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Submit ReviewAI Security Podcast - ChatGPT and other Generative AI use Large Language Model (LLM) but can these AI systems be attacked? ☠ 🤔 . In this 3 part AI Security series from Cloud Security Podcast Original episode, we're going to talk about the importance of AI security and how to protect your Language Model aka llm program from attack. How can LLMs be attacked by malicious threat actors - beyond the phishing email that everyone has been talking about. Who is this episode for? If you work with LLMs used by AI system or working on securing of internal LLM being built; then you would this video helpful in understanding the types of attacks that be used against a LLM.
Useful Resources are listed here: - NIST AI Risk Management Framework - 1.pdf%20">https://nvlpubs.nist.gov/nistpubs/ai/NIST.AI.100-1.pdf - Attack Mitre for LLM - Atlas https://atlas.mitre.org/ - OWASP Top 10 LLM - https://owasp.org/www-project-top-10-for-large-language-model-applications/descriptions/ - The AI Attack Surface Map v1.0 - Daniel Miessler, Unsupervised Learning - https://danielmiessler.com/blog/the-ai-attack-surface-map-v1-0/
YouTube Link to the Episode - https://youtu.be/Yl9qqt9C5lE
Episode ShowNotes, Links and Transcript on Cloud Security Podcast: www.cloudsecuritypodcast.tv
FREE CLOUD BOOTCAMPs on www.cloudsecuritybootcamp.com
Host Twitter: Ashish Rajan (@hashishrajan)
Podcast Twitter - @CloudSecPod @CloudSecureNews
If you want to watch videos of this LIVE STREAMED episode and past episodes - Check out our other Cloud Security Social Channels:
- Cloud Security News
- Cloud Security BootCamp
Spotify TimeStamp for Episode
(00:00) Intro (00:49) LLM Explained (01:40) LLM Application Input Prompts (03:01) Data used by LLM Applications (04:58) LLM Applications Themselves (08:15) Infrastructure used to host LLM Application (11:11) What about Responsive AI (12:05) Ways to protect LLM Applications against these attacks (13:00) Useful Resources for AI Security (13:30) How do you defend against AI Attacks? (13:38) Outro - Thank you for watching & Subscribing
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