J. Rubin, Michael I. Gordon, Nguyen Nguyen, M. Rinard
{"title":"移动应用中的隐蔽通信(T)","authors":"J. Rubin, Michael I. Gordon, Nguyen Nguyen, M. Rinard","doi":"10.1109/ASE.2015.66","DOIUrl":null,"url":null,"abstract":"This paper studies communication patterns in mobile applications. Our analysis shows that 63% of the external communication made by top-popular free Android applications from Google Play has no effect on the user-observable application functionality. To detect such covert communication in an efficient manner, we propose a highly precise and scalable static analysis technique: it achieves 93% precision and 61% recall compared to the empirically determined \"ground truth\", and runs in a matter of a few minutes. Furthermore, according to human evaluators, in 42 out of 47 cases, disabling connections deemed covert by our analysis leaves the delivered application experience either completely intact or with only insignificant interference. We conclude that our technique is effective for identifying and disabling covert communication. We then use it to investigate communication patterns in the 500 top-popular applications from Google Play.","PeriodicalId":6586,"journal":{"name":"2015 30th IEEE/ACM International Conference on Automated Software Engineering (ASE)","volume":"154 1","pages":"647-657"},"PeriodicalIF":0.0000,"publicationDate":"2015-11-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"24","resultStr":"{\"title\":\"Covert Communication in Mobile Applications (T)\",\"authors\":\"J. Rubin, Michael I. Gordon, Nguyen Nguyen, M. Rinard\",\"doi\":\"10.1109/ASE.2015.66\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper studies communication patterns in mobile applications. Our analysis shows that 63% of the external communication made by top-popular free Android applications from Google Play has no effect on the user-observable application functionality. To detect such covert communication in an efficient manner, we propose a highly precise and scalable static analysis technique: it achieves 93% precision and 61% recall compared to the empirically determined \\\"ground truth\\\", and runs in a matter of a few minutes. Furthermore, according to human evaluators, in 42 out of 47 cases, disabling connections deemed covert by our analysis leaves the delivered application experience either completely intact or with only insignificant interference. We conclude that our technique is effective for identifying and disabling covert communication. We then use it to investigate communication patterns in the 500 top-popular applications from Google Play.\",\"PeriodicalId\":6586,\"journal\":{\"name\":\"2015 30th IEEE/ACM International Conference on Automated Software Engineering (ASE)\",\"volume\":\"154 1\",\"pages\":\"647-657\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-11-09\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"24\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2015 30th IEEE/ACM International Conference on Automated Software Engineering (ASE)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ASE.2015.66\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 30th IEEE/ACM International Conference on Automated Software Engineering (ASE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ASE.2015.66","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
This paper studies communication patterns in mobile applications. Our analysis shows that 63% of the external communication made by top-popular free Android applications from Google Play has no effect on the user-observable application functionality. To detect such covert communication in an efficient manner, we propose a highly precise and scalable static analysis technique: it achieves 93% precision and 61% recall compared to the empirically determined "ground truth", and runs in a matter of a few minutes. Furthermore, according to human evaluators, in 42 out of 47 cases, disabling connections deemed covert by our analysis leaves the delivered application experience either completely intact or with only insignificant interference. We conclude that our technique is effective for identifying and disabling covert communication. We then use it to investigate communication patterns in the 500 top-popular applications from Google Play.