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Detection Techniques against DDoS attacks: A Comprehensive Review
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 96 - Number 5 |
| Year of Publication: 2014 |
| Authors: Shaveta Gupta, Dinesh Grover, Abhinav Bhandari |
10.5120/16794-6390
|
Shaveta Gupta, Dinesh Grover, Abhinav Bhandari . Detection Techniques against DDoS attacks: A Comprehensive Review. International Journal of Computer Applications. 96, 5 ( June 2014), 49-57. DOI=10.5120/16794-6390
Abstract
Distributed Denial of Service (DDoS) attacks have also become a problem for users of computer systems connected to the Internet. So defending internet from these attacks has become the need of the hour. There are three solutions against DDoS attacks: Prevention, Detection and Reaction. Detection is one of the key steps in defending against DoS/ DDoS attacks. There are some challenges that has to face while adopting any of the detection technique. If attacks can be detected close to attack sources, attack traffic can be filtered before it wastes any network bandwidth. A good detection technique should have short detection time, low false positive rate, low false negative rate but high normal packet survival ratio. This review paper provides the comparative analysis of various detection techniques with their corresponding advantages and disadvantages.
References
- Stephen Specht, Ruby Lee," Taxonomies of distributed Denial of Service Networks Attacks, Tools and Countermeasures:Technical Report". CE-L2003-03 May 16,2003.
- Rajesh Kumar,"An Introduction to DDoS – Distributed Denial of Service attack" March 15,2011.
- Tao Peng, Christopher Leckie and Kotagiri Ramamohanarao,"Survey of Network-Based Defence Mechanisms Countering the DoS and DdoS Problems" ACM Computing Surveys, Vol. 39, No. 1, Article 3, Publication date: April 2007.
- Rocky K. C. Chang, The Hong Kong Polytechnic University,"Defending against Flooding-Based Distributed Denial-of-Service Attacks. ",Volume 40 Issue 10,Oct 2002.
- Amit Kulkarni and Stephen Bush,"Detecting Distributed Denial-of-Service Attacks Using Kolmogorav Complexity Metrics. " 2001;http://citeseerx. ist. psu. edu/viewdoc/summary?doi=10. 1. 1. 16. 5589
- Sandeep kumar,"A Pattern matching model for misuse intrusion detection. "Proceedings of the 17th National Computer Security Conference,1994.
- James Cannady,"Artificial Neural Network for MisuseDetection. "1998;http://webpages. cs. luc. edu/~pld/courses/447/sum08/class9/cannady. 1998. artificial_neural_networks_for_misuse_detection. pdf
- Animesh Patcha and Jung-Min Park," An overview of anamoly detection techniques:Existing solutions and latest technological trends. "Volume 51, Issue 12, 22 August 2007, Pages 3448–3470
- Victoria J. Hodge and Jim austin,"A survey of outlier dtection methodologies. "Artificial intelligence Review 22:85-126,2004.
- Keunsoo Lee, Juhyun Kim, Ki Hoon Kwon,Younggoo Han, Sehun Kim,"DDos attack detection method using cluster analysis",Volume 34 Issue 3, April 2008, Pages 1659–1665
- Saman Taghavi Zargar, Member, IEEE, James Joshi, Member, IEEE, and David Tipper, Senior Member, IEEE,"A survey of defence mechanisms against distributed denial of service flooding attacks"IEEE Communications Survey & Tutorials accepted for publication 11 Feb,2013.
- Mohammed Alenezi,Martin J Reed,"Methodologies for detecting DoS/DDoS attacks against network servers. "ICSNC 2012 : The Seventh International Conference on Systems and Networks Communication
- Yufeng Kou, Chang-Tien Lu, Sirirat Sinvongwattana,Yo-Ping Huang,"Survey of fraud detection techniques". Proceedings of the 2004 IEEE International Conference on Networking, Sensing & Control Taipei, Taiwan, March 21-23, 2004
- Monowar H. Bhuyan,H. J. Kashyap,D. K. Bhattacharya and J. K. Kalita"Detecting Distributed Denial of Service Attacks:Methods,Tools and Future Directions"www. cs. uccs. edu/~jkalita/papers/2013/BhuyanMonowarComputerJournal 2013
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