IMPROVE:Identifying Minimal PROfile VEctors for similarity based access control

Misra, Gaurav and Such, Jose M. and Balogun, Hamed (2016) IMPROVE:Identifying Minimal PROfile VEctors for similarity based access control. In: 2016 IEEE Trustcom/BigDataSE/I​SPA. 2016 IEEE Trustcom/BigDataSE/I​SPA . IEEE, CHN, pp. 868-875. ISBN 9781509032068

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Abstract

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 a 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.

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Contribution in Book/Report/Proceedings
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©2016 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
ID Code:
79966
Deposited By:
Deposited On:
22 Jun 2016 13:04
Refereed?:
Yes
Published?:
Published
Last Modified:
05 Apr 2020 00:44