Deep Seated Neural Network Learner Model for Trust Recommendation
Keywords:
Pervasive Computing, Trust Recommendation, Machine learning, Deep neural network, OptimizationAbstract
Recent and cutting-edge paradigms now used in the field of computers is pervasive computing. In comparison to traditional computer environments, its capacity to distribute computational services within settings where people live, work, or socialise makes problems like privacy, trust, and identification more difficult. One of the main issues with pervasive computing is the breach of security and privacy caused by malicious nodes. This study presents the new deep seated neural network leaner which recommends the trustworthy and unworthy transaction context in pervasive computing environment. Several models such as gaussian naive bayes, random forest, extra tree classifier, passive aggressive classifier, support vector machine learning algorithms are built. The proposed model out performs better compare to other machine learning models.
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