Okonta O. Emmanuel¹✉, Ajani Dele¹ and Okonta I. Love²
¹Department of Computer Education, FCE(T), Asaba, Nigeria
²Department of Educational Foundations, FCE(T), Asaba, Nigeria
Received: May 30, 2023/ Revised: June 30, 2023/Accepted: July 11, 2023
(✉) Corresponding Author: Okey.okonta@fcetasaba-edu.ng
Abstract
Intrusion monitoring is the act of monitoring unwanted traffic on a network or a device, analysing them for signs of possible incidents, which are violations or imminent threats of violation of computer security policies, acceptable use policies, or standard security practices. Intrusion detection is the process of detecting a possible compromise or events occurring in a computer system or network. An IDMS can be a piece of installed software or a physical intelligent appliance that monitors network traffic in order to detect and prevent unwanted activity and events such as illegal and malicious traffic, traffic that violates security policy, and traffic that violates acceptable use policies. This innovative design primarily focused on identifying possible incidents, logging information about them, attempting to stop them, and reporting them to security administrators. In addition, try to inoculate the system to prevent similar attacks using recognisable signature patterns and this will enhance National Security and prevent unwarranted cyber-attacks on organizations and important National resources.
Keywords: Innovative, Intelligent Detection, Monitoring System and National Security.
References
Bao, F, Chen I-R, Chang M, Cho J-H (2012). Hierarchical Trust Management for Wireless Sensor Networks and its applications to trust-based routing and intrusion detection. IEEE Trans Network Server Management 9(2):169–183
Baig, M. &. Kumar. K (2011). “Intrusion Detection in Wireless Networks Using Selected Features,” Int. J. Computing. Sci. Inf. Technol.,2, pp. 1887–1893, 2011.
Bosman, H., Iacca, G., Tejada, A., Wörtche, H. J. and Liotta, A. (2017). Spatial anomaly detection in sensor networks using neighbourhood information. Information Fusion 33:41–56.
Corchado, E. & Herrero, A. (2011). “Neural visualization of network traffic data for intrusion detection,” Appl. Soft Computing., 11(2), 2042–2056.
Denning, D. E (1987). “An intrusion-detection model,” IEEE Transactions on Software Engineering, 13(2), 222–232.
Fu, Y, Yan Z, Cao J, Kone O, Cao X (2017). An automata based intrusion detection method for internet of things. Mob Inf Syst 2017(1750637):13. https://doi.org/10.1155/2017/1750637
Goyal, M. K., Aggarwal, A. & Jain, N. (2012). “Effect of change in rate of genetic algorithm operator on composition of signatures for misuse intrusion detection system,” in 2012 2nd IEEE International Conference on Parallel, Distributed and Grid Computing, 12, 669–672. http://economictimes.indiatimes.com/industry/banking/finance/banking/3-2-million-debit-cards-compromised-sbi-hdfc-bank-icici-yes-bank-and-axis-worst-hit/articleshow /54945561.cms. Accessed 26 Dec 2017.
Krimmling, J. and Peter, S. (2014) Integration and evaluation of intrusion detection for CoAP in smart city applications. In: IEEE Conference on Communications and Network Security (CNS’14), pp 73–78.
Mohanabharathi, M., Kalaikumaran, T. & Karthi, S. (2012), “Feature Selection for Wireless Intrusion Detection System Using Filter and Wrapper Model,” Int. J. Mod. Eng. Res., 2(4), 1552–1556, 2012.
Sun, B., Wu, K., Xiao, Y. and Wang, R. (2007). Integration of mobility and intrusion detection for wireless ad hoc networks. Wiley’s International Journal of Communication Systems 20(6), 695–721
Shaikha, H. K. & Abduallah, W. M. (2017) “Review of intrusion detection systems,” Academic Journal of Nawroz University, vol. 6, no. 3, pp. 106–111.
Wu, S. X. & Banzhaf, W. (2010), “The use of computational intelligence in intrusion detection systems: A review,” Appl. Soft Computing., vol. 10, no. 1, pp. 1–35, Jan. 2010.
Xiao, Y., Shen, X. S. and Du, D. Z. (2007). Wireless Network Security, Springer Science+Business Media, LLC, USA. E-ISBN-10 0-387-33112-3.
How to cite this article
Okonta, O. E., Ajani, D. and Okonta, L. I. (2023). Innovative framework design of an Intelligent Detection and Monitoring System (IDMS) to leverage national security. Science Archives, Vol. 4(3), 190-194. https://doi.org/10.47587/SA.2023.4302
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