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Dynamics 365 ERP - Development

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Apr 9, 2024

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AI Summary

  • Large Language Models (LLMs) are computational systems that process and generate text by learning from vast datasets. They are integral in driving business innovations and enhancing operational efficiencies.
  • LLMs introduce new cybersecurity challenges that need to be addressed.
  • 'Securing' LLMs involves safeguarding data integrity, ensuring operational continuity, maintaining confidentiality, and protecting system security.
  • Prompt injection is a cybersecurity threat where hackers use deceptive instructions to trick LLMs into revealing sensitive information or generating harmful code.
  • Prevention measures for prompt injection include manual inspection of instructions, limiting LLMs' ability to interact with unpredictable online content, and testing LLM models with known prompt injection techniques.
  • Training data poisoning occurs when bad actors introduce deceptive information into LLMs, leading to the unintentional dissemination of false facts. Countermeasures for data poisoning include sourcing training data from reliable channels, employing sandboxing techniques, and continuously monitoring LLMs' output.
  • Permission issues with plugins can pose risks if excessive permissions are granted. Recommendations for mitigating these risks include assigning only essential access rights, implementing user consent protocols, and minimizing plugin interaction.
  • Data leakage in AI models is a rare but potential issue. Preventive measures for data leakage include routinely cleansing data ingested by LLMs, implementing robust security measures, and training LLM models with synthetic data.
  • Excessive agency in LLMs can lead to undesirable decisions. Suggestions for handling this issue include granting LLMs the essential level of autonomy, incorporating human oversight, and monitoring LLM activities.
  • Red teaming is an important component for ensuring the resilience and security of AI infrastructure. Prioritizing threat modeling, developing realistic attack scenarios, and leveraging expertise from various domains are essential for effective red teaming.
  • Developers, CIOs, and security teams need to recognize and mitigate the novel risks introduced by LLMs. Taking a proactive, preventative approach to security and collaborating closely between CIOs and CSOs is crucial for secure LLM implementations.

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