A Review on Machine Learning Models for Channel Estimation and Security of Software Defined Networks

It can be concluded from the previous discussions that security awareness in spectrum assignment is a critical aspect for cognitive IoT networks catering to defence and military applications or situations which deal with confidential and classified data. Various approaches pertaining to security in cognitive networks have been presented with their salient features. The probability of false alarm has also been investigated for ideal and practical channel conditions. It has been shown that hardware constraints poses a serous challenge in real time critical cognitive IoT networks. The paper presents the conventional and contemporary techniques to mitigate the issue of cyber attacks pertaining to such hardware constrained cognitive IoT Networks.

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