Author
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Author 1
Syed Irtaza Hassnain
Faculty of Science and Technology, Thammasat University Rangsit Center, Pathumthani 12120, Thailand
Summary
Edited Journals
IECE Contributions

Open Access | Research Article | 31 March 2025
Neural Network-Enhanced Machine Learning Applications in Cybersecurity for Real-Time Detection of Anomalous Activities and Prevention of Unauthorized Access in Large-Scale Networks
IECE Transactions on Neural Computing | Volume 1, Issue 1: 55-64, 2025 | DOI: 10.62762/TNC.2025.920886
Abstract
Neural network-enhanced machine learning is revolutionizing cybersecurity by enabling real-time detection of anomalous activities and proactive prevention of unauthorized access in large-scale networks. Traditional security measures often prove ineffectual in the face of the fast-developing threats, as they depend on unchanging rules and signature detections, which can be bypassed by the advanced cyber adversaries. In contrast, neural networks apply deep learning techniques to several data sets including user behavior, network traffic, and system activity, which helps them to spot small irregularities that may mean a potential threat. By feed-forwarding new information on the high-quality tr... More >

Graphical Abstract
Neural Network-Enhanced Machine Learning Applications in Cybersecurity for Real-Time Detection of Anomalous Activities and Prevention of Unauthorized Access in Large-Scale Networks