An Efficient and Effective Immune Based Classifier

Abstract

Problem statement: Artificial Immune Recognition System (AIRS) is most popular and effective immune inspired classifier. Resource competition is one stage of AIRS. Resource competition is done based on the number of allocated resources. AIRS uses a linear method to allocate resources. The linear resource allocation increases the training time of classifier. Approach: In this study, a new nonlinear resource allocation method is proposed to make AIRS more efficient. New algorithm, AIRS with proposed nonlinear method, is tested on benchmark datasets from UCI machine learning repository. Results: Based on the results of experiments, using proposed nonlinear resource allocation method decreases the training time and number of memory cells and doesn't reduce the accuracy of AIRS. Conclusion: The proposed classifier is an efficient and effective classifier.

A Novel Local Network Intrusion Detection System Based on Support Vector Machine

“…For this a policy has to be defined, when and how alerts and logging messages are processed so it can respond to the alarm and take the appropriate action, for instance by ousting the intruder, calling the proper external authorities and so on. Intrusion systems are noted for high false alarm rates and considerable research effort is still concentrated on finding effective intrusion, nonintrusion discriminates (Golzari et al, 2001;Wahid and Zulkarnain, 2011). It was suggested by Lundin and Jonsson (2002) that techniques should be combined in order to correct some of these problems.…”

“…In a misuse based intrusion detection system , intrusions are detected by looking for activities that correspond to know signatures of intrusions or vulnerabilities (Golzari et al, 2001). While an anomaly based intrusion detection system detect intrusions by searching for abnormal network traffic.…”

“…Intrusion detection is the process of monitoring the events occurring in a computer system or network and analyzing them for sign of intrusion. A Network Intrusion Detection System (NIDS) is a system that emits alerts commensurate with abnormal or unauthorized events in the network (Golzari et al, 2001). Snort (Wahid and Zulkarnain, 2011) as a popular NIDS is widely used to audit network packets and compare them with a database of known attack signatures (Ektefa et al, 2011;Lundin and Jonsson, 2002;Sodiya et al, 2004).…”

Evaluation of Artificial Immune System with Artificial Neural Network for Predicting Bombay Stock Exchange Trends

“…A human immune system consists of B-cells that recognize antigens which entering from external environment. B-cells are a type of immune cell, depending on protein molecules called antibody (Golzari et al, 2011). A B-cell identifies the antigen when its antibodies appear into contact with an antigen of complementary shape (Do et al, 2009).…”

“…In artificial Immune recognition system there is need to allocate resources in such way that only limited memory cells should be used but without reducing the accuracy of AIRS (Golzari et al, 2011). The main objective in scanning of data base to mine the spatially co-located moving objects is to minimize the computation cost and memory usage (Manikandan and Srinivasan, 2013)".…”

Robust Memory Management Using Real Time Concepts

“…In artificial Immune recognition system there is need to allocate resources in such way that only limited memory cells should be used but without reducing the accuracy of AIRS (Golzari et al, 2011). The main objective in scanning of data base to mine the spatially co-located moving objects is to minimize the computation cost and memory usage (Manikandan and Srinivasan, 2013)".…”