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Deep Learning-Based Methodology for Tracking Cybersecurity in Networked Computers

Deep Learning-Based Methodology for Tracking Cybersecurity in Networked Computers

Dharmesh Dhabliya, N. R. Solomon Jebaraj, Sanjay Kumar Sinha, Asha Uchil, Anishkumar Dhablia, Jambi Ratna Raja Kumar, Sabyasachi Pramanik, Ankur Gupta
Copyright: © 2024 |Pages: 16
ISBN13: 9798369326916|ISBN13 Softcover: 9798369347683|EISBN13: 9798369326923
DOI: 10.4018/979-8-3693-2691-6.ch007
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MLA

Dhabliya, Dharmesh, et al. "Deep Learning-Based Methodology for Tracking Cybersecurity in Networked Computers." Risk Assessment and Countermeasures for Cybersecurity, edited by Mohammed Amin Almaiah, et al., IGI Global, 2024, pp. 115-130. https://doi.org/10.4018/979-8-3693-2691-6.ch007

APA

Dhabliya, D., Jebaraj, N. R., Sinha, S. K., Uchil, A., Dhablia, A., Raja Kumar, J. R., Pramanik, S., & Gupta, A. (2024). Deep Learning-Based Methodology for Tracking Cybersecurity in Networked Computers. In M. Almaiah, Y. Maleh, & A. Alkhassawneh (Eds.), Risk Assessment and Countermeasures for Cybersecurity (pp. 115-130). IGI Global. https://doi.org/10.4018/979-8-3693-2691-6.ch007

Chicago

Dhabliya, Dharmesh, et al. "Deep Learning-Based Methodology for Tracking Cybersecurity in Networked Computers." In Risk Assessment and Countermeasures for Cybersecurity, edited by Mohammed Amin Almaiah, Yassine Maleh, and Abdalwali Alkhassawneh, 115-130. Hershey, PA: IGI Global, 2024. https://doi.org/10.4018/979-8-3693-2691-6.ch007

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Abstract

Effective surveillance of cybersecurity is essential for safeguarding the security of computer networks. Nevertheless, due to the increasing scope, complexity, and amount of data created by computer networks, cybersecurity monitoring has become a more intricate issue. The difficulty of correctly and effectively monitoring computer network cybersecurity is a challenge faced by traditional approaches examining a greater quantity of data. Hence, using deep learning models to oversee computer network cybersecurity becomes necessary. This chapter introduces a technique for overseeing the cybersecurity of computer networks by using deep learning knowledge about models. The combination of CNN (convolutional neural networks) and LSTM (long short-term memory) models is used for monitoring the cybersecurity of computer networks. This combination enhances the accuracy of classifying network cybersecurity problems. The CICIDS2017 dataset is used for training and evaluating the suggested model.

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