Kevin A. Roundy, Paula Barmaimon Mendelberg, Nicola Dell, Damon McCoy, Daniel N. Nissani, T. Ristenpart, Acar Tamersoy
{"title":"The Many Kinds of Creepware Used for Interpersonal Attacks","authors":"Kevin A. Roundy, Paula Barmaimon Mendelberg, Nicola Dell, Damon McCoy, Daniel N. Nissani, T. Ristenpart, Acar Tamersoy","doi":"10.1109/SP40000.2020.00069","DOIUrl":null,"url":null,"abstract":"Technology increasingly facilitates interpersonal attacks such as stalking, abuse, and other forms of harassment. While prior studies have examined the ecosystem of software designed for stalking, there exists an unstudied, larger landscape of apps—what we call creepware—used for interpersonal attacks. In this paper, we initiate a study of creepware using access to a dataset detailing the mobile apps installed on over 50 million Android devices. We develop a new algorithm, CreepRank, that uses the principle of guilt by association to help surface previously unknown examples of creepware, which we then characterize through a combination of quantitative and qualitative methods. We discovered apps used for harassment, impersonation, fraud, information theft, concealment, and even apps that purport to defend victims against such threats. As a result of our work, the Google Play Store has already removed hundreds of apps for policy violations. More broadly, our findings and techniques improve understanding of the creepware ecosystem, and will inform future efforts that aim to mitigate interpersonal attacks.","PeriodicalId":6849,"journal":{"name":"2020 IEEE Symposium on Security and Privacy (SP)","volume":"3 1","pages":"626-643"},"PeriodicalIF":0.0000,"publicationDate":"2020-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"27","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 IEEE Symposium on Security and Privacy (SP)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SP40000.2020.00069","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 27
Abstract
Technology increasingly facilitates interpersonal attacks such as stalking, abuse, and other forms of harassment. While prior studies have examined the ecosystem of software designed for stalking, there exists an unstudied, larger landscape of apps—what we call creepware—used for interpersonal attacks. In this paper, we initiate a study of creepware using access to a dataset detailing the mobile apps installed on over 50 million Android devices. We develop a new algorithm, CreepRank, that uses the principle of guilt by association to help surface previously unknown examples of creepware, which we then characterize through a combination of quantitative and qualitative methods. We discovered apps used for harassment, impersonation, fraud, information theft, concealment, and even apps that purport to defend victims against such threats. As a result of our work, the Google Play Store has already removed hundreds of apps for policy violations. More broadly, our findings and techniques improve understanding of the creepware ecosystem, and will inform future efforts that aim to mitigate interpersonal attacks.