@inproceedings{b9ff77f6ae654b73ab764fa8165a5605,
title = "An autonomous model to enforce security policies based on user's behavior",
abstract = "To protect user's information, computer systems utilize access control models. These models are supported by a set of policies defined by security administrators in the environment where the organization is active. In previous studies it has been shown that building a user interface that dynamically changes with the security policies defined for each user is a cumbersome task. This work is a further expansion of an improved dynamic model that adjusts users' security policies based on the level of trust that they hold. We use machine learning beside the trust manager component that helps the system to adapt itself, learn from the user's behavior and recognize access patterns based on the similar access requests and not only limit the illegitimate access, but also predict and prevent potential malicious and questionable accesses.",
keywords = "Access Policies, Database, Dynamic Model, Machine Learning, Security Policies, Trust Model",
author = "Kambiz Ghazinour and Mehdi Ghayoumi",
note = "Publisher Copyright: {\textcopyright} 2015 IEEE.; 14th IEEE/ACIS International Conference on Computer and Information Science, ICIS 2015 ; Conference date: 28-06-2015 Through 01-07-2015",
year = "2015",
month = jul,
day = "24",
doi = "10.1109/ICIS.2015.7166576",
language = "English",
series = "2015 IEEE/ACIS 14th International Conference on Computer and Information Science, ICIS 2015 - Proceedings",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "95--99",
editor = "Takayuki Ito and Yanggon Kim and Naoki Fukuta",
booktitle = "2015 IEEE/ACIS 14th International Conference on Computer and Information Science, ICIS 2015 - Proceedings",
}