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Analysis and Performance Evaluation of Application Specific Processors for Network-Based Intrusion Detection Systems

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Advances in Computing and Information Technology

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 176))

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Abstract

By growing and development of computer networks and generalizing the use of modern services on the information platform, the importance of communication and information security is considered more than the other times by network representations and users. Presented reports by response computer incident different groups show the wide growth of computer attacks in the recent years. In this case Network Intrusion Detection Systems (NIDS) as one of the Intrusion Detection System (IDS) types, are be transformed to the utilization systems for establishing the security levels and detecting the illegal activities in the network. This research includes an IDS which is written in C programming language that uses 15597 Snort rules and MIT Lincoln Lab network traffic. By running this security application on the V850, OR1K, MIPS32, ARM7TDMI and PowerPC32 microprocessors, their performance can be evaluated. For increasing the performance in this research, the GNU Compiler Collection (GCC) optimization levels are used and at the end, base on O2 optimization level a new combination of optimization flags is presented which the performance of ARM7TDMI microprocessor is increased.

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Correspondence to Majid Nezakatolhoseini .

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Nezakatolhoseini, M., Jabbehdari, S., Pourmina, M.A. (2012). Analysis and Performance Evaluation of Application Specific Processors for Network-Based Intrusion Detection Systems. In: Meghanathan, N., Nagamalai, D., Chaki, N. (eds) Advances in Computing and Information Technology. Advances in Intelligent Systems and Computing, vol 176. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-31513-8_7

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  • DOI: https://doi.org/10.1007/978-3-642-31513-8_7

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-31512-1

  • Online ISBN: 978-3-642-31513-8

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