Zero day Cyber-attacks created potential impacts on the way information is held and protected, however one of the vital priorities for governments, agencies and organizations is to secure their network businesses, transactions and communications, simultaneously to avoid security policy and privacy violations under any circumstances. Covert Channel is used to in/ex-filtrate classified data secretly, whereas encryption is used merely to protect communication from being decoded by unauthorized access. In this paper, we propose a new Security Model to mitigate security attacks on legitimate targets misusing IPv6 vulnerabilities. The approach analyses, detects and classifies hidden communication channels through implementing an enhanced feature selection algorithm with a coherent Naive Bayesian Classifier. NBC is one of the most prominent classification algorithm defining the highest probability in data mining area. The proposed framework uses Intelligent Heuristic Algorithm (IHA) to analyse and create a novel primary training data, furthermore a modified Decision Tree C4.5 technique is suggested to classify the richest attribute presenting hidden channels in IPv6 network. The results evaluation showed better detection performance, high accuracy in True Positive Rate (TPR) and a low False Negative Rate (FNR) and a clear attribute ranking
