Soft Computing Techniques for Intrusion Detection - A Survey
Abstract
Due to the extensive use of computers and data communication among computers, in recent years, network security is emerging as an important field in protecting the communication networks from the cyber crime, cyber threats, unauthorized access, etc. Intrusions are the set of actions that violates the integrity, availability or confidentiality of a network resource. It can be thought of as a successful attack on network Intrusion Detection System (IDS) is a system which detects the attacks and informs it. This paper presents the soft computing based techniques that can be used for detection of intrusions.
How to cite this article:
Panda BK. Soft Computing Techniques for Intrusion Detection - A Survey. J Engr Desg Anal 2020; 3(2): 101-103.
References
Powell D, Stroud R. Conceptual Model and Architecture, Deliverable D2, Project MAFTIA IST-1999-11583, IBM Zurich Research Laboratory Research Report RZ 3377, 2001.
Zhong S, Khoshgoftaar T, Seliya N. Clustering based network intrusion detection. Int Journal of Reliability Quality and Safety 2007; 14(2): 169-187.
Pakkurthi S, Avadhani PS, Korimilli V et al. Approaches and Data Processing Techniques for Intrusion Detection System. 2009; 9(12): 181-186.
Lunt TF, Tamaru A, Gilham F et al. Computer Science Laboratory, SRI International, Menlo Park, CA, USA, Final Technical Report, 1992.
Shah K, Dave N, Chavan S et al. Adaptive neuro fuzzy intrusion detection system. IEEE International Conference on Information Technology: Coding and Computing. Society 2004; 70: 74.
Anderson D, Frivold T, Valdes A. Next-generation intrusion detection expert system (NIDES): A summary Technical Report SRI CSL. Computer Science Laboratory, SRI International 1995.
Stephen FO, Reuven RL. An adaptive expert system approach for intrusion detection. International Journal of Security and Networks 2006; 1(3/4): 206-217.
Shi Z, Shi Z, Olumide S et al. Network Anomalous Intrusion Detection using Fuzzy Bayes. IFIP International Federation for Information 2007 228: 525-530.
Bharanidharan S, Idris NB. Improved Intrusion Detection System Using Fuzzy Logic for Detecting Anamoly and Misuse Type of Attacks. International Conference of Soft Computing and Pattern Recognition. 2009; 212-217.
Jaiganesh V, Sumathi P, Mangyakarsi S. An analysis of intrusion Detection System using back propagation. Neural Network 2013.
Published
Issue
Section
Copyright (c) 2021 Journal of Engineering Design and Analysis
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
We, the undersigned, give an undertaking to the following effect with regard to our article entitled
“_______________________________________________________________________________________________________________________________________________________________________________
________________________________________________________________________________” submitted for publication in (Journal title)________________________________________________ _______________________________________________________Vol.________, Year _________:-
1. The article mentioned above has not been published or submitted to or accepted for publication in any form, in any other journal.
2. We also vouchsafe that the authorship of this article will not be contested by anyone whose name(s) is/are not listed by us here.
3. I/We declare that I/We contributed significantly towards the research study i.e., (a) conception, design and/or analysis and interpretation of data and to (b) drafting the article or revising it critically for important intellectual content and on (c) final approval of the version to be published.
4. I/We hereby acknowledge ADRs conflict of interest policy requirement to scrupulously avoid direct and indirect conflicts of interest and, accordingly, hereby agree to promptly inform the editor or editor's designee of any business, commercial, or other proprietary support, relationships, or interests that I/We may have which relate directly or indirectly to the subject of the work.
5. I/We also agree to the authorship of the article in the following sequence:-
Authors' Names (in sequence) Signature of Authors
1. _____________________________________ _____________________________________
2. _____________________________________ _____________________________________
3. _____________________________________ _____________________________________
4. _____________________________________ _____________________________________
5. _____________________________________ _____________________________________
6. _____________________________________ _____________________________________
7. _____________________________________ _____________________________________
8. _____________________________________ _____________________________________
Important
(I). All the authors are required to sign independently in this form in the sequence given above. In case an author has left the institution/ country and whose whereabouts are not known, the senior author may sign on his/ her behalf taking the responsibility.
(ii). No addition/ deletion/ or any change in the sequence of the authorship will be permissible at a later stage, without valid reasons and permission of the Editor.
(iii). If the authorship is contested at any stage, the article will be either returned or will not be
processed for publication till the issue is solved.
