BlockHarass-X: A Federated Learning and Blockchain-Enabled Deep Learning Framework for Preventing Cyberstalking and Online Harassment Against Women
Keywords:
Cyberstalking Detection, Online Harassment Against Women, Federated Learning, Blockchain Security, CNN–BiLSTM Model, Privacy-Preserving Deep Learning, Cybercrime Prevention, Hash-Chain Ledger, Digital Safety, Explainable AI (XAI)Abstract
The rapid growth of social media and digital communication platforms has intensified theprevalence of cyberstalking and online harassment against women, posing significant threatsto psychological well-being, privacy, and digital safety. Traditional centralized detection models suffer from privacy leakage, data silos
References
Anti-Defamation League. (2021). Online Hate and Harassment Report.
UN Women. (2020). Cyber Violence Against Women and Girls: A Global Review
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Published
2024-11-20
How to Cite
Mahesh Narayan Sharma,Raj Sinha. (2024). BlockHarass-X: A Federated Learning and Blockchain-Enabled Deep Learning Framework for Preventing Cyberstalking and Online Harassment Against Women . Journal of Computational Analysis and Applications (JoCAAA), 33(08), 2677–2696. Retrieved from https://eudoxuspress.com/index.php/pub/article/view/4441
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