{"title":"基于标准服务器比较的时钟漂移数字设备特征提取方法","authors":"Naoto Hoshikawa, T. Shimobaba, T. Ito","doi":"10.1109/ICCCI49374.2020.9145998","DOIUrl":null,"url":null,"abstract":"Open connectivity is required to expand the IoT services, but such environments are prone to the risk of information leakage and illegal operation by spoofing. In this paper, we present clock fingerprints concept based on clock frequency trait, and propose a method for extracting trait using clock drifts and criterion server. This trait can be available in identifying digital equipment to increase security in the future open IoT services. In our two experiments, we demonstrate the extraction of traits from some computers. First one show that unique characteristics can be extracted from two kinds of clock signals. Second show that different characteristics can be extracted from the same model number and the same software settings. We conclude with the challenges that we plan to address in our future work to improve this method.","PeriodicalId":153290,"journal":{"name":"2020 2nd International Conference on Computer Communication and the Internet (ICCCI)","volume":"92 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Trait Extraction Method for Digital Equipment Using Clock Drifts Based on Comparison of Criterion Server\",\"authors\":\"Naoto Hoshikawa, T. Shimobaba, T. Ito\",\"doi\":\"10.1109/ICCCI49374.2020.9145998\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Open connectivity is required to expand the IoT services, but such environments are prone to the risk of information leakage and illegal operation by spoofing. In this paper, we present clock fingerprints concept based on clock frequency trait, and propose a method for extracting trait using clock drifts and criterion server. This trait can be available in identifying digital equipment to increase security in the future open IoT services. In our two experiments, we demonstrate the extraction of traits from some computers. First one show that unique characteristics can be extracted from two kinds of clock signals. Second show that different characteristics can be extracted from the same model number and the same software settings. We conclude with the challenges that we plan to address in our future work to improve this method.\",\"PeriodicalId\":153290,\"journal\":{\"name\":\"2020 2nd International Conference on Computer Communication and the Internet (ICCCI)\",\"volume\":\"92 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-06-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2020 2nd International Conference on Computer Communication and the Internet (ICCCI)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICCCI49374.2020.9145998\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 2nd International Conference on Computer Communication and the Internet (ICCCI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCCI49374.2020.9145998","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Trait Extraction Method for Digital Equipment Using Clock Drifts Based on Comparison of Criterion Server
Open connectivity is required to expand the IoT services, but such environments are prone to the risk of information leakage and illegal operation by spoofing. In this paper, we present clock fingerprints concept based on clock frequency trait, and propose a method for extracting trait using clock drifts and criterion server. This trait can be available in identifying digital equipment to increase security in the future open IoT services. In our two experiments, we demonstrate the extraction of traits from some computers. First one show that unique characteristics can be extracted from two kinds of clock signals. Second show that different characteristics can be extracted from the same model number and the same software settings. We conclude with the challenges that we plan to address in our future work to improve this method.