IMPROVE - Identifying Minimal PROfile VEctors for Similarity Based Access Control

There is ample evidence which shows that social media users struggle to make appropriate access control decisions while disclosing their information and smarter mechanisms are needed to assist them. Using profile information to ascertain similarity between users and provide suggestions to them during the process of making access control decisions has been put forth as possible solution to this problem. This paper presents an empirical study aimed at identifying the minimal subset of attributes which are most suitable for being used to create profile vectors for the purpose of predicting access control decisions. We begin with an exhaustive list of 30 profile attributes and identify a subset of 2 profile attributes which are shown to be sufficient in obtaining similarity between profiles and predicting access control decisions with the same accuracy as previous models. We demonstrate that using this pair of attributes will help mitigate the challenges encountered by similarity based access control mechanisms.