@inproceedings{akram-jyoti-2023-revolutionizing,
    title = "Revolutionizing Authentication: Harnessing Natural Language Understanding for Dynamic Password Generation and Verification",
    author = "Al-Rumaim, Akram  and
      D. Pawar, Jyoti",
    editor = "D. Pawar, Jyoti  and
      Lalitha Devi, Sobha",
    booktitle = "Proceedings of the 20th International Conference on Natural Language Processing (ICON)",
    month = dec,
    year = "2023",
    address = "Goa University, Goa, India",
    publisher = "NLP Association of India (NLPAI)",
    url = "https://preview.aclanthology.org/fix-sig-urls/2023.icon-1.67/",
    pages = "670--678",
    abstract = "In our interconnected digital ecosystem, API security is paramount. Traditional static password systems once used for API authentication, face vulnerabilities to cyber threats. This paper explores Natural Language Understanding (NLU) as a tool for dynamic password solutions, achieving 49.57{\%} accuracy. It investigates GPT-2 for dynamic password generation and innovative NLU-based verification using a set of specific criteria and threshold adjustments. The study highlights NLU{'}s benefits, challenges, and prospects in enhancing API security. This approach is a significant stride in safeguarding digital interfaces amidst evolving Cyber Security threats. Keywords: Cyber Security, Authentication, API Security, Generative AI, Dynamic Passwords, Passwords Verification, NLU"
}