A Novel Immunity Inspired Approach for Anomaly Detection

Artificial Immune System (AIS) over the years has caught attention of researchers of various domains for complex problem solving. AIS model the procedure and methodologies of Biological Immune System (BIS) which protects the body from diverse attacks and different challenges. Scientists over the years are amazed with the appealing features of BIS that can be exploited. The most significant of them is its ability to distinguish self and non-self. This theory forms the basis of Negative Selection Algorithm (NSA) in AIS. NSA is competent for anomaly detection problems. From this perspective this research paper presents a Novel Immunity inspired approach for Anomaly Detection (NIIAD) with the feature of fine tuning. The main intention of adopting finetuning is to covering more self region and identifying non self region proficiently. Experimental results reflects high detection ratio with less false alarm and low overhead