Скачать или смотреть LLM Security - The Invisible Battlefield for AI Security

The security landscape for Large Language Models (LLMs), focusing heavily on adversarial attacks and necessary mitigation strategies. The discussion spans various threats, including model poisoning, which involves injecting malicious data during training, and different forms of prompt injection attacks, such as indirect prompt injection that manipulates an LLM to perform unintended actions like data exfiltration. Multiple defence techniques are explored, ranging from security tools and open-source frameworks for AI governance and security to architectural strategies like defense-in-depth for Retrieval-Augmented Generation (RAG) systems and adherence to Zero Trust principles. Furthermore, the texts examine the security trade-offs between using third-party hosted LLM APIs and self-hosting models, noting that while hosted solutions offer built-in safety features, self-hosting provides greater data control and customisation flexibility regarding guardrails and fine-tuning controls.#ai #education #machinelearning #facts #cybersecurity #science