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Adversarial Attacks on Large Language Models and Defense Mechanisms

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Manage episode 522295605 series 3474671
Indhold leveret af HackerNoon. Alt podcastindhold inklusive episoder, grafik og podcastbeskrivelser uploades og leveres direkte af HackerNoon eller deres podcastplatformspartner. Hvis du mener, at nogen bruger dit ophavsretligt beskyttede værk uden din tilladelse, kan du følge processen beskrevet her https://da.player.fm/legal.

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 episoder

Artwork
iconDel
 
Manage episode 522295605 series 3474671
Indhold leveret af HackerNoon. Alt podcastindhold inklusive episoder, grafik og podcastbeskrivelser uploades og leveres direkte af HackerNoon eller deres podcastplatformspartner. Hvis du mener, at nogen bruger dit ophavsretligt beskyttede værk uden din tilladelse, kan du følge processen beskrevet her https://da.player.fm/legal.

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 episoder

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