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Multivariate Linear Regression Model for Host Based Intrusion Detection

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Computational Intelligence in Data Mining - Volume 3

Part of the book series: Smart Innovation, Systems and Technologies ((SIST,volume 33))

Abstract

Computer security is an important issue for an organization due to increasing cyber-attacks. There exist some intelligent techniques for designing intrusion detection systems which can protect the computer and network systems. In this paper, we discuss multivariate linear regression model (MLRM) to develop an anomaly detection system for outlier detection in hardware profiles. We perform experiments on performance logfiles taken from a personal computer. Simulation results show that our model discovers intrusion effectively and efficiently.

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Correspondence to Sunil Kumar Gautam .

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Gautam, S.K., Om, H. (2015). Multivariate Linear Regression Model for Host Based Intrusion Detection. In: Jain, L., Behera, H., Mandal, J., Mohapatra, D. (eds) Computational Intelligence in Data Mining - Volume 3. Smart Innovation, Systems and Technologies, vol 33. Springer, New Delhi. https://doi.org/10.1007/978-81-322-2202-6_33

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  • DOI: https://doi.org/10.1007/978-81-322-2202-6_33

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  • Publisher Name: Springer, New Delhi

  • Print ISBN: 978-81-322-2201-9

  • Online ISBN: 978-81-322-2202-6

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