Efficient Negative Selection Algorithm and its Analysis
Artificial immune algorithm has been used to many fields researching such as intrusion detection system,information retrieval system and data mining system.Negative selection algorithm is the typical method for artificial immune algorithm.But it is not efficient because that checking antigen repeated using same sub-string,finding detector method is slow and comparing detector of antigen by bit need large consumption.By analyzing antigen,detector and matching rules of them,this paper presents conversion algorithm to convert self to some self-numbers,convert detector to detector-numbers and convert antigen to some antigen-numbers.Then giving the red-black tree based negative selection algorithm to index self-number and detector-number.It can avoid checking antigen and obtaining sub-string repeatedly.Using efficient negative selection algorithm and negative selection algorithm to realize prototype,testing and comparing their performance,the result proves efficient negative selection algorithm can reduce the number of comparing detector of antigen,and increase efficient of negative selection algorithm.