Elimination of policy conflict to improve the PDP evaluation performance

Fan, Daidu; Zhang, Liyong

doi:10.1016/j.jnca.2016.12.001

Cited by 20 publications

(14 citation statements)

References 19 publications

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“…However, they do not formulate a general method of refinement. Moreover, Deng and Zhang ( 2015 ) argue that conflicts can be eliminated by constructing a special data structure called resource index tree.…”

Section: Related Work and Related Notationsmentioning

confidence: 99%

“…Ngo et al ( 2015 ) propose an XACML logical model and a decision diagram by the data interval partition aggregation. We have done some research about it in Deng and Zhang ( 2015 ); Deng et al ( 2016 ). In addition, Deng et al ( 2019a ) propose the XACML policy evaluation engine XDPMOE based on bitmap storage and HashMap to improve the evaluation efficiency of the XACML policy.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Improvement on PDP Evaluation Performance Based on Neural Networks and SGDK-means Algorithm

Fan

Song

et al. 2021

Soft Comput

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Section: Related Work and Related Notationsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Improvement on PDP Evaluation Performance Based on Neural Networks and SGDK-means Algorithm

Fan

Song

et al. 2021

Soft Comput

Self Cite

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“…To detect conflicts between rules in a given policy and evaluate access request, Fan Deng et al [20] presented an engine called f orm conf lict. In detail, it detects two types of conflict to be resolved: (i) common resource conflict; and (ii) dependent resource conflict.…”

Section: B Policy Conflict Resolutionmentioning

confidence: 99%

Towards a Fine-Grained Access Control Mechanism for Privacy Protection and Policy Conflict Resolution

Son¹,

Chen²

2019

ijacsa

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Access control is a security technique that specifies access rights to resources in a computing environment. As information systems nowadays become more complex, it plays an important role in authenticating and authorizing users and preventing an attacker from targeting sensitive information. However, no proper consideration has been fully investigated so far in privacy protection. While many studies have acknowledged this issue, recent studies have not provided a fine-grained access control system for data privacy protection. As the data set becomes larger, we have to confront more privacy challenges. For example, the access control mechanism must be able to guarantee fine-grained access control, privacy protection, conflicts and redundancies between rules of the same policy or between different policies. In this paper, we propose a comprehensive framework for enforcing attribute-based security policies stored in the JSON document together with the feature of data privacy protection and incorporates a policy structure based on the prioritization of functions to resolve conflicts at a fine-grained level called "Privacy aware access control model for policy conflict resolution". We also use Polish notation for modeling conditional expressions which are the combination of subject, action, resource, and environment attributes so that privacy policies are flexible, dynamic and fine-grained. Experiments are carried out to two aspects (i) illustrate the relationship between the processing time for access decision and the complexity of policies; (ii) illustrate the relationship between the processing time for the traditional approach (single policy, multi-policy without priority) and our approach (multi-policy with priority). Experimental results show that the evaluation performance satisfies the privacy requirements defined by the user.

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“…There are already some efficient algorithms to statically detect conflicts in access control policies [13,14,15,16,17,18]. The method is generally to look for conflict in all combinations of a number of rules (often only two rules).…”

Section: Introductionmentioning

confidence: 99%

Efficiently Characterizing the Undefined Requests of a Rule-Based System

Cheng

Royer

Tisi

2018

Lecture Notes in Computer Science

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Rule-based systems are used to define complex policies in several contexts, because of the flexibility and modularity they provide. This is especially critical for security systems, which may require to compose evolving policies for privacy, accountability, access control, etc. The inclusion of conflicting rules in complex policies, results in the inability of the system to unambiguously answer to certain requests, with possibly unpredictable effects. The static identification of these undefined requests is particularly challenging for unconstrained rule-based systems, including quantifiers, computations and chaining of rules. In this paper we introduce a static method to precisely characterize the set of all undefined requests for a given unconstrained rule-based system, providing the user with a global view of the rule conflicts. We propose an enumerative approach, made usable in practice by two key performance optimizations: a finer classification of the rules and the resort of the topological sorting. We demonstrate its application on a well-known policy with more than fifty rules.

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Elimination of policy conflict to improve the PDP evaluation performance

Cited by 20 publications

References 19 publications

Improvement on PDP Evaluation Performance Based on Neural Networks and SGDK-means Algorithm

Improvement on PDP Evaluation Performance Based on Neural Networks and SGDK-means Algorithm

Towards a Fine-Grained Access Control Mechanism for Privacy Protection and Policy Conflict Resolution

Efficiently Characterizing the Undefined Requests of a Rule-Based System

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