Journal
SOFT COMPUTING
Volume 18, Issue 9, Pages 1697-1703Publisher
SPRINGER
DOI: 10.1007/s00500-014-1250-8
Keywords
Cloud computing; DDoS attack detection; HTTP packet pattern; MapReduce
Categories
Funding
- Basic Science Research Program through the National Research Foundation of Korea (NRF) - Ministry of Education [2013R1A1A2A1001-1667]
- National Research Foundation of Korea [22A20130012158] Funding Source: Korea Institute of Science & Technology Information (KISTI), National Science & Technology Information Service (NTIS)
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Cloud computing is a more advanced technology for distributed processing, e.g., a thin client and grid computing, which is implemented by means of virtualization technology for servers and storages, and advanced network functionalities. However, this technology has certain disadvantages such as monotonous routing for attacks, easy attack method, and tools. This means that all network resources and operations are blocked all at once in the worst case. Various studies such as pattern analyses and network-based access control for infringement response based on Infrastructure as a Service, Platform as a Service and Software as a Service in cloud computing services have therefore been recently conducted. This study proposes a method of integration between HTTP GET flooding among Distributed Denial-of-Service attacks and MapReduce processing for fast attack detection in a cloud computing environment. In addition, experiments on the processing time were conducted to compare the performance with a pattern detection of the attack features using Snort detection based on HTTP packet patterns and log data from a Web server. The experimental results show that the proposed method is better than Snort detection because the processing time of the former is shorter with increasing congestion.
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