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With the explosive growth of the internet, XACML policies have grown rapidly in size and complexity, and the efficiency of ABAC decision-making is unable to meet people's increasing demands, so this paper serves to solve this problem by providing a model based on an ACO algorithm. The model first divides the XACML policy into different classifications by using an ACO algorithm, then searches for related policies by calculating the Euclidean Distance with the request attribute values and XACML policy center attribute values. This approach transforms the policy evaluation into a numerical calculation. To evaluate the efficiency and the effectiveness of these methods, the paper conducts two sets of tests. The first results shows that the classification effect of ACO algorithms is better than K-means; and the second results shows that the Euclidean Distance method is more efficient than the execution vectors used by Said Marouf, et al. to search for related policies.

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Browsers have become the de-facto platform for users and their online presence. They have also become a rich environment for 3rd party extensions that enrich the user browsing experience by extending upon the browser's functionalities. Protecting user privacy against malicious or vulnerable extensions is an important task performed by modern browser platforms such as Google Chrome and Safari. To do so, these platforms adopt a per-extension permission model, where each extension is given a set of permissions based on its requirements. These models suffer from coarse-grained access controls and insufficient user awareness. In this paper we implement a runtime framework as a browser extension called REM. REM monitors the accesses made by 3rd party Chrome extensions, informs users of the accesses, and allows them to customize the permissions given to extensions. The custom permission settings are enforced by the framework at runtime. We evaluated our framework on popular Chrome extensions & were successful in monitoring and controlling their accesses with little overhead. We also conducted a user study to evaluate the effectiveness of REM compared to current standard methods.