{"title":"基于DNS查询相似度的Android pua检测与分类","authors":"Mitsuhiro Hatada, Tatsuya Mori","doi":"10.1109/COMPSAC.2017.103","DOIUrl":null,"url":null,"abstract":"This work develops a method of detecting and classifying “potentially unwanted applications” (PUAs) such as adware or remote monitoring tools. Our approach leverages DNS queries made by apps. Using a large sample of Android apps from third-party marketplaces, we first reveal that DNS queries can provide useful information for the detection and classification of PUAs. Next, we show that existing DNS blacklists are ineffective to perform these tasks. Finally, we demonstrate that our methodology performed with high accuracy.","PeriodicalId":6556,"journal":{"name":"2017 IEEE 41st Annual Computer Software and Applications Conference (COMPSAC)","volume":"160 1","pages":"590-595"},"PeriodicalIF":0.0000,"publicationDate":"2017-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":"{\"title\":\"Detecting and Classifying Android PUAs by Similarity of DNS queries\",\"authors\":\"Mitsuhiro Hatada, Tatsuya Mori\",\"doi\":\"10.1109/COMPSAC.2017.103\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This work develops a method of detecting and classifying “potentially unwanted applications” (PUAs) such as adware or remote monitoring tools. Our approach leverages DNS queries made by apps. Using a large sample of Android apps from third-party marketplaces, we first reveal that DNS queries can provide useful information for the detection and classification of PUAs. Next, we show that existing DNS blacklists are ineffective to perform these tasks. Finally, we demonstrate that our methodology performed with high accuracy.\",\"PeriodicalId\":6556,\"journal\":{\"name\":\"2017 IEEE 41st Annual Computer Software and Applications Conference (COMPSAC)\",\"volume\":\"160 1\",\"pages\":\"590-595\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-09-07\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"6\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2017 IEEE 41st Annual Computer Software and Applications Conference (COMPSAC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/COMPSAC.2017.103\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 IEEE 41st Annual Computer Software and Applications Conference (COMPSAC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/COMPSAC.2017.103","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Detecting and Classifying Android PUAs by Similarity of DNS queries
This work develops a method of detecting and classifying “potentially unwanted applications” (PUAs) such as adware or remote monitoring tools. Our approach leverages DNS queries made by apps. Using a large sample of Android apps from third-party marketplaces, we first reveal that DNS queries can provide useful information for the detection and classification of PUAs. Next, we show that existing DNS blacklists are ineffective to perform these tasks. Finally, we demonstrate that our methodology performed with high accuracy.
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