Dynamic event classification for intrusion and false alarm detection in vehicular ad hoc networks

International Journal of Information and Communication Technology

Volumn 8, Issue 2-3, 2016, Pages 140-164

  Al Zamil, Mohammed G H ^a   Samarah, Samer ^a  

^a YARMOUK UNIVERSITY   (Jordan)

Author keywords

Ad hoc data classification; Automatic vehicle location; False alarm detection; Intrusion detection; Mining ad hoc networks; Sensor networks

Indexed keywords

ALARM SYSTEMS; ERRORS; INTRUSION DETECTION; SEMANTICS; SENSOR NETWORKS;

AD HOC DATUM; AUTOMATIC VEHICLE LOCATIONS; BINARY CLASSIFICATION; CLASSIFICATION TECHNIQUE; COMMUNICATION MESSAGES; FALSE ALARMS; INTRUSION DETECTION SYSTEMS; OPTIMISATION PROBLEMS;

VEHICULAR AD HOC NETWORKS;

EID: 84959333664     PISSN: 14666642     EISSN: 17418070     Source Type: Journal    
DOI: 10.1504/IJICT.2016.074840     Document Type: Article

References (43)

1. Al Zamil, M.G. and Can, A.B. (2011) 'ROLEX-SP: rules of lexical syntactic patterns for free text categorization', Knowledge-Based Systems, Vol. 24, No. 1, pp.58-65.
2. Anthony, M.H.G. (1997) Computational Learning Theory, Cambridge University Press, New York, USA.
3. Ball, P. (2012) Why Society is a Complex Matter: Meeting Twenty-First Century Challenges with a New Kind of Science, Springer, Berlin, Germany.
4. Bao, F., Chen, R., Chang, M. and Cho, J.H. (2012) 'Hierarchical trust management for wireless sensor networks and its applications to trust-based routing and intrusion detection', Network and Service Management, IEEE Transactions on, Vol. 9, No. 2, pp.169-183.
5. Behrisch, M., Bieker, L., Erdmann, J. and Krajzewicz, D. (2011) 'SUMO - simulation of urban mobility-an overview', SIMUL 2011, the Third International Conference on Advances in System Simulation, pp.55-60).
6. Berlin MOD Collection [online] http://dna.fernuni-hagen.de/secondo/BerlinMOD/BerlinMOD.html (accessed 25 October 2013).
7. Besson, L. and Leleu, P. (2009) 'A distributed intrusion detection system for ad-hoc wireless sensor networks: the AWISSENET distributed intrusion detection system', Systems, Signals and Image Processing, 2009: IWSSIP 2009, 16th International Conference on, June, pp.1-3, IEEE.
8. Bhargava, S. and Agrawal, D.P. (2001) 'Security enhancements in AODV protocol for wireless ad hoc networks', Vehicular Technology Conference, 2001: VTC 2001, IEEE VTS 54th, Fall, Vol. 4, pp.2143-2147, IEEE.
9. Boppana, R.V. and Su, X. (2011) 'On the effectiveness of monitoring for intrusion detection in mobile ad hoc networks', Mobile Computing, IEEE Transactions on, Vol. 10, No. 8, pp.1162-1174.
10. Defude, B., Delot, T., Ilarri, S., Zechinelli, J.L. and Cenerario, N. (2008) 'Data aggregation in VANETs: the VESPA approach', Proceedings of the 5th Annual International Conference on Mobile and Ubiquitous Systems: Computing, Networking, and Services, July, p.13, Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering (ICST).
11. Deng, H., Zeng, Q. and Agrawal, D.P. (2003) 'SVM-based intrusion detection system for wireless ad hoc networks', Proceedings of the 58th IEEE Vehicular Technology Conference (VTC'03), Orlando, FL, USA, 6-9 October, Vol. 3, pp.2147-2151.
12. Dua, S. and Du, X. (2011) Data Mining and Machine Learning in Cybersecurity, Taylor & Francis, USA.
13. Düntgen, C., Behr, T. and Güting, R.H. (2009) 'Berlin MOD: a benchmark for moving object databases', The VLDB Journal, Vol. 18, No. 6, pp.1335-1368.
14. El Zarki, M., Mehrotra, S., Tsudik, G. and Venkatasubramanian, N. (2002) 'Security issues in a future vehicular network', European Wireless, February, Vol. 2, No. 1, pp.1-10.
15. Ghafoor, K.Z., Abu Bakar, K., Van Eenennaam, E., Khokhar, R.H. and Gonzalez, A.J. (2011) 'A fuzzy logic approach to beaconing for vehicular ad hoc networks', International Journal of Telecommunication Systems. Vol. 52, No. 1, pp.139-149.
16. Ghafoor, K.Z., Lloret, J., Bakar, K.A., Sadiq, A.S. and Mussa, S.A.B. (2013) 'Beaconing approaches in vehicular ad hoc networks: a survey', Wireless Personal Communications, Vol. 73, No. 3, pp.885-912.
17. Han, J., Kamber, M. and Pei, J. (2006) Data Mining: Concepts and Techniques, Morgan Kaufmann, CA, USA.
18. Huang, Y. and Lee, W. (2003) 'A cooperative intrusion detection system for ad hoc networks', Proceedings of the 1st ACM Workshop on Security of Ad Hoc and Sensor Networks (SASN'03), Fairfax, VA, USA, pp.135-147
19. Hwang, K., Cai, M., Chen, Y. and Qin, M. (2007) 'Hybrid intrusion detection with weighted signature generation over anomalous internet episodes', Dependable and Secure Computing, IEEE Transactions on, Vol. 4, No. 1, pp.41-55.
20. Keung, Y., Li, B. and Zhang, Q. (2010) 'The intrusion detection in mobile sensor network', Proceedings of the Eleventh ACM International Symposium on Mobile Ad Hoc Networking and Computing, September, pp.11-20, ACM.
21. Khokhar, R.H., Zia, T., Ghafoor, K.Z., Lloret, J. and Shiraz, M. (2013) 'Realistic and efficient radio propagation model for V2X communications', KSII Transactions on Internet & Information Systems, Vol. 7, No. 8, pp.1933-1954.
22. Lauf, A.P., Peters, R.A. and Robinson, W.H. (2010) 'A distributed intrusion detection system for resource-constrained devices in ad-hoc networks', Ad Hoc Networks, Vol. 8, No. 3, pp.253-266.
23. Lauría, E.J. and Tayi, G.K. (2003) 'A comparative study of data mining algorithms for network intrusion detection in the presence of poor quality data', IQ, pp.190-201.
24. Mabu, S., Chen, C., Lu, N., Shimada, K. and Hirasawa, K. (2011) 'An intrusion-detection model based on fuzzy class-association-rule mining using genetic network programming', Systems, Man, and Cybernetics, Part C: Applications and Reviews, IEEE Transactions on, Vol. 41, No. 1, pp.130-139.
25. Maciá-Pérez, F., Mora-Gimeno, F., Marcos-Jorquera, D., Gil-Martínez-Abarca, J.A., Ramos-Morillo, H. and Lorenzo-Fonseca, I. (2011) 'Network intrusion detection system embedded on a smart sensor', Industrial Electronics, IEEE Transactions on, Vol. 58, No. 3, pp.722-732.
26. Mishra, A., Nadkarni, K. and Patcha, A. (2004) 'Intrusion detection in wireless ad hoc networks', Wireless Communications, Vol. 11, No. 1, pp.48-60, IEEE.
27. Mitrokotsa, A. and Dimitrakakis, C. (2013) 'Intrusion detection in MANET using classification algorithms: the effects of cost and model selection', Ad Hoc Networks, Vol. 11, No. 1, pp.226-237.
28. Mitrokotsa, A., Tsagkaris, M. and Douligeris, C. (2008) 'Intrusion detection in mobile ad hoc networks using classification algorithms', Proceedings of the 7th Annual Mediterranean Ad Hoc Networking Workshop (Med-Hoc-Net 2008), 23-27 June, pp.133-144, Springer, Palma de Mallorca, Spain.
29. Muggleton, S. and De Raedt, L. (1994) 'Inductive logic programming: theory and methods', The Journal of Logic Programming, Vol. 19, No. 1, pp.629-679.
30. Nguyen, H.A. and Choi, D. (2008) 'Application of data mining to network intrusion detection: classifier selection model', Challenges for Next Generation Network Operations and Service Management, pp.399-408, Springer, Berlin Heidelberg.
31. Shah, N. and Valiveti, S. (2012) 'Intrusion detection systems for the availability attacks in ad-hoc networks', International Journal of Electronics and Computer Science Engineering (IJECSE), Vol. 1, No. 3pp.1850-1857, ISSN: 2277-1956.
32. Singh, J. and Sharma, N. (2012) 'Wormhole attack detection by using intrusion detection system in VANET', International Journal of Computer Networks and Wireless Communications, Vol. 2, No. 5, pp.638-642.
33. Singh, S. and Bansal, M. (2013) 'Improvement of intrusion detection system in data mining using neural network', International Journal of Advanced Research in Computer Science and Software Engineering, Vol. 3, No. 9, pp.1124-1130.
34. Sumra, I.A., Ahmad, I., Hasbullah, H. and Bin Ab Manan, J.L. (2011) 'Classes of attacks in VANE', Electronics, Communications and Photonics Conference (SIECPC), 2011 Saudi International, pp.1-5, IEEE.
35. Sun, B., Osborne, L., Xiao, Y. and Guizani, S. (2007) 'Intrusion detection techniques in mobile ad hoc and wireless sensor networks', Wireless Communications, Vol. 14, No. 5, pp.56-63, IEEE.
36. Tan, M., Deklerck, R., Cornelis, J. and Jansen, B. (2013) 'Phased searching with NEAT in a time-scaled framework: experiments on a computer-aided detection system for lung nodules', Artificial Intelligence in Medicine, Vol. 59, No. 3, pp.157-167.
37. Tavallaee, M., Stakhanova, N. and Ghorbani, A.A. (2010) 'Toward credible evaluation of anomaly-based intrusion-detection methods', Systems, Man, and Cybernetics, Part C: Applications and Reviews, IEEE Transactions on, Vol. 40, No. 5, pp.516-524.
38. Valiant, L.G. (1984) 'A theory of the learnable', Communications of the ACM, Vol. 27, No. 11, pp.1134-1142.
39. Wang, Y. and Fu, W. (2009) 'Intrusion detection in Gaussian distributed wireless sensor networks', Proceedings of IEEE International Conference on Mobile Ad Hoc and Sensor Systems (MASS), Macau, China, pp.12-15.
40. Wei, M. and Kim, K. (2012) 'Intrusion detection scheme using traffic prediction for wireless industrial networks', Journal of Communications and Networks, Vol. 14, No. 3, pp.310-318.
41. Ye, J. Jieping and Wang, T. (2006) 'Regularized discriminant analysis for high dimensional, low sample size data', Proceedings of the 12th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Philadelphia, PA, USA, 20-23 August.
42. Zhang, Y., Lee, W. and Huang, Y.A. (2003) 'Intrusion detection techniques for mobile wireless networks', Wireless Networks, Vol. 9, No. 5, pp.545-556.
43. Zhang, Y., Meratnia, N. and Havinga, P. (2010) 'Outlier detection techniques for wireless sensor networks: a survey', Communications Surveys & Tutorials, Vol. 12, No. 2, pp.159-170, IEEE.