Volume 11 Number 6 (Jun. 2016)
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JSW 2016 Vol.11(6): 577-588 ISSN: 1796-217X
doi: 10.17706/jsw.11.6.577-588

A Predictable Information Security Based Context Aware Trust Model for Organization Management: A Statistical Analysis

Vinod Duraivelu1*, Chandrasekaran Subramaniam2
1Department of Computer Science and Engineering, Sathyabama University, Chennai, 600 127, Tamil Nadu, India.
2Department of Computer Science and Engineering, Sri Ranganathar institute of engineering and technology, Coimbatore, Tamil Nadu, India.


Abstract—The objective of the work is to propose a Predictable Context Aware Trust (PCAT) model for achieving organisation information security in the presence of suspicious entities and authorities. The properties of the PCAT model are studied including the suspicion stack pertaining to the members in different contexts. A reputation score is rewarded based on the contexts in which the information exchange is done. The proposed information trust model encompasses the trust level of the members, degree of suspicion in the information, the levels of privacy, reputation values of the trustees and their trust relationships to predict organization security. An airway passenger guidance system is taken up for statistical analysis. A conceptual and hierarchical trust pyramid is considered at different context levels and the formal implications are derived using context sensitive standard deontic logic. The formal specifications of a passport checking sub system are given in Temporal Logic of Actions (TLA+) which uses certificate authorities and trustees to evaluate passengers by assigning suspicious values.

Index Terms—Trust value, suspicion stack, context aware, standard deontic logic, reputation.

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Cite: Vinod Duraivelu, Chandrasekaran Subramaniam, "A Predictable Information Security Based Context Aware Trust Model for Organization Management: A Statistical Analysis," Journal of Software vol. 11, no. 6, pp. 577-588, 2016.

General Information

ISSN: 1796-217X (Online)
Frequency: Monthly (2006-2019); Bimonthly (Since 2020)
Editor-in-Chief: Prof. Antanas Verikas
Executive Editor: Ms. Yoyo Y. Zhou
Abstracting/ Indexing: DBLP, EBSCO, Google Scholar, ProQuest, INSPEC, ULRICH's Periodicals Directory, WorldCat, etc
E-mail: jsw@iap.org
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