Microsoft is buckling down to keep scammers away from its Voice-over-IP and instant messaging service Skype. Microsoft Research has made use of a sophisticated machine language to weed out fraudulent users.
The test was carried out on a group of 200,000 users which consisted of an equal number of legitimate and fake customers. After four months of activity, the team scored 68-percent success at detecting fake accounts. This has also resulted in the reduction of active fraudulent users by a factor of 2.3 over the course of the last 10 months.
“We investigate possible improvements in online fraud detection based on information about users and their interactions. We develop, apply, and evaluate our methods in the context of Skype. Specifically, in Skype, we aim to provide tools that identify fraudsters that have eluded the first line of detection systems and have been active for months. Our approach to automation is based on machine learning methods. We rely on a variety of features present in the data, including static user profiles (e.g., age), dynamic product usage (e.g., time series of calls), local social behavior (addition/deletion of friends), and global social features (e.g., PageRank). We introduce new techniques for pre-processing the dynamic (time series) features and fusing them with social features. We provide a thorough analysis of the usefulness of the different categories of features and of the effectiveness of our new techniques.”, reads the abstract of the project.
While this test was highly concentrated on Skype, the team anticipates that these techniques will work on other platforms as well. “we chose not to rely on Skype’s informal intent in those definitions, nor on Skype’s software … in order to develop robust, self-contained methods.”. You can grab the research paper from the download link below.
