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内容由Deirdre Connolly, Thomas Ptacek, David Adrian, Deirdre Connolly, Thomas Ptacek, and David Adrian提供。所有播客内容(包括剧集、图形和播客描述)均由 Deirdre Connolly, Thomas Ptacek, David Adrian, Deirdre Connolly, Thomas Ptacek, and David Adrian 或其播客平台合作伙伴直接上传和提供。如果您认为有人在未经您许可的情况下使用您的受版权保护的作品,您可以按照此处概述的流程进行操作https://zh.player.fm/legal
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Cryptanalyzing LLMs with Nicholas Carlini

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内容由Deirdre Connolly, Thomas Ptacek, David Adrian, Deirdre Connolly, Thomas Ptacek, and David Adrian提供。所有播客内容(包括剧集、图形和播客描述)均由 Deirdre Connolly, Thomas Ptacek, David Adrian, Deirdre Connolly, Thomas Ptacek, and David Adrian 或其播客平台合作伙伴直接上传和提供。如果您认为有人在未经您许可的情况下使用您的受版权保护的作品,您可以按照此处概述的流程进行操作https://zh.player.fm/legal

'Let us model our large language model as a hash function—'
Sold.
Our special guest Nicholas Carlini joins us to discuss differential cryptanalysis on LLMs and other attacks, just as the ones that made OpenAI turn off some features, hehehehe.
Watch episode on YouTube: https://youtu.be/vZ64xPI2Rc0
Transcript: https://securitycryptographywhatever.com/2025/01/28/cryptanalyzing-llms-with-nicholas-carlini/
Links:
- https://nicholas.carlini.com
- “Stealing Part of a Production Language Model”: https://arxiv.org/pdf/2403.06634
- ‘Why I attack"’: https://nicholas.carlini.com/writing/2024/why-i-attack.html
- “Cryptanalytic Extraction of Neural Network Models”, CRYPTO 2020: https://arxiv.org/abs/2003.04884
- “Stochastic Parrots”: https://dl.acm.org/doi/10.1145/3442188.3445922
- https://help.openai.com/en/articles/5247780-using-logit-bias-to-alter-token-probability-with-the-openai-api
- https://community.openai.com/t/temperature-top-p-and-top-k-for-chatbot-responses/295542
- https://opensource.org/license/mit
- https://github.com/madler/zlib
- https://ai.meta.com/blog/yann-lecun-ai-model-i-jepa/
- https://nicholas.carlini.com/writing/2024/how-i-use-ai.html
"Security Cryptography Whatever" is hosted by Deirdre Connolly (@durumcrustulum), Thomas Ptacek (@tqbf), and David Adrian (@davidcadrian)

  continue reading

章节

1. Mathematical Attacks on AI Security (00:00:00)

2. AI Model Extraction and Security (00:12:07)

3. Model Extraction Security Mechanism Analysis (00:16:11)

4. Model Extraction Attack Methodology Discussion (00:29:18)

5. Training Data Extraction Attack Methodology (00:39:00)

6. Data Poisoning Attacks and Defenses (00:50:59)

7. AI Security Defense Challenges and Strategies (00:59:24)

8. Exploring AI Model Capabilities (01:06:20)

9. Challenges in AI Model Security (01:15:21)

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Artwork
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Fetch error

Hmmm there seems to be a problem fetching this series right now. Last successful fetch was on November 11, 2025 16:14 (1M ago)

What now? This series will be checked again in the next day. If you believe it should be working, please verify the publisher's feed link below is valid and includes actual episode links. You can contact support to request the feed be immediately fetched.

Manage episode 463607233 series 2956114
内容由Deirdre Connolly, Thomas Ptacek, David Adrian, Deirdre Connolly, Thomas Ptacek, and David Adrian提供。所有播客内容(包括剧集、图形和播客描述)均由 Deirdre Connolly, Thomas Ptacek, David Adrian, Deirdre Connolly, Thomas Ptacek, and David Adrian 或其播客平台合作伙伴直接上传和提供。如果您认为有人在未经您许可的情况下使用您的受版权保护的作品,您可以按照此处概述的流程进行操作https://zh.player.fm/legal

'Let us model our large language model as a hash function—'
Sold.
Our special guest Nicholas Carlini joins us to discuss differential cryptanalysis on LLMs and other attacks, just as the ones that made OpenAI turn off some features, hehehehe.
Watch episode on YouTube: https://youtu.be/vZ64xPI2Rc0
Transcript: https://securitycryptographywhatever.com/2025/01/28/cryptanalyzing-llms-with-nicholas-carlini/
Links:
- https://nicholas.carlini.com
- “Stealing Part of a Production Language Model”: https://arxiv.org/pdf/2403.06634
- ‘Why I attack"’: https://nicholas.carlini.com/writing/2024/why-i-attack.html
- “Cryptanalytic Extraction of Neural Network Models”, CRYPTO 2020: https://arxiv.org/abs/2003.04884
- “Stochastic Parrots”: https://dl.acm.org/doi/10.1145/3442188.3445922
- https://help.openai.com/en/articles/5247780-using-logit-bias-to-alter-token-probability-with-the-openai-api
- https://community.openai.com/t/temperature-top-p-and-top-k-for-chatbot-responses/295542
- https://opensource.org/license/mit
- https://github.com/madler/zlib
- https://ai.meta.com/blog/yann-lecun-ai-model-i-jepa/
- https://nicholas.carlini.com/writing/2024/how-i-use-ai.html
"Security Cryptography Whatever" is hosted by Deirdre Connolly (@durumcrustulum), Thomas Ptacek (@tqbf), and David Adrian (@davidcadrian)

  continue reading

章节

1. Mathematical Attacks on AI Security (00:00:00)

2. AI Model Extraction and Security (00:12:07)

3. Model Extraction Security Mechanism Analysis (00:16:11)

4. Model Extraction Attack Methodology Discussion (00:29:18)

5. Training Data Extraction Attack Methodology (00:39:00)

6. Data Poisoning Attacks and Defenses (00:50:59)

7. AI Security Defense Challenges and Strategies (00:59:24)

8. Exploring AI Model Capabilities (01:06:20)

9. Challenges in AI Model Security (01:15:21)

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