Two Layer Defending Mechanism against DDoS Attacks
Journal: The International Arab Journal of Information Technology (Vol.12, No. 4)Publication Date: 2015-07-01
Authors : Kiruthika Subramanian; Preetha Gunasekaran; Mercy Selvaraj;
Page : 317-324
Keywords : DDoS; hop count; IP2HC table; clustering; IP spoofing; testbed.;
Abstract
Distributed Denial of Service (DDoS) attackers make a service unavailable for intended users. Attackers use IP spoofing as a weapon to disguise their identity. The spoofed traffic follows the same principles as normal traffic, so detection and filtering is very essential. Hop Count Filtering (HCF) scheme identifies packet whose source IP address is spoofed. The information about a source IP address and its corresponding hops from a server (victim) recorded in a table at the victim. The incoming packet is checked against this table for authenticity. The design of IP2HC table reduces the amount of storage space by IP address clustering. The proposed work filters majority of the spoofed traffic by Hop Count Filter-Support Vector Machine (HCF-SVM) algorithm on the network layer. DDoS attackers using genuine IP is subjected to traffic limit at the application layer. The two layer defense approach protects legitimate traffic from being denied, thereby mitigating DDoS effectively. HCF-SVM model yields 98.99% accuracy with reduced False Positive (FP) rate and the rate limiter punishes the aggressive flows and provides sufficient bandwidth for legitimate users without any denial of service. The implementation of the proposed work is carried out on an experimental testbed.
Other Latest Articles
- Effects of Training Set Dimension on Recognition of Dysmorphic Faces with Statistical Classifiers
- Topical Web Crawling for Domain-Specific Resource Discovery Enhanced by Selectively using Link-Context
- Arabic Text Classification using K-Nearest Neighbour Algorithm
- Optimized Features Selection using Hybrid PSOGA for Multi-View Gender Classification
- Optimizing Ontology Alignments by using NSGA-II
Last modified: 2019-11-14 22:41:51