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Clustering software into peer groups based on its apparent functionalityallows for simple, intuitive categorization of software that can, inparticular, help identify which software uses comparatively more privilege thanis necessary to implement its functionality. Such relative comparison canimprove the security of a software ecosystem in a number of ways. For example,it can allow market operators to incentivize software developers to adhere tothe principle of least privilege, e.g., by encouraging users to usealternative, less-privileged applications for any desired functionality. Thispaper introduces software peer group analysis, a novel technique to identifyleast privilege violation and rank software based on the severity of theviolation. We show that peer group analysis is an effective tool for detectingand estimating the severity of least privilege violation. It providesintuitive, meaningful results, even across different definitions of peer groupsand security-relevant privileges. Our evaluation is based on empiricallyapplying our analysis to over a million software items, in two different onlinesoftware markets, and on a validation of our assumptions in a medium-scale userstudy.

Apples and Oranges: Detecting Least-Privilege Violators with Peer Group Analysis