Access Domain-Based Approach for Anomaly Detection and Resolution in XACML Policies

Hadj, Maryem Ait El; Benkaouz, Yahya; Khoumsi, Ahmed; Erradi, Mohammed

doi:10.1007/978-3-319-76354-5_27

Cited by 1 publication

(3 citation statements)

References 7 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Consider a policy P with 3 rules. Each rule has two attributes att 1 and att 2 , such that Total complexity (phase 1 + phase 2): Since the complexity of phase 1 is greater than the complexity of phase 2, the former is the order of the total complexity : O(n × d 2 (max(d, n)). We assume that attributes are not constant parameters, i.e.…”

Section: Complexity Of Algorithmmentioning

confidence: 99%

“…To make the suggested method scalable with great policies (i.e., policies with a huge number of rules), we decompose the policy into several clusters of rules, and then the method is applied to each cluster. A preliminary version of this work is given in [2] which presents succinctly a method to detect and resolve anomalies. Compared to [2], our contributions are as follows:…”

Section: Introductionmentioning

confidence: 99%

“…A preliminary version of this work is given in [2] which presents succinctly a method to detect and resolve anomalies. Compared to [2], our contributions are as follows:…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Formal Approach to Detect and Resolve Anomalies while Clustering ABAC Policies

Hadj¹,

Khoumsi²,

Benkaouz³

et al. 2018

ICST Transactions on Security and Safety

Self Cite

View full text Add to dashboard Cite

In big data environments with big number of users and high volume of data, we need to manage the corresponding huge number of security policies. Using Attribute-Based Access Control (ABAC) model to ensure access control might become complex and hard to manage. Moreover, ABAC policies may be aggregated from multiple parties. Therefore, they may contain several anomalies such as conflicts and redundancies, resulting in safety and availability problems. Several policy analysis and design methods have been proposed. However, most of these methods do not preserve the original policy semantics. In this paper, we present an ABAC anomaly detection and resolution method based on the access domain concept, while preserving the policy semantics. To make the suggested method scalable for large policies, we decompose the policy into clusters of rules, then the method is applied to each cluster. We prove correctness of the method and evaluate its computational complexity. Experimental results are given and discussed.

show abstract

Section: Complexity Of Algorithmmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%