iReTADS: An Intelligent Real-Time Anomaly Detection System for Cloud Communications Using Temporal Data Summarization and Neural Network

A new distributed environment at less financial expenditure on communication over the Internet is presented by cloud computing. In recent times, increased number of users has made network traffic monitoring a difficult task. Although and security problems are rising in parallel, there need to develop system for providing reducing traffic. method, iReTADS, proposed reduce using data summarization technique also provide through an effective real-time neural network. plays significant role mining, still no real methods present assist summary evaluation. Thus, it serious endeavor four metrics with temporal features such as conciseness, information loss, interestingness, intelligibility. addition, metric time introduced summarization. Finally, known Modified Synergetic Neural Network (MSNN) summarized datasets detecting anomaly-behaved nodes introduced. Experimental results reveal that iReTADS can effectively monitor detect anomalies. It may further drive studies controlling outbreaks pandemics while studying medical datasets, which smart healthy cities.