• P-ISSN 0974-6846 E-ISSN 0974-5645

Indian Journal of Science and Technology


Indian Journal of Science and Technology

Year: 2024, Volume: 17, Issue: 15, Pages: 1596-1605

Original Article

Proactive Analysis and Detection of Cyber-attacks using Deep Learning Techniques

Received Date:30 November 2023, Accepted Date:23 March 2024, Published Date:15 April 2024


Objectives: This study objective is to create a proactive forensic framework with a classification model to identify the malicious content to avoid cyber-attacks. Methods: In this proposed work, a novel framework is introduced to analyze and detect network attacks before it happens. It monitors the network packet flow, captures the packets, analyzes the packet flow proactively, and detects cyber-attacks using different machine learning algorithms and Deep Convolution Neural network (CNN) technique. The KDD dataset is used in this experiment with 30% for testing and 80% for training. Findings: The simulation results show that the detection percentage of the proposed framework reaches a maximum of 95.92% in different scenarios. It is approximately 10% higher than the existing proactive frameworks for example Gawand’s model, Ahmetoglu’s model and many more. Novelty and applications: The proposed framework is a proactive model which detects the cyber-attack in prior to avoid cyber-attacks. The deep CNN model highly efficient for detecting cyber-attack.

Keywords: Proactive Forensic Framework, Deep CNN, Classification Algorithms, Cyber attack detection, Intrusion Detection System


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© 2024 Abirami et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Published By Indian Society for Education and Environment (iSee)


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