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Intrusion detection system using hybrid differential evolution and group method of data handling approach

Sharma, Alokanand and Onwubolu, Godfrey C. (2008) Intrusion detection system using hybrid differential evolution and group method of data handling approach. [Conference Proceedings]

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This paper proposes a new intrusion detection methodology based on hybrid of differential evolution (DE) and group method of data handling (GMDH). It focuses on intrusion detection based on system call sequences using text processing techniques. The hybrid DE-GMDH is used to classify a process as either normal or abnormal. This work presents the application of PCA and hybrid DE-GMDH to modeling high dimensional bench-mark DARPA-1998 database. For modeling and classifying the data, we adopted this combination of two stage PCA and hybrid DE-GMDH procedure. The presented technique shows significantly better results than other existing techniques avaliable in the literature in achieving lower false positive rates at 100% detection rate.

Item Type: Conference Proceedings
Additional Information: The 2nd International Conference on Inductive Modelling (ICIM’2008) dedicated to the blessed memory of Academician Alexey Grigorievich Ivakhnenko is held in Kyiv on September 15-19, 2008. This year is very remarkable for all those working in the inductive modelling field in view of the 95th Anniversary from the Ivakhnenko’s birthday and 40th anniversary from publication of the very first Ivakhnenko’s article where the Group Method of Data Handling (GMDH) was suggested. The initial Conference ICIM'2002 took place in Lviv,Ukraine, in May 2002. Following the Conference, two workshops was held in Kyiv, Ukraine, in July 2005 and in Prague, Czech Republic, on September 23-26, 2007. The series of conferences and workshops is the only international forum that focuses on theory, algorithms, applications, solutions, and new developments of data mining and knowledge extraction technologies which originate from GMDH as a typical inductive modelling method. Built on principles of self-organization, inductive modelling has been developing and using in several key areas and can be found in data mining technologies like Polynomial Neural Networks, Adaptive Learning Networks, or Statistical Learning Networks. More recent developments also utilize Genetic Algorithms or the idea of Active Neurons and multileveled self-organization to build models from data. The motivation of this 2nd Conference is to analyze the state-of-the-art of modelling methods that inductively generate models from data, to discuss concepts of an automated knowledge discovery workflow, to share new ideas on model validation and visualization, to present novel applications in different areas, and to give inspiration and background on how inductive modelling can contribute to solving the current global challenges.
Uncontrolled Keywords: Dimensionality reduction, inductive modeling,DE, GMDH, hybrid systems, intrusion detection
Subjects: T Technology > TA Engineering (General). Civil engineering (General)
Divisions: Faculty of Science, Technology and Environment (FSTE) > School of Engineering and Physics
Depositing User: Alokanand Sharma
Date Deposited: 12 Aug 2008 23:44
Last Modified: 12 Aug 2012 23:44

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