[AISWorld] Episode 72 -- Large Language Model (LLM) Risks and Mitigation Strategies

[Dave Chatterjee, Ph.D.]

Dear Colleagues:

Greetings!

First, I would like to share a significant milestone and thank you for your vital support. The Cybersecurity Readiness Podcast Series has now been downloaded over 10K times and has listeners in 105 countries. The podcast episodes are being used in classrooms and for corporate training and serve as insight sources in research and publications.

As machine learning algorithms continue to evolve, Large Language Models (LLMs) like GPT-4 are gaining popularity. While these models hold great promise in revolutionizing various functions and industries—ranging from content generation and customer service to research and development—they also come with their own set of risks and ethical concerns. In this episode, Rohan Sathe, Co-founder & CTO/Head of R&D at Nightfall.ai, and I review the LLM-related risks and how best to mitigate them.

Action Items and Discussion Highlights

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Large Language Models (LLMs) are built on specialized machine learning models and architectures called transformer-based architectures, and they are leveraged in Natural Language Processing (NLP) contexts.
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There's been a lot of ongoing work in using LLMs to automate customer support activities.
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LLM usage has dramatically shifted to include creative capabilities such as image generation, copywriting, design creation, and code writing.
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There are three main LLM attack vectors: a) Attacking the LLM Model directly, b) Attacking the infrastructure and integrations, and c)Attacking the application.
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Prevention and mitigation strategies include a) Strict input validation and sanitization, b) Isolating the LLM environment from other critical systems and resources, c) Restricting the LLM's access to sensitive resources and limiting its capabilities to the minimum required for its intended purpose; d) Regularly audit and review the LLM's environment and access controls; e) Implement real-time monitoring to promptly detect and respond to unusual or unauthorized activities; and f) Establish robust governance around ethical development and use of LLMs.

I hope you enjoy the episode – https://www.cybersecurityreadinesspodcast.com/large-language-model-llm-risks-and-mitigation-strategies/


Sincerely,

Dave Chatterjee, Ph.D. (https://dchatte.com<https://dchatte.com/>)
Visiting Professor, Pratt School of Engineering, Duke University