상세정보
학술지
A Novel Anomaly-Network Intrusion Detection System Using ABC Algorithms
Cited 15 time in 
Download 1 time
Share 
Download 1 time
Share
- 저자
- 배창석, Wei-Chang Yeh, Mohd Afizi Mohd Shukran, Yuk Ying Chung, Tsung-Jung Hsieh
- 발행일
- 201212
- 출처
- International Journal of Innovative Computing, Information and Control, v.8 no.12, pp.8231-8248
- ISSN
- 1349-4198
- 출판사
- IJICIC
- 협약과제
- 11SC1700, 인간 교감 신개념 UI 기반 인터랙션 기술, 손승원
- 초록
- Network Intrusion Detection Systems (NIDSs) are increasingly in demand today as the widespread of networked machines and Internet technologies emerge rapidly. As a result, many unauthorized activities by external and internal attackers within organizations need to be detected in recent years. Thus, it is crucial that organizations should have the capability to detect these unlawful activities so that the integrity of organizational information can be protected. In previous research, NIDSs have been approached by various machine learning techniques. From our knowledge, it is first time applying the Artificial Bee colony (ABC) to solve the intrusion detection problems. In this paper, a new network intrusion system based on ABC searching algorithm has been proposed and implemented. The performance of the proposed Anomaly-based NIDS (A-NIDS) using ABC algorithm (called A-NIDS-ABC for short) has been tested using KDD-99 datasets developed by MIT Lincoln Labs. We have also compared the proposed A-NIDS-ABC with other five traditional classification algorithms. The experimental results showed that the proposed method can outperform other five popular benchmark classifiers and is suitable for the network intrusion detection. © 2012.
- KSP 제안 키워드
- ABC algorithm, Anomaly-based NIDS, Artificial bee colony, Classification algorithm, Intrusion Detection Systems(IDSs), Intrusion detection system(IDS), Intrusion system, Machine Learning technique(MLT), Searching algorithm, external and internal, network intrusion detection system