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@article{191801,
        author = {Ananya Sharma and Anushka Raj and Rishika Solanki},
        title = {Humanised AI for Emotion Based Threat Prediction on the Dark Web},
        journal = {International Journal of Innovative Research in Technology},
        year = {},
        volume = {12},
        number = {no},
        pages = {165-166},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=191801},
        abstract = {A place on internet that is encrypted and anonymous is known as dark web. Dark web is like a untraceable hidden layer of the internet used to store and access the confidential information. Dark was originally built by U.S.  Department of Defense to allow for a secure and anonymous communication among intelligence agencies and government workers. But there are number of incidents which reported the misuse of this platform for conducting the criminal and illegal activities in a hidden manner such as illegal weapons distribution, human trafficking, human organ trafficking, illegal drugs distribution. This paper introduces a novel approach that integrates humanized artificial intelligence (AI) with emotion-based threat prediction to enhance the detection and prevention of potential threats on the dark web. By analyzing emotional cues within dark web communications, the proposed system aims to identify and predict threats more effectively, thereby bolstering cybersecurity measures in this challenging domain.},
        keywords = {humanized AI, Emotion Recognition, Threat Prediction, Dark Web, Affective Computing and Cybersecurity},
        month = {},
        }