Smart Approach for Botnet Detection Based on Network Traffic Analysis

Today, botnets are the most common threat on Internet and used as main attack vector against individuals businesses. Cybercriminals have exploited for many illegal activities, including click fraud, DDOS attacks, spam production. In this article, we suggest a method identifying behavior of data traffic using machine learning classifiers genetic algorithm to detect botnet activities. By categorizing based time slots, investigate viability detecting without seeing whole network flow. We also evaluate efficacy two well-known classification methods with reference data. demonstrate experimentally, existing datasets, that it is possible activities high precision.