Fatih Durmaz, Nureddin Kamadan, Melih Öz, M. Unal, Arsalan Javeed, Cemal Yilmaz, E. Savaş
{"title":"TimeInspector:用于检测定时攻击的静态分析方法","authors":"Fatih Durmaz, Nureddin Kamadan, Melih Öz, M. Unal, Arsalan Javeed, Cemal Yilmaz, E. Savaş","doi":"10.1109/EuroSPW59978.2023.00037","DOIUrl":null,"url":null,"abstract":"We present a static analysis approach to detect malicious binaries that are capable of carrying out a timing attack. The proposed approach is based on a simple observation that the timing attacks typically operate by measuring the execution times of short sequences of instructions. Consequently, given a binary, we first construct the control flow graph of the binary and then determine the paths between the pairs of time readings, on which a suspiciously low number of instructions might be executed. In the presence of such a path, we mark the binary as potentially malicious and report all the suspicious paths identified. In the experiments, where a collection of benign and malicious binaries were used, the proposed approach correctly detected all the malicious binaries with an accuracy up to 99.5% and without any false negatives.","PeriodicalId":220415,"journal":{"name":"2023 IEEE European Symposium on Security and Privacy Workshops (EuroS&PW)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"TimeInspector: A Static Analysis Approach for Detecting Timing Attacks\",\"authors\":\"Fatih Durmaz, Nureddin Kamadan, Melih Öz, M. Unal, Arsalan Javeed, Cemal Yilmaz, E. Savaş\",\"doi\":\"10.1109/EuroSPW59978.2023.00037\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We present a static analysis approach to detect malicious binaries that are capable of carrying out a timing attack. The proposed approach is based on a simple observation that the timing attacks typically operate by measuring the execution times of short sequences of instructions. Consequently, given a binary, we first construct the control flow graph of the binary and then determine the paths between the pairs of time readings, on which a suspiciously low number of instructions might be executed. In the presence of such a path, we mark the binary as potentially malicious and report all the suspicious paths identified. In the experiments, where a collection of benign and malicious binaries were used, the proposed approach correctly detected all the malicious binaries with an accuracy up to 99.5% and without any false negatives.\",\"PeriodicalId\":220415,\"journal\":{\"name\":\"2023 IEEE European Symposium on Security and Privacy Workshops (EuroS&PW)\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-07-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2023 IEEE European Symposium on Security and Privacy Workshops (EuroS&PW)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/EuroSPW59978.2023.00037\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2023 IEEE European Symposium on Security and Privacy Workshops (EuroS&PW)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/EuroSPW59978.2023.00037","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
TimeInspector: A Static Analysis Approach for Detecting Timing Attacks
We present a static analysis approach to detect malicious binaries that are capable of carrying out a timing attack. The proposed approach is based on a simple observation that the timing attacks typically operate by measuring the execution times of short sequences of instructions. Consequently, given a binary, we first construct the control flow graph of the binary and then determine the paths between the pairs of time readings, on which a suspiciously low number of instructions might be executed. In the presence of such a path, we mark the binary as potentially malicious and report all the suspicious paths identified. In the experiments, where a collection of benign and malicious binaries were used, the proposed approach correctly detected all the malicious binaries with an accuracy up to 99.5% and without any false negatives.