Title :
Modified Ant Miner for Intrusion Detection
Author :
Agravat, Deven ; Vaishnav, Urmi ; Swadas, P.B.
Author_Institution :
Dept. of Inf. Technol., G H Patel Coll. of Eng. & Technol., Vallabh Vidyanagar, India
Abstract :
This paper proposes Modified Ant Miner algorithm for intrusion detection. Ant Miner and its descendant have produced good result on many classification problems. Data mining technique is still relatively unexplored area for intrusion detection. In this paper, modification has been suggested in basic ant miner algorithm to improve accuracy and training time of algorithm. The KDD Cup 99 intrusion data set is used to evaluate our proposed algorithm and the result obtained from this experiment is compared with that of Support Vector Machine. It has been found that our proposed algorithm is more effective in case of DOS, U2R, and R2L type of attacks.
Keywords :
data mining; pattern classification; security of data; support vector machines; DOS; KDD Cup 99 intrusion data set; R2L; U2R; classification problems; data mining technique; intrusion detection; modified ant miner algorithm; support vector machine; Computer networks; Data mining; Educational institutions; IP networks; Information technology; Intrusion detection; Machine learning; Support vector machine classification; Support vector machines; Telecommunication traffic; Ant Miner; Intrusion Detection; Support Vector Machine;
Conference_Titel :
Machine Learning and Computing (ICMLC), 2010 Second International Conference on
Conference_Location :
Bangalore
Print_ISBN :
978-1-4244-6006-9
Electronic_ISBN :
978-1-4244-6007-6
DOI :
10.1109/ICMLC.2010.52
