitoring code into a monitor-target application. In particular, for performance improvements of control-flow monitoring, implementing a monitoring code that operates in multi-thread makes things more complicated. In this paper, we propose an automatic code-generation framework that automatically translate an application into the control-flow monitorable application. In the proposed framework, the applied technique for control-flow monitoring is based on separate signature-based control-flow monitoring (SSCFM) technique that is able to expect performance improvements in multi-threaded or multi-core environments by separating the signature update and the signature verification on the thread level. The proposed framework automatically analyzes a monitor-target application and generates a SSCFM-applied application based on the analysis results. We anticipate that our automatic multi-thread code generation framework for control flow monitoring lessens the burden in runtime control-flow monitoring field.\",\"PeriodicalId\":273383,\"journal\":{\"name\":\"2019 International Conference on Artificial Intelligence in Information and Communication (ICAIIC)\",\"volume\":\"12 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-02-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2019 International Conference on Artificial Intelligence in Information and Communication (ICAIIC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICAIIC.2019.8668997\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 International Conference on Artificial Intelligence in Information and Communication (ICAIIC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICAIIC.2019.8668997","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Automatic Multi-Thread Code Generation for Monitoring Signature-based Control Flow
Signature-based control flow monitoring is a representative technique for detecting control flow errors in run time. However, it is very inefficient and time consuming to manually insert the monitoring code into a monitor-target application. In particular, for performance improvements of control-flow monitoring, implementing a monitoring code that operates in multi-thread makes things more complicated. In this paper, we propose an automatic code-generation framework that automatically translate an application into the control-flow monitorable application. In the proposed framework, the applied technique for control-flow monitoring is based on separate signature-based control-flow monitoring (SSCFM) technique that is able to expect performance improvements in multi-threaded or multi-core environments by separating the signature update and the signature verification on the thread level. The proposed framework automatically analyzes a monitor-target application and generates a SSCFM-applied application based on the analysis results. We anticipate that our automatic multi-thread code generation framework for control flow monitoring lessens the burden in runtime control-flow monitoring field.