  Authorization and access control play an essential role in protecting
sensitive information from malicious users. The system is based on security
policies to determine if an access request is allowed. However, of late, the
growing popularity of big data has created a new challenge which the security
policy management is facing with such as dynamic and update policies in run
time. Applications of dynamic policies have brought many benefits to modern
domains. To the best of our knowledge, there are no previous studies focusing
on solving authorization problems in the dynamic policy environments. In this
article, we focus on analyzing and classifying when an update policy occurs,
and provide a pragmatic solution for such dynamic policies. The contribution of
this work is twofold: a novel solution for managing the policy changes even
when the access request has been granted, and an XACML-based implementation to
empirically evaluate the proposed solution. The experimental results show the
comparison between the newly introduced XACs-DyPol framework with Balana (an
open source framework supporting XACML 3.0). The datasets are XACML 3.0-based
policies, including three samples of real-world policy sets. According to the
comparison results, our XACs-DyPol framework performs better than Balana in
terms of all updates in dynamic security policy cases. Specially, our proposed
solution outperforms by an order of magnitude when the policy structure
includes complex policy sets, policies, and rules or some complicated
comparison expression which contains higher than function and less than
function.
