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WorldCist'17 - 5th World Conference on Information Systems and Technologies

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Reputation Analysis of Sensors’ Trust within Tabu Search

Reputation of the sensors are highly essential in authenticating the sensing data, especially when sensors are deployed in a hostile environment. We refer to the term “data-trust” as the degree of confidence, which can be represented as a quantitative score, based on the reputation of the sensor and the reputation is comprehended with spatial and temporal redundancy. In this paper, we have analyzed the vulnerability of the sensors subject to radical environmental conditions, and we have derived a first-order differential equation utilizing a linear combination of trust factors to quantify the trust value. The trust value is expressed as a weighted combination of two trust factors: coherent data (spatial redundancy) and periodic behavior (temporal redundancy) of the sensors. The selection of weights are automated based on a cost value suited for the operating environment, and it is treated as a combinatorial optimization problem, with an objective function to maximize the confidence of the sensor. We employed Tabu Search to find the better combination of weights to be associated with the trust factors, in order to find the positive subspace reflecting the domain of trusted sensor operations. We carried out a set of experiments with varying proportions of the selected trust factors and the experimental outcomes were analyzed in drawing boundaries of trusted domain (trust space). Our experimental results with varying malfunctioning sensor readings showed the Tabu Search reduced the solution space by 22% in comparison to the local search (Simulated Annealing) and the trust space holding the trust values greater than 50% aided in accepting the malfunctioning sensor data.


Sami Habib    
Kuwait University

PaulvannaNayaki Marimuthu    
Kuwait University


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