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Adversarial Attacks on Large Language Models and Defense Mechanisms

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Manage episode 522295605 series 3474671
Inhoud geleverd door HackerNoon. Alle podcastinhoud, inclusief afleveringen, afbeeldingen en podcastbeschrijvingen, wordt rechtstreeks geüpload en geleverd door HackerNoon of hun podcastplatformpartner. Als u denkt dat iemand uw auteursrechtelijk beschermde werk zonder uw toestemming gebruikt, kunt u het hier beschreven proces https://nl.player.fm/legal volgen.

This story was originally published on HackerNoon at: https://hackernoon.com/adversarial-attacks-on-large-language-models-and-defense-mechanisms.
Comprehensive guide to LLM security threats and defenses. Learn how attackers exploit AI models and practical strategies to protect against adversarial attacks.
Check more stories related to cybersecurity at: https://hackernoon.com/c/cybersecurity. You can also check exclusive content about #adversarial-attacks, #llm-security, #defense-mechanisms, #prompt-injection, #user-preference-manipulation, #ai-and-data-breaches, #owasp, #adversarial-ai, and more.
This story was written by: @hacker87248088. Learn more about this writer by checking @hacker87248088's about page, and for more stories, please visit hackernoon.com.
Large Language Models face growing security threats from adversarial attacks including prompt injection, jailbreaks, and data poisoning. Studies show 77% of businesses experienced AI breaches, with OWASP naming prompt injection the #1 LLM threat. Attackers manipulate models to leak sensitive data, bypass safety controls, or degrade performance. Defense requires a multi-layered approach: adversarial training, input filtering, output monitoring, and system-level guards. Organizations must treat LLMs as untrusted code and implement continuous testing to minimize risks.

  continue reading

269 afleveringen

Artwork
iconDelen
 
Manage episode 522295605 series 3474671
Inhoud geleverd door HackerNoon. Alle podcastinhoud, inclusief afleveringen, afbeeldingen en podcastbeschrijvingen, wordt rechtstreeks geüpload en geleverd door HackerNoon of hun podcastplatformpartner. Als u denkt dat iemand uw auteursrechtelijk beschermde werk zonder uw toestemming gebruikt, kunt u het hier beschreven proces https://nl.player.fm/legal volgen.

This story was originally published on HackerNoon at: https://hackernoon.com/adversarial-attacks-on-large-language-models-and-defense-mechanisms.
Comprehensive guide to LLM security threats and defenses. Learn how attackers exploit AI models and practical strategies to protect against adversarial attacks.
Check more stories related to cybersecurity at: https://hackernoon.com/c/cybersecurity. You can also check exclusive content about #adversarial-attacks, #llm-security, #defense-mechanisms, #prompt-injection, #user-preference-manipulation, #ai-and-data-breaches, #owasp, #adversarial-ai, and more.
This story was written by: @hacker87248088. Learn more about this writer by checking @hacker87248088's about page, and for more stories, please visit hackernoon.com.
Large Language Models face growing security threats from adversarial attacks including prompt injection, jailbreaks, and data poisoning. Studies show 77% of businesses experienced AI breaches, with OWASP naming prompt injection the #1 LLM threat. Attackers manipulate models to leak sensitive data, bypass safety controls, or degrade performance. Defense requires a multi-layered approach: adversarial training, input filtering, output monitoring, and system-level guards. Organizations must treat LLMs as untrusted code and implement continuous testing to minimize risks.

  continue reading

269 afleveringen

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