A CNN Based Anomaly Detection System for Real Time Fog Based Application
G K Nischitha, S Manishankar, Phani Deshpande, A Anoop · 2021 Asian Conference on Innovation in Technology (ASIANCON) · 2021
The rapid growth in technology and everything becoming smart the adaptability of intelligent technologies in our daily life has taken a prominent place. In the view to maintain and stock the data cloud is being used. To condense the issues like latency and energy consumption fog computing has been introduced. However many techniques are present to find the anomaly present in the data but deeper inside no works are found to detect anomaly of in network. In order to provide system that identifies the anomaly present in network while transmitting data at fog level and to aggregate those anomaly if found using a Machine learning technique is proposed in the paper. With a fog based eco system built, further taking up a neural network algorithm that is convolution neural network a system for detecting anomaly and aggregating data has been anticipated in the paper.