Association rule mining and Genetic Algorithm(GA) for Data Mining based Intrusion Detection System: A Review Approach


Along with the transformation of technical era, the technical progression has also raised concerns near the security of web doings. These activities remain in a way or the other are tried to be cooperated by the opponent with the aim of ahead knowledge which may be someway useful for him/her. In addition, fanatics are also operating web for gratifying their merciless goals which is currently an utmost concern for security agencies. Although there are many successful attempts have been made to restrict the existence of these illegitimate people, there still is a need for an effective assertion solution. In respect to this, data mining comes out as a solution by bringing into existence a mining concept named Terrorist Network Mining. Guerrilla network mining has proved as the most feasible solution where detection and analysis of terrorists is well performed. Still there were some improvements required to this concept which was efficiently done by uniting fuzzy with genetic procedures with the interruption discovery system (IDS) resulting into significant and efficient detection process. Hence the paper discusses about how well an intrusion detection system performs when combined with fuzzy data mining (reveal patterns whose behavior is intrusive) with genetic algorithm (leads to the achievement of efficient detection of intruders).



Data Mining algorithms

Software And Hardware

• Hardware: Processor: i3 ,i5 RAM: 4GB Hard disk: 16 GB • Software: operating System : Windws2000/XP/7/8/10 Anaconda,jupyter,spyder,flask Frontend :-python Backend:- MYSQL