The week's pick
Random Articles
Reseach Article
A System for Denial-of-Service Attack Detection using MCA and IDS-based on Fuzzy Logic
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 141 - Number 2 |
| Year of Publication: 2016 |
| Authors: Lalita Saini, N.Y. Suryawanshi |
10.5120/ijca2016909555
|
Lalita Saini, N.Y. Suryawanshi . A System for Denial-of-Service Attack Detection using MCA and IDS-based on Fuzzy Logic. International Journal of Computer Applications. 141, 2 ( May 2016), 26-29. DOI=10.5120/ijca2016909555
Abstract
In the networking world, a denial of service (DoS) attack is an incident in which a user is deprived of the services of a resource they would normally expect to have. Intrusion Detection System (IDS) is the tool that is able to detect occurrences of intrusion at host, the network and application in the system. One of the most common network attacks is Denial of Service (DoS) attack. In DoS attack of the computer system an individual host will send huge number of packets to one machine so it make the operating of the network and host slow. In this paper, signature of selected attacks such as Smurf, Ping-of-Death which are based on network flow is considered and Mail-Bomb. The system uses MCA based system for detection of the DoS attack. The proposed system monitors the network path to detect attacks and the results show less false negative error during monitoring of the system. Specially, signature based IDS which use fuzzy decision tree for monitoring network path observes that there are great improvements on speed of detection as well as performance of system in the organization.
References
- V. Paxson, “Bro: A System for Detecting Network Intruders in Realtime,”Computer Networks, vol. 31, pp. 2435-2463, 1999
- P. Garca-Teodoro, J. Daz-Verdejo, G. Maci-Fernndez, and E.Vzquez, “Anomaly-based Network Intrusion Detection: Techniques,Systems and Challenges,” Computers & Security, vol. 28,pp. 18-28, 2009.
- D. E. Denning, “An Intrusion-detection Model,” IEEE Transactions on Software Engineering, pp. 222-232, 1987.
- K. Lee, J. Kim, K. H. Kwon, Y. Han, and S. Kim, “DDoS attack detection method using cluster analysis,” Expert Systems with Applications, vol. 34, no. 3, pp. 1659-1665, 2008.
- A. Tajbakhsh, M. Rahmati, and A. Mirzaei, “Intrusion detection using fuzzy association rules,” Applied Soft Computing, vol. 9,no. 2, pp. 462-469, 2009.
- J. Yu, H. Lee, M.-S. Kim, and D. Park, “Traffic flooding attack detection with SNMP MIB using SVM,” Computer Communications, vol. 31, no. 17, pp. 4212-4219, 2008.
- J. Luo, and S. M. Bridges, “Mining fuzzy association rules and fuzzy frequency episodes for intrusion detection”, International Journal of Intelligent Systems, Vol. 15, No. 8, pp. 687-704, 2000.
Index Terms
Keywords