Collaborative Policy Administration
Collaborative Policy Administration
ABSTRACT:
Policy based management is a very effective method to protect sensitive information. However, the over claim of privileges is widespread in emerging applications, including mobile applications and social network services, because the applications’ users involved in policy administration have little knowledge of policy based management. The over claim can be leveraged by malicious applications, then lead to serious privacy leakages and financial loss. To resolve this issue, this paper proposes a novel policy administration mechanism, referred to as Collaborative Policy Administration (CPA for short), to simplify the policy administration. In CPA, a policy administrator can refer to other similar policies to set up their own policies to protect privacy and other sensitive information. This paper formally defines CPA, and proposes its enforcement framework. Furthermore, in order to obtain similar policies more effectively, which is the key step of CPA, a text mining based similarity measure method is presented. We evaluate CPA with the data of Android applications, and demonstrate that the text mining based similarity measure method is more effective in obtaining similar policies than the previous category based method
EXISTING SYSTEM:
The traditional framework of policy based management consists of four core components: PDP (Policy Decision Point), PEP (Policy Enforcement Point), PAP (Policy Administration Point) and PR (Policy Repository). A well-trained policy administrator or group will specify, verify policies in PAP, and deploy the policies in PR. After a system runs, PDP will retrieve applicable policies from PR, and make decisions. PEP takes charge of the decision, such as satisfying the request where a subject wants to open a file (authorization action), or launching a logger to record system context (obligation action). The over claim of privileges, where a not well-trained administrator assigns more privileges than those are required of a subject, is a increasingly serious problem, especially when the method of policy based management is applied to emerging application scenarios, such as mobile applications and social network services. For instance, during the process of Android application development, three roles are usually involved in the policy administration: Application Developers declare which permissions the application will request; Application Marketers verify whether the application is legitimate or not by an automatic tool; Application Users decide whether to approve the permission requests. These three roles are usually performed by those who are not well-trained in policy based management.
DISADVANTAGES OF EXISTING SYSTEM:
The marketers usually tend to allow more applications regardless of the malicious permission requests; and the application users may not know what the requested permissions mean, thus approving all requests because they are eager to use the application. The same issue exists in social network services, where a user is asked to grant access to private data to third-party applications. This challenge to policy administration is increasing serious due to the explosion of these applications.
PROPOSED SYSTEM:
This paper proposes Collaborative Policy Administration (CPA for short). The essential idea of CPA is that applications with similar functionalities shall have similar policies which will be specified and deployed. Thus, to specify or verify policies, CPA will examine policies already specified by other similar applications and perform collaborative recommendation. The degree of similarity will be calculated by predefined algorithms, which cloud be a category based algorithm and a text mining based algorithm, etc.
ADVANTAGES OF PROPOSED SYSTEM:
v Two main functions in policy administration are defined based on similarity measure methods, which will select similar policies as a refinement basis to assist administrators to design or verify their target policies.
v We propose a text mining based similarity measure method to help policy administrators to obtain similar policies.
v The framework supports two types of user interfaces, and provides functions of collaborative policy design and collaborative policy verification.
SYSTEM REQUIREMENTS:
HARDWARE REQUIREMENTS:
Ø System : Pentium IV 2.4 GHz.
Ø Hard Disk : 40 GB.
Ø Floppy Drive : 1.44 Mb.
Ø Monitor : 15 VGA Colour.
Ø Mouse : Logitech.
Ø Ram : 512 Mb.
Ø MOBILE : ANDROID
SOFTWARE REQUIREMENTS:
Ø Operating system : Windows XP.
Ø Coding Language : Java 1.7
Ø Tool Kit : Android 2.3
Ø IDE : Eclipse
REFERENCE:
Weili Han,Member, IEEE,Zheran Fang, Laurence T. Yang,Member, IEEE,Gang Pan,Member, IEEE, and Zhaohui Wu,Senior Member, IEEE “Collaborative Policy Administration” – IEEE TRANSACTIONS ON PARALLEL AND DISTRIBUTED SYSTEMS 2013
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