A Computational Dynamic Trust Model for User Authorization

 Abstract

Development of authorization mechanisms for secure information access by a large community of users in an open environment is an important problem in the ever-growing Internet world. In this paper we propose a computational dynamic trust model for user authorization, rooted in findings from social science. Unlike most existing computational trust models, this model distinguishes trusting belief in integrity from that in competence in different contexts and accounts for subjectivity in the evaluation of a particular trustee by different trusters. Simulation studies were conducted to compare the performance of the proposed integrity belief model with other trust models from the literature for different user behavior patterns. Experiments show that the proposed model achieves higher performance than other models especially in predicting the behavior of unstable users.

Aim

The main aim is to compute dynamic trust model for user authorization to secure information access by a large community of users in an open environment in the ever-growing Internet world.

Scope:

The scope is to enable automated trust management that mimics trusting behaviors, trusting belief in integrity from that in competence

Existing System

Social trust model defines five conceptual trust types:

1) trusting behavior,

2) trusting intention,

3) trusting belief,

4) institution-based trust,

5) disposition to trust.

 Trusting behavior is an action that increases a truster's risk or makes the truster vulnerable to the trustee.

Trusting intention indicates that a truster is willing to engage in trusting behaviors with the trustee.

Trusting belief is a truster's subjective belief in the fact that a trustee has attributes beneficial to the truster. The following are the four attributes used most often: Competence, Benevolence, Integrity, Predictability

Institution-based trust is the belief that proper structural conditions are in place to enhance the probability of achieving a successful outcome.

Two subtypes of institution- based trust are:

 1. Structural assurance       2. Situational normality.

 Disposition to trust characterizes a truster's general propensity to depend on others across a broad spectrum of situations. Two subtypes of disposition to trust are: 1. Faith in human 2. Trusting stance

Trust intention and trusting belief are situation and trustee specific. Institution-based trust is situation specific. Disposition to trust is independent of situation and trustee. Trusting belief positively relates to trusting intention, which in turn results in the trusting behavior. Institution- based trust positively affects trusting belief and trusting intention. Structural assurance is more related to trusting intention while situational normality affects both. Disposition to trust positively influences institution-based trust, trusting belief and trusting intention. Faith in humanity impacts trusting belief. Trusting stance influences trusting intention.

The existing approaches are to extract reputation from the social network topology that encodes reputation information, for social networks, based on the concept of feedback centrality, for access control in P2P networks, based on the assumption of transitivity of trust in social networks, where a simple mathematical model based on fuzzy set membership is used to calculate the trustworthiness of each node in a trust graph symbolizing interactions between network nodes, for nodes in a P2P network, based on the history of interactions between nodes.

Disadvantages

Although the existing approaches integrate context into trust computation, their application is limited to specific domains.

Proposed System

In this paper we propose a computational dynamic trust model for user authorization, rooted in findings from social science. This model distinguishes trusting belief in integrity from that in competence in different contexts and accounts for subjectivity in the evaluation of a particular trustee by different trusters. The proposed model accounts for different types of trust. Specifically, it distinguishes trusting belief in integrity from that in competence. The model takes into account the subjectivity of trust ratings by different entities, and introduces a mechanism to eliminate the impact of subjectivity in reputation aggregation.

Advantages

The model evaluates trust separately for each property of each component of a platform.The proposed dynamic trust model enables automated trust management that mimics trusting behaviors in society, such as selecting a corporate partner, forming a coalition, or choosing negotiation protocols or strategies in e-commerce. The formalization of trust helps in designing algorithms to choose reliable resources in peer-to-peer systems, developing secure protocols for ad hoc networks and detecting deceptive agents in a virtual community. Experiments in a simulated trust environment show that the proposed integrity trust model performs better than other major trust models in predicting the behavior of users whose actions change based on certain patterns over time.

System Architecture 

SYSTEM CONFIGURATION

HARDWARE REQUIREMENTS:-

·                 Processor               -   Pentium –III

·                Speed                -    1.1 Ghz

·                RAM                 -    256 MB(min)

·                Hard Disk         -   20 GB

·                Floppy Drive    -    1.44 MB

·                Key Board                 -    Standard Windows Keyboard

·                Mouse               -    Two or Three Button Mouse

·                Monitor             -    SVGA

SOFTWARE REQUIREMENTS:-

·                Operating System              : Windows  7                                       

·                Front End                  : JSP AND SERVLET

·                Database                  : MYSQL

·                Tool                           :NETBEANS

References

Bhargava, B, Yi Lu, Angin, P. “A COMPUTATIONAL DYNAMIC TRUST MODEL FOR USER AUTHORIZATION” Dependable and Secure Computing, IEEE Transactions on  (Volume:12 ,  Issue: 1 ) February 2014.