Journal of
Systemics, Cybernetics and Informatics
 



ISSN: 1690-4524 (Online)


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Honorary Editorial Advisory Board's Chair
William Lesso (1931-2015)

Editor-in-Chief
Nagib C. Callaos


Sponsored by
The International Institute of
Informatics and Systemics

www.iiis.org
 

Editorial Advisory Board

Editors

Journal's Reviewers
 

Description and Aims

Submission of Articles

Areas and Subareas

Information to Contributors

Editorial Peer Review Methodology

Integrating Reviewing Processes


Detection of Minimal Set of Trips Causing the Necessity to Use Extra Vehicle for Vehicle Scheduling Problem
Katerina Pastircáková, Jaromír Šulc
(pages: 1-4)

Key Factors in the Success of Self - Directed Learning of Military Personnel - Taking Smartphone as an Example
Yen-Hsi Lo, Yen-Fen Lo, Po-Yun Chiang, Jung Hsiao
(pages: 5-8)

Machine Learning Based IP Network Traffic Classification Using Feature Significance Analysis
Te-Shun Chou, John Pickard, Ciprian Popoviciu
(pages: 9-12)

The Information System for US Stock Market: Fundamental and Technical Analysis
Sergejs Hilkevics, Galina Hilkevica
(pages: 13-24)

The Impact of Environmental and Social Performance on the Market Value of Shares of Czech Joint-Stock Corporations
Alena Kocmanova, Marie Pavlakova Docekalova, Iveta Simberova
(pages: 25-31)

Play the Game! Analogue Gamification for Raising Information Security Awareness (Invited Paper)
Margit Scholl
(pages: 32-35)

Using Informatics and Technology Practices for Academic Performance Review
Kim Moorning
(pages: 36-41)

Multiple Research Perspectives as a Paradigm to Co-Create Meaningful Real-life Experiences
Jan Detand, Marina Emmanouil
(pages: 42-46)

A Methodology to Integrate Regulatory Expertise, Research and Education to Accelerate Biomedical Device Translation
Diana Easton
(pages: 47-52)

Active Learning through Smart Grid Model Site in Challenge Based Learning Course
Ellen A. Kalinga, Kwame S. Ibwe, Nerey H. Mvungi, Hannu Tenhunen
(pages: 53-64)

Non-Linear Static Analysis of Masonry Buildings under Seismic Actions
Maria Luisa Beconcini, Paolo Cioni, Pietro Croce, Paolo Formichi, Filippo Landi, Caterina Mochi
(pages: 65-70)

Toward an Engaging Hands-on Environment for a Beginning Networking and Security Class
Lopamudra Roychoudhuri
(pages: 71-76)

Designing Representations, Affecting Reality: A Meta-Model Proposal to Address the Question of Design Epistemology from the Perspective of Cognitive Science
Andrea Zammataro
(pages: 77-80)

Dielectrophoretic Movement of Cell around Surface Electrodes in Flow Channel
Yusuke Takahashi, Shigehiro Hashimoto, Manabu Watanabe
(pages: 81-87)


 

Abstracts

 


ABSTRACT


Network Intrusion Detection System – A Novel Approach

Krish Pillai


Network intrusion starts off with a series of unsuccessful breakin attempts and results eventually with the permanent or transient failure of an authentication or authorization system. Due to the current complexity of authentication systems, clandestine attempts at intrusion generally take considerable time before the system gets compromised or damaging change is affected to the system giving administrators a window of opportunity to proactively detect and prevent intrusion. Therefore maintaining a high level of sensitivity to abnormal access patterns is a very effective way of preventing possible break-ins. Under normal circumstances, gross errors on the part of the user can cause authentication and authorization failures on all systems. A normal distribution of failed attempts should be tolerated while abnormal attempts should be recognized as such and flagged. But one cannot manage what one cannot measure. This paper proposes a method that can efficiently quantify the behaviour of users on a network so that transient changes in usage can be detected, categorized based on severity, and closely investigated for possible intrusion. The author proposes the identification of patterns in protocol usage within a network to categorize it for surveillance. Statistical anomaly detection, under which category this approach falls, generally uses simple statistical tests such as mean and standard deviation to detect behavioural changes. The author proposes a novel approach using spectral density as opposed to using time domain data, allowing a clear separation or access patterns based on periodicity. Once a spectral profile has been identified for network, deviations from this profile can be used as an indication of a destabilized or compromised network. Spectral analysis of access patterns is done using the Fast Fourier Transform (FFT), which can be computed in T(N log N) operations. The paper justifies the use of this approach and presents preliminary results of studies the author has conducted on a restricted campus network. The paper also discusses how profile deviations of the network can be used to trigger a more exhaustive diagnostic setup that can be a very effective first-line of defense for any network.

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