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Adversarial Attacks on Large Language Models and Defense Mechanisms

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Manage episode 522295605 series 3474671
Content provided by HackerNoon. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by HackerNoon or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://ro.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 episoade

Artwork
iconDistribuie
 
Manage episode 522295605 series 3474671
Content provided by HackerNoon. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by HackerNoon or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://ro.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 episoade

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