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Virparia, P. V.
- Challenges in Genetic Algorithm Based Intrusion Detection
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National Journal of System and Information Technology, Vol 4, No 1 (2011), Pagination: 109-116Abstract
Intrusion detection is the technique of detecting malicious traffic on a network or a device. It is one of the critical network security components against emerging intrusions techniques and attacks. In this paper we present a survey of different intrusion detection approaches. Intrusion Detection Systems based on Genetic Algorithm are currently attracting researchers due to its inherent potential. Intrusion detection faces various challenges like reliably detect malicious activity and perform efficiently to cope with the large amount of network traffic. Here we have analyzed the present research challenges and issues in Genetic Algorithm based intrusion detection. Finally we carry out our experiments based on our sample Genetic Algorithm using KDD Cup 99 data set. The main contribution of the implementation is the understanding of challenges in Genetic Algorithm based intrusion detection.Keywords
Security, Challenges, Genetic Algorithm, Intrusion Detection
References
- Sumit A. Khandelwal, Shoba. A. Ade, Amol A. Bhosle and Radha S. Shirbhate, "A Simplified Approach to Identify Intrusion in Network with Anti Attacking Using .net Tool", International Journal of Computer and Electrical Engineering, Vol. 3, No. 3, June 2011
- Z. Muda, W. Yassin, M. N. Sulaiman, and N. I. Udzir, "A K-Means and Naive Bayes Learning Approach for Better Intrusion Detection", Information Technology Journal 10(3): 648-655, 2011
- 3Fatin Norsyafawati Mohd Sabri, Norita Md.Norwawi, and Kamaruzzaman Seman, "Identifying False Alarm Rates for Intrusion Detection System with Data Mining", IJCSNS International Journal of Computer Science and Network Security, VOL.11 No.4, April 2011
- Ghanshyam Prasad Dubey, Prof. Neetesh Gupta, Rakesh K Bhujade, "A Novel Approach to Intrusion Detection System using Rough Set Theory and Incremental SVM", International Journal of Soft Computing and Engineering (IJSCE) ISSN: 2231- 2307, Volume-1, Issue-1, March 2011
- Ritu Ranjani Singh, Neetesh Gupta, Shiv Kumar, "To Reduce the False Alarm in Intrusion Detection System using self Organizing Map", International Journal of Soft Computing and Engineering (IJSCE) ISSN: 2231-2307, Volume-1, Issue-2, May 2011
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- S. Selvakani Kandeeban, R. S. Rajesh, "A Mutual Construction for IDS Using GA", International Journal of Advanced Science and Technology Vol. 29, April, 2011
- Kunjal Mankad, Priti Srinivas Sajja, and Rajendra Akerkar, "EVOLVING RULES USING GENETIC FUZZY APPROACH - AN EDUCATIONAL CASE STUDY", International Journal on Soft Computing ( IJSC ), Vol.2, No.1, February 2011
- VEGARD ENGEN, "MACHINE LEARNING FOR NETWORK BASED INTRUSION DETECTION", PhD thesis, Bournemouth University, June 2010
- R. Shanmugavadivu, Dr.N.Nagarajan, "NETWORK INTRUSION DETECTION SYSTEM USING FUZZY LOGIC", Indian Journal of Computer Science and Engineering (IJCSE)
- S.Sethuramalingam, Dr.E.R. Naganathan, "HYBRID FEATRUE SELECTION FOR NETWORK INTRUSION", International Journal on Computer Science and Engineering (IJCSE)
- Ahmed AHMIM, Nacira GHOUALMI, Noujoud KAHYA, "Improved Off-Line Intrusion Detection Using A Genetic Algorithm And RMI", (IJACSA) International Journal of Advanced Computer Science and Applications, Vol. 2, No.1, January 2011
- M. Sadiq Ali Khan, "Rule based Network Intrusion Detection using Genetic Algorithm", International Journal of Computer Applications (0975 – 8887) Volume 18– No.8, March 2011
- Ian Stewart, "A Modified Genetic Algorithm and Switch-Based Neural Network Model Applied to Misuse-Based Intrusion Detection", Master of Science Thesis, Queen's University, Kingston, Ontario, Canada, February 2009
- Zorana Bankovic,"A Genetic Algorithm-based Solution for Intrusion Detection", Journal of Information Assurance and Security, (2009) 192-199
- Ian Stewart, "A Modified Genetic Algorithm and Switch-Based Neural Network Model Applied to Misuse-Based Intrusion Detection", MS Thesis, Queen's University, Kingston, Ontario, Canada, February 2009
- S. SELVAKANI and R.S.RAJESH, "Escalate Intrusion Detection using GA - NN", Int. J. Open Problems Compt. Math., Vol. 2, No. 2, June 2009
- Zorana Bankovic, José M. Moya, Álvaro Araujo, Slobodan Bojanic and Octavio Nieto-Taladriz, "A Genetic Algorithm-based Solution for Intrusion Detection", Journal of Information Assurance and Security 4 (2009) 192-199
- H. Günes Kayacik, A. Nur Zincir-Heywood, Malcolm I. Heywood, "Selecting Features for Intrusion Detection: A Feature Relevance Analysis on KDD 99 Intrusion Detection Datasets", the NIMS Laboratory, http://www.cs.dal.ca/projectx, 2006
- Russell Meyer, “Challenges of Managing an Intrusion Detection System (IDS) in the Enterprise”, As part of Information Security Reading Room, SANS Institute, http://www.sans.org, June 2011
- Valerie Vogel, "Network and Host Security Implementation". Retrieved June 2011 from https://wiki.internet2.edu/confluence/display/secguide/Network+and+Host +Security+Implementation+(Stage+1)
- Development of Software Dispatcher Based Load Balancing Algorithms for Heterogeneous Cluster Based Web Systems
Abstract Views :291 |
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National Journal of System and Information Technology, Vol 5, No 2 (2012), Pagination: 105-114Abstract
Once the web site becomes a popular and the access frequency from a large domain of user increase then single web server may not be able to handle high volume of incoming traffic. To provide a better service to all the clients, they need a fully replicated web server clusters. In such an environment, one of the most important issues is that of server selection (and load balancing). In web cluster, load balancing process done at Open Systems Interconnection layer 4 (Hardware Load Balancer) and layer 7 (Software Load Balancer) with typical static and dynamic load balancing approaches. In this paper we present the performance analysis of round robin, random, least connection and new execution time load balancing algorithms at layer 7 in heterogeneous web cluster. The main purpose of this paper is to help in design of new algorithms in future by studying the behavior of various static and dynamic load balancing algorithms.Keywords
Web Cluster, Load Balancing, Static Load Balancing, Dynamic Load BalancingReferences
- Valeria Cardellini, Emiliano Casalicchio, Michele Colajani, Philip S Yu (2001). The State of the Art in Locally Distributed Web-server Systems, IBM Research Report, pp. 10-12, 26-41
- Valeria Cardellini, Michele Colajani, Philip S Yu(1999). Dynamic Load Balancing on Web-Server System, IEEE Internet computing, Vol. 3, pp. 10-15
- Michele Colajani, Philip S Yu, D. M. Dias (1998). Analysis of Task assignment polices in scalable distributed web systems, IEEE Transactions on Parallel and Distributed Systems, Vol. 9, pp. 7-13
- Tony Bourke (2001). Server Load Balancing, Sebastopol, CA, O'REILLY, pp. 13-22
- Hossien Bidgoli (2004), The Internet Encyclopedia, Vol. 2,John Wiley & Sons, Hoboken, New Jersey, pp. 499-511
- Willy Tarreau (2006). Making application scalable with load balancing. Information Website: http://1wt.eu/articles/2006_lb/
- http://www.ibm.com/software/network/dispatcher
- http://www.cisco.com
- http://www.foundrynet.com/pdf/wp-server-load-bal-web-enterprise.pdf
- A Review on Learning Repositories and Fuzzy XML in Education Field
Abstract Views :278 |
PDF Views:7
Authors
Affiliations
1 Department of Computer Science, Sardar Patel University, Vallabh Vidyanagar, Gujarat, IN
2 Department of Computer Science, Sardar Patel University, Vallabh Vidyanagar, IN
1 Department of Computer Science, Sardar Patel University, Vallabh Vidyanagar, Gujarat, IN
2 Department of Computer Science, Sardar Patel University, Vallabh Vidyanagar, IN
Source
National Journal of System and Information Technology, Vol 10, No 2 (2017), Pagination: 105-114Abstract
Well-designed syllabus plays an important role in the Education Domain. A repository of learning objects that has a well-defined metadata structure can be used to customize and design creative syllabus to embody the exchange and re-use of syllabus. To satisfy the need of reusable syllabus learning objects, many researches have focused mainly on Learning Object Repository and Fuzzy XML based Rules. This paper reviews the work done so far in these areas and founds a need for a knowledge based system for syllabus learning objects to increase reusability, interoperability, accessibility and durability.Keywords
Learning Object Repository, XML, Fuzzy XML.References
- Abhishek Gaurav, Reda Alhajj; Incorporating Fuzziness in XML and Mapping Fuzzy Relational Data into Fuzzy XML, ACM, 1-59593-108-2/06/0004, (2006).
- Adolfo Guzman-Arenas, Alma-Delia Cuevas; Knowledge accumulation through automatic merging of ontologies, http://dl.acm.org/citation.cfm?id=1663652.1663778, (2010).
- Andy Ju An Wang and Ken Yetsko; Building Reusable Information Security Courseware, http://dl.acm.org/citation.cfm?id=1107642, (2005).
- Changtao Qu, Wolfgang Nejdl, Holger Schinzel; Integrating Schema-specific Native XML Repositories into a RDF-based E-Learning P2P Network, http://dl.acm.org/citation.cfm?id=1344622 , (2002).
- Dimitrios A. Koutsomitropoulos, Andreas D. Alexopoulos, Georgia D. Solomou and Theodore S. Papatheodorou; The Use of Metadata for Educational Resources in Digital Repositories: Practices and Perspectives”, D-Lib Magazine, Volume 16, Number ½, (2010).
- Filip Neven and Erik Duval; Reusable Learning Objects: a Survey of LOM-Based Repositories, http://dl.acm.org/citation.cfm?id=641067,(2002).
- Ishan Sudeera Abeywardena, Chee Seng Chan, and Choy Yoong Tham; OERScout Technology Framework: A Novel Approach to Open Educational Resources Search, from Internation Review of Research in Open and Distance Learning, Volume 14, Number 4, (2013).
- Ismar Frango Silveira, Nizam Omarand Pollyana Notargiacomo Mustaro; The Architecture of Learning Object Repositories, http://proceedings.informingscience.org/ InSITE2005 /P117 Silveira.pdf, (2005).
- K. Naresh kumar, Dr. Ch. Satyanand Reddy, Prof. N.V.E.S. Murthy; Fuzzy-Based XML Knowledge Retrieval Methods in Edaphology, https://www.researchgate.net/publication/301644241_Fuzzy-Based_XML_Knowledge_Retrieval_Methods_in_Edaphology , (2016).
- McGreal, R.; Online Education Using Learning Objects. RoutledgeFalmer: London and New York. Hardback. ISBN: 0 4153 3512 4, (2004).
- Miguel-Angel Sicilia,Elena García; On the Concepts of Usability and Reusability of Learning Objects, http://www.irrodl.org/index.php/irrodl/article/view/155/236 , (2003).
- Nilufar Baghaei; A collaborative constraint-based Intelligent system for learning object oriented Analysis and design using UML, (2007).
- Osama Shata; A Critique Of Stephen Downes' Article, "Learning Objects: A Middle Eastern Perspective”, http://www.irrodl.org/index.php/irrodl/article/view/33/79, (2001).
- Peter Sefton and Duncan Dickinson; “Repositories post 2010: embracing heterogeneity in AWE, the Academic Working Environment”, OpenRepositories July 2010, Madrid, Spain, (2010).
- Priti Srinivas Sajja; Multi-Tier Knowledge-Based System Accessing Learning Object Repository Using Fuzzy XML, http://www.irma-international.org/viewtitle/38370/, (2013).
- Priti Srinivas Sajja; Knowledge Representation Using Fuzzy XML Rules for Web Based Expert System, http://www.irma-international.org/chapter/knowledge-representation-using-fuzzy-xml-rules-in-web-based-expert-system-for-medical-diagnosis/124446/, (2015).
- UWEO Instructional Resources / Why is the course syllabus important? (n.d.), Retrieved 25-2-2015 from websitehttp://www.outreach.washington.edu/teaching/why syllabus.asp, (2015).
- Y. Eguigure, A. Zapata, V. Menendez, M. Prieto; Quality Evaluation Model for Learning Objects From Pedagogical Perspective. A Case Of Study, published in Iberoamerican Journal of Applied Computing, ISSN 2237-4523, (2011).
- Zeynel Cebeci, Fuat Budak, Mehmet Tekdal; Working with XML for Flexible Management of Online Course Syllabi, http://scialert.net/abstract/?doi=itj.2006.322.328, (2006).