Train, tune and distribute models with generative AI and machine learning capabilities
The rapidity and discontinuity of innovation and technological advancement and adoption of Generative AI (GenAI) Large Language Models (LLMs) have introduced an exponentially hyper-complex landscape of security challenges. Several of the challenges beyond more traditional data privacy and security issues came to the fore with the recent launch of DeepSeek and the challenges for transparency and reliability of GenAI LLMs and Agents. This white paper examines some of the technical aspects of these issues, focusing on identity confusion, data privacy, shadow GenAI risk for enterprise, national security concerns, cybersecurity vulnerabilities, and regulatory compliance. We will also explore the integration of digital identity and blockchain technologies for GenAI LLM agents to address some of these security challenges and industry pain points and meet growingly stringent regulatory requirements.
AI security is not just about traditional cybersecurity anymore. The rise of GenAI and LLMs has created new risks that need better transparency, regulation, and identity verification solutions: possibly using blockchain technology.