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@article{188928,
        author = {Mrs .Poonam M. Ramgirwar and Ms.Priya P. Borade and Ashwini Shinde},
        title = {Exploring Dual-Use Risks and Sustainable Deployment of Large Language Models: Advances in Generative AI for Cybersecurity, Human-Robot Interaction, and Environmental Management},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {12},
        number = {7},
        pages = {3758-3769},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=188928},
        abstract = {This paper provides a comprehensive examination of the advancements, challenges, and implications associated with large language models (LLMs) and generative artificial intelligence (AI) across multiple application domains. Emphasizing both the beneficial and potentially harmful uses of these technologies, this research surveys recent literature in cybersecurity, human-robot interaction, synthetic data augmentation, environmental impact mitigation, and AI model alignment. The study highlights critical issues such as dual-use risks of LLMs, adversarial vulnerabilities, privacy concerns, computational sustainability, and the integration of new hardware architectures. Drawing from a diverse set of case studies and empirical findings, the analysis underscores the importance of responsible AI deployment practices, including transparency, explainability, and regional workload management. The paper further explores cutting-edge applications ranging from robotic artistic creation to personalized fashion recommendations and multimedia content generation. Recommendations are provided to guide future research focused on enhancing security, ethical governance, and ecological sustainability in generative AI development. Ultimately, this work serves as a pivotal reference for researchers and practitioners aiming to harness the transformative potential of LLMs while addressing their complex technical and societal challenges.},
        keywords = {},
        month = {December},
        }