Title :
Improved Negative Selection Algorithm Based on Bloom Filter
Author :
Zhu Tieying ; Ma Zhixing ; Liu Shaojun ; Zhou Zhiguo
Author_Institution :
Dept. Sch. of Comput., Northeast Normal Univ., Changchun, China
Abstract :
Negative selection algorithm is a prosing method in anomaly detection. How to improve complexity of the detector generation and speedup the detection efficiency is an open issue. The paper put forward an improved negative selection algorithm based on bloom filter. It reduced the overhead of detector generation and significantly cut down the matching scale. The related experiments proved the effectiveness of the improved algorithm.
Keywords :
security of data; anomaly detection; bloom filter; improved negative selection algorithm; intrusion detection; prosing method; Artificial immune systems; Data mining; Detectors; Filters; Hidden Markov models; Intrusion detection; Machine learning; Machine learning algorithms; Redundancy; Robustness;
Conference_Titel :
E-Business and Information System Security, 2009. EBISS '09. International Conference on
Conference_Location :
Wuhan
Print_ISBN :
978-1-4244-2909-7
Electronic_ISBN :
978-1-4244-2910-3
DOI :
10.1109/EBISS.2009.5137999
