Functional Dependency and Performance Strategy in Deception Detection using Fuzziness and Uncertainty with Underlying Randomness Syndromes

Deception detection is an essential strategy for the efficient and secure communication. The implementation of soft computing techniques such as fuzzy logic, uncertainty, randomness, neural networks and genetic algorithm plays a vital role in identifying the deception in an information sharing system. The combined implementation of fuzziness, randomness and uncertainty provides the maximum output than compare it with the individual implementations is an obvious result. In this study, researchers analyze the combined performance and dependency computation for the combined application of randomness, fuzziness and uncertainty towards deception detection. Researchers considers two different domains for the proposed model and the final results are discussed.