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BotTracer: Bot user detection using clustering method in RecDroid
- Source :
- NOMS
- Publication Year :
- 2016
- Publisher :
- IEEE, 2016.
-
Abstract
- RecDroid is a smartphone permission management system which provides users with a fine-grained real-time app permission control and a recommendation system regarding whether to grant the permission or not based on expert users' responses in the network. However, in such a system, malware owners may create multiple bot users to misguide the recommendation system by providing untruthful responses on the malicious app. Threshold-based detection method can detect malicious users which are dishonest on many apps, but it cannot detect malicious users that target on some specific apps. In this work, we present a clustering-based method called BotTracer to finding groups of bot users controlled by the same masters, which can be used to detect bot users with high reputation scores. The key part of the proposed method is to map the users into a graph based on their similarity and apply a clustering algorithm to group users together. We evaluate our method using a set of simulated users' profiles, including malicious users and regular ones. Our experimental results demonstrate high accuracy in terms of detecting malicious users. Finally, we discuss several clustering features and their impact on the clustering results.
- Subjects :
- 021110 strategic, defence & security studies
Information retrieval
business.industry
Computer science
0211 other engineering and technologies
020206 networking & telecommunications
02 engineering and technology
Permission
Recommender system
computer.software_genre
World Wide Web
Set (abstract data type)
Management system
0202 electrical engineering, electronic engineering, information engineering
Key (cryptography)
Malware
Mobile telephony
Cluster analysis
business
computer
Subjects
Details
- Database :
- OpenAIRE
- Journal :
- NOMS 2016 - 2016 IEEE/IFIP Network Operations and Management Symposium
- Accession number :
- edsair.doi...........843a6fb3670d752ae893060d2d4a55d2