Document Details

Document Type : Article In Conference 
Document Title :
High Performance Data Mining for Network Intrusion Detection
ارتفاع التعدين بيانات الأداء لكشف التسلل الشبكة
 
Subject : High performance computing, data mining, 
Document Language : English 
Abstract : Computer intrusion detection is an approach to detect suspected intrusions as soon as possible to reduce the damage to the system and take appropriate actions using the audit data generated by the computers. There are two basic approaches, anomaly detection and misuse detection. Anomaly detection is to define correct behavior of the system, and then to detect abnormal behaviors. Misuse detection is to characterize known intrusion patterns and generate explicit rules to describe them. Then, it monitors for those patterns to indicate an occurrence of intrusion. However, these algorithms are computationally expensive and the audit data are usually too huge to be processed manually or find valuable information heuristically. We use a high performance data mining technique to discover underlying hidden knowledge embedded in large volumes of data. We develop a parallel data mining model for intrusion detection using a parallel backpropagation neural network. We evaluate the performance of the developed model in terms of speedup, prediction rate, and false alarm rate. We also introduce the concurrent programming library we have been developing called Computational Resiliency library (CRlib) to implement the proposed high performance data mining algorithms. 
Conference Name : Parallel and Distributed Computing and Systems 
Duration : From : 9/11/1426 AH - To : 11/11/1426 AH
From : 9/11/2004 AD - To : 11/11/2004 AD 
Publishing Year : 1426 AH
2004 AD 
Article Type : Article 
Conference Place : Cambridge, Massachusetts, USA 
Organizing Body : MIT 
Added Date : Wednesday, February 16, 2011 

Researchers

Researcher Name (Arabic)Researcher Name (English)Researcher TypeDr GradeEmail
معظم صديقيSiddiqui, Muazzam ResearcherDoctoratemaasiddiqui@kau.edu.sa

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 29008.docx docx 

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