Distributed denial of services attack protection system with genetic algorithms on Hadoop cluster computing framework

DDoS attacks become serious as one of the menaces of the Internet security. It is difficult to prevent because DDoS attacker send spoofing packets to victim which makes the identification of the origin of attacks very difficult. A series of techniques have been studied such as pattern matching by le...

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Bibliographic Details
Main Authors: Mizukoshi, Masataka, Munetomo, Masaharu
Format: Conference Proceeding
Language:English
Subjects:
Accuracy
Computer crime
DDoS attack
Distributed processing
Genetic Algorithm
Genetic algorithms
Genetics
Hadoop
IP networks
Sparks
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Summary:DDoS attacks become serious as one of the menaces of the Internet security. It is difficult to prevent because DDoS attacker send spoofing packets to victim which makes the identification of the origin of attacks very difficult. A series of techniques have been studied such as pattern matching by learning the attack pattern and abnormal traffic detection. However, pattern matching approach is not reliable because attackers always set attacks of different traffic patterns and pattern matching approach only learns from the past DDoS data. Therefore, a reliable system has to watch what kind of attacks are carried out now and investigate how to prevent those attacks. Moreover, the amount of traffic flowing through the Internet increase rapidly and thus packet analysis should be done within considerable amount of time. This paper proposes a scalable, real-time traffic pattern analysis based on genetic algorithm to detect and prevent DDoS attacks on Hadoop distributed processing infrastructure. Experimental results demonstrate the effectiveness of our scalable DDoS protection system.
ISSN:1089-778X
1941-0026
DOI:10.1109/CEC.2015.7257075