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The Domain Name System (DNS), whose major function is to manage associations between domain names and IP addresses, plays a major role in managing the Internet. Thus, a DNS impairment would significantly impact society. A major cause of DNS impairment is Distributed Denial of Service (DDoS) attack on authoritative DNS servers. Our study focuses on the recently emerging DDoS attack known as the DNS Water Torture Attack. This attack causes open resolvers, which are improperly configured cache DNS servers that accept requests from both LAN and WAN, to send many queries to resolve domains managed by target servers. Domain names for resolving sent in this attack include varying random subdomains. Cache servers certainly will not have cached data for these queries, and so a huge volume of queries converges to the target authoritative servers via cache servers. In this paper, we propose a detection method for this attack using the Naive Bayes Classifier. Experimental results show that our method is capable of detecting this attack with a 95.59% detection rate. Moreover, the results of performance simulation show that our method is fast enough to process more than 2.3 Gbps of traffic on the fly.

Detection of the DNS Water Torture Attack by Analyzing Features of the Subdomain Name