Mitigating Insecure Outputs in Large Language Models(LLMs): A Practical Educational Module

Author:

Barek MD Abdul1,Rahman Md Mostafizur2,Akter Shapna1,Islam Riad A.B.M Kamrul1,Rahman Md Abdur1,Shahriar Hossain3,Rahman Akond4,Wu Fan5

Affiliation:

1. University of West Florida,Department of Intelligent Systems and Robotics,USA

2. University of West Florida,Dept. of Cybersecurity and Information Technology,USA

3. Center for Cybersecurity, University of West Florida,USA

4. Auburn University,Computer Science and Software Engineering,USA

5. Tuskegee University,Dept. of Computer Science,USA

Funder

National Science Foundation

Publisher

IEEE

Reference21 articles.

1. LIm censorship: A machine learning challenge or a computer security problem?;Glukhov;arXiv preprint,2023

2. Authentic learning for the 21st century: An overview;Lombardi;Educause learning initiative,2007

3. Teaching devops security education with hands-on labware: Automated detection of security weakness in python;Akter,2023

4. Security Risk and Attacks in AI: A Survey of Security and Privacy

5. A comparative study on HIPAA technical safeguards assessment of android mHealth applications

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