Neural Network Model Using An Enhanced Whale Optimization Method For Cyber Threat Detection
DOI:
https://doi.org/10.47392/IRJAEH.2025.0022Keywords:
Credential stuffing, Neural Network (NN), Cyber-attackAbstract
In our modern, highly-connected society, cybersecurity is of the utmost importance. With the rapid advancement and increasing integration of technology into our daily lives, the need of cyber security cannot be emphasized enough. Cybersecurity is vital for individual’s protection. Credential stuffing is a sort of cyber assault whereby attackers use previously obtained usernames, keywords and passwords to unlawfully invoke user accounts across many websites. This is plausible as many individuals utilize identical passwords and usernames across several websites. The proposed Enhanced Whale Optimization Algorithm Neural Network (EWOA-NN) model may address the issues of failure detection, prediction, and credential stuffing attacks. A unique optimization method called the neural network is trained using EWOA. After confirming the efficacy of the proposed attack identification model, we will conduct an empirical comparison with respect to certain security research.
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