Artificial Immune Recognition System-Based Classification Technique

Nowadays, data mining methods are being applied in the field of knowledge generation, which helps in decision making and intersects many disciplines of computer science such as artificial intelligence, database, statistics, visualization, and high-performance parallel computing. An artificial immune system has a set of algorithm inspired by biological immune system. This algorithm supports machine learning, and they are designed to solve difficult problems such as intrusion detection and prevention, data clustering, classification, and exploration. The proposed method focuses on executing a supervised learning algorithm AIRS, i.e., artificial immune recognition system of AIS for classification. AIRS exhibits characteristics as self-regulation, performance empirical, and parameter stability.

[1]  Fernando José Von Zuben,et al.  An Evolutionary Immune Network for Data Clustering , 2000, SBRN.

[2]  Vivek Tiwari,et al.  Association rule mining: A graph based approach for mining frequent itemsets , 2010, 2010 International Conference on Networking and Information Technology.

[3]  Wei Wang,et al.  Improved pattern recognition with complex artificial immune system , 2009, Soft Comput..

[4]  M. S. Prasasd Babu,et al.  Artificial immune recognition systems in medical diagnosis , 2015, 2015 6th IEEE International Conference on Software Engineering and Service Science (ICSESS).

[5]  Alan S. Perelson,et al.  Self-nonself discrimination in a computer , 1994, Proceedings of 1994 IEEE Computer Society Symposium on Research in Security and Privacy.

[6]  J Timmis,et al.  An artificial immune system for data analysis. , 2000, Bio Systems.

[7]  Dipankar Dasgupta,et al.  Immunological Computation: Theory and Applications , 2008 .

[8]  Zhou Ji,et al.  Artificial immune system (AIS) research in the last five years , 2003, The 2003 Congress on Evolutionary Computation, 2003. CEC '03..

[9]  Gregg H. Gunsch,et al.  Novel steganography detection using an artificial immune system approach , 2003, The 2003 Congress on Evolutionary Computation, 2003. CEC '03..

[10]  Raj T. Jitha,et al.  A survey paper on various reversible data hiding techniques in encrypted images , 2015, 2015 IEEE International Advance Computing Conference (IACC).