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Anonymity and Skepticism: The Evolution and Implications of the TOR Network

Authors: Dr. Dalia Mohamed Younis, Krishan kumar Yadav

Published: 2025-03-05 23:49:29.649

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Abstract

In today's era of increasing reliance on mobile devices, chatbots play a vital role due to their simplicity and accessibility. The COVID-19 pandemic has further highlighted the insufficiency of healthcare resources, emphasizing the need for scalable digital solutions. This paper presents an application that leverages deep learning to assist with online disease diagnosis via a chatbot interface. The study focuses on predicting an individual’s susceptibility to heart attacks based on specific health indicators. Using a robust dataset, a deep learning model was developed to analyse key features and accurately assess the risk of cardiac events. The model was then integrated into a chatbot, allowing users to access personalized health insights in real-time. By combining advanced machine learning techniques with an intuitive conversational interface, the proposed system aims to enhance early detection and preventive care. The application is designed to reduce the burden on healthcare systems while empowering individuals with critical health information in a user-friendly format. This approach demonstrates the potential of integrating artificial intelligence with conversational platforms to address pressing health challenges effectively.

Keywords

TOR Network, Internet Anonymity, Online Privacy, Digital Surveillance, Malicious Exit Nodes, Traffic Correlation Attacks

References

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How to Cite

Dr. Dalia Mohamed Younis, Krishan kumar Yadav, (2025-03-05 23:49:29.649). Anonymity and Skepticism: The Evolution and Implications of the TOR Network. JANOLI International Journal of Computer Science and Engineering , Volume rn1ql9uo4BygpjFCAoIa, Issue 1.

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