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Reseach Article

Using Ontologies to Model Attacks in an Internet based Mobile Ad-hoc Network (iMANET)

by Samrudhi Sharma, Manali Trivedi, Lakshmi Kurup
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 110 - Number 2
Year of Publication: 2015
Authors: Samrudhi Sharma, Manali Trivedi, Lakshmi Kurup
10.5120/19287-0705

Samrudhi Sharma, Manali Trivedi, Lakshmi Kurup . Using Ontologies to Model Attacks in an Internet based Mobile Ad-hoc Network (iMANET). International Journal of Computer Applications. 110, 2 ( January 2015), 7-12. DOI=10.5120/19287-0705

@article{ 10.5120/19287-0705,
author = { Samrudhi Sharma, Manali Trivedi, Lakshmi Kurup },
title = { Using Ontologies to Model Attacks in an Internet based Mobile Ad-hoc Network (iMANET) },
journal = { International Journal of Computer Applications },
issue_date = { January 2015 },
volume = { 110 },
number = { 2 },
month = { January },
year = { 2015 },
issn = { 0975-8887 },
pages = { 7-12 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume110/number2/19287-0705/ },
doi = { 10.5120/19287-0705 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:45:18.753182+05:30
%A Samrudhi Sharma
%A Manali Trivedi
%A Lakshmi Kurup
%T Using Ontologies to Model Attacks in an Internet based Mobile Ad-hoc Network (iMANET)
%J International Journal of Computer Applications
%@ 0975-8887
%V 110
%N 2
%P 7-12
%D 2015
%I Foundation of Computer Science (FCS), NY, USA
Abstract

In this paper the usage of Semantic Web techniques to secure Internet based Mobile Ad-hoc Networks (iMANETs) has been proposed. Ontologies will be used instead of Taxonomies to depict network security issues. These ontologies can be placed in the knowledge base of an Intrusion Detection System (IDS). Using inference over the semantic relations will help Intrusion Detection Systems recognize and add future attacks to its existing knowledge base.

References
  1. S. Stolfo, 'Intrusion Detection Systems', 2006.
  2. P. Kazienko, 'Intrusion Detection Systems (IDS) Part I - (network intrusions; attack symptoms; IDS tasks; and IDS architecture)', WindowSecurity, 2003.
  3. V. Raskin, C. Hempelmann, K. Triezenberg and S. Nirenburg, 'Ontology in information security: a useful theoretical foundation and methodological tool', pp. 53--59, 2001.
  4. J. Pinkston, J. Undercoffer, A. Joshi and T. Finin, 'A target-centric ontology for intrusion detection', University of Maryland, Baltimore County Department of Computer Science and Electrical Engineering, 2003.
  5. J. Undercoffer, A. Joshi, J. Pinkston, "Modeling Computer Attacks: An Ontology for Intrusion Detection" August 2003
  6. A. Salahi and M. Ansarinia, 'Predicting Network Attacks Using Ontology-Driven Inference', arXiv preprint arXiv:1304. 0913, 2013.
  7. Hsieh, C. , Chen, R. and Huang, Y. (2014). Applying an ontology to a patrol intrusion detection system for wireless sensor networks. International Journal of Distributed Sensor Networks, 2014.
  8. A. Jayasuriya, S. Perreau, A. Dadej and S. Gordon, 'Hidden vs exposed terminal problem in ad hoc networks', 2004.
  9. C. Perkins and E Royer, "Ad Hoc On-Demand Distance Vector Routing," 2nd IEEE Wksp. Mobile Comp. Sys. and Apps. , 1999.
  10. Jhaveri, R. , Patel, A. , Parmar, J. and Shah, B. (2010). MANET Routing Protocols and Wormhole Attack against AODV. International Journal of Computer Science and Network Security, [online] 10(4), pp. 12-17.
  11. Hu, J. and Burmester, M. (2004). Network-layer Security of Mobile Adhoc Networks. Florida State University.
  12. D. Johnson and D. Maltz, "Dynamic Source Routing in Ad Hoc Wireless Networks," Mobile Computing, T. Imielinski and H. Korth, Ed. , pp. 153-81. Kluwer, 1996.
  13. Mohammad Ilyas, "The Handbook of Ad Hoc Wireless Networks".
  14. G. Antoniou and F. Van Harmelen, 'Web ontology language: Owl', Springer, pp. 67--92, 2004.
  15. W3. org, 'OWL Web Ontology Language Overview', 2014. [Online]. Available:http://www. w3. org/TR/2004/REC-owl-features-20040210/#s2. 1.
  16. De Vergara, J. , Villagra, V. and Berrocal, J. (2004). Applying the Web ontology language to management information definitions. IEEE Communications Magazine, 42(7), pp. 68-74
  17. Simon H, Ray," A taxonomy of network and computer attacks, "Elsevier, Computers & Security (2005) 24, 31e43.
  18. Protege. stanford. edu, 'protégé', 2014. [Online]. Available: http://protege. stanford. edu/.
  19. W3. org, 'RDF Schema 1. 1', 2014. [Online]. Available: http://www. w3. org/TR/2014/PER-rdf-schema-20140109/.
  20. Derivo. de, (2015). SPARQL-DL API – derive GmbH. [online] Available at: http://www. derivo. de/en/resources/sparql-dl-api. html [Accessed 29 Dec. 2014].
  21. Owlapi. sourceforge. net, (2015). OWL API. [online] Available at: http://owlapi. sourceforge. net/ [Accessed 29 Dec. 2014].
  22. Shahriari, H. , Makarem, M. , Sirjani, M. ,Jalili, R. and Movaghar, A. (2010). Vulnerability analysis of networks to detect multiphase attacks using the actor based language Rebeca. Computers and Electrical Engineering, 36(5), pp. 874-885.
Index Terms

Computer Science
Information Sciences

Keywords

Intrusion Detection Semantic Web Ontology Ad-Hoc Networks Security Attacks Web Ontology Language Protégé OWL.