Journal
Scientific and technical journal «Priborostroenie»
UDK004.056
Issue:11 (61)
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COMBINING HADOOP AND SNORT TECHNOLOGIES FOR DETECTION OF NETWORK ATTACKS
Annotation
A method of information processing on the base of Big Data technologies aimed at computer at-tacks detection is studied. The need to create specialized approaches and design methods that will im-prove the efficiency of processing the received information is justified. The possibilities and effectiveness assessments of parallel data processing with the purpose of computer influences detection using a functional approach, as well as the key principles of working with Big Data, are considered. The mathematical model by means of which the technique of intrusion detection is developed is presented. The principle of implementation of the tasks of information processing and anomaly detection based on integration of Hadoop, Snort platforms is described. Main results of the experimental evaluation of the method used to detect computer attacks are presented
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