AI Data Security: Protecting AI Models and Sensitive Data
Blog post from Duality
Artificial intelligence (AI) is revolutionizing industries by driving innovation and efficiency, but it also introduces complex data security challenges. AI systems require large volumes of sensitive data for model training and operation, making them susceptible to risks such as data poisoning, leakage, and unauthorized access. Effective AI data security involves implementing controls to protect the confidentiality, integrity, and availability of data used in AI systems. It differs from traditional data security by addressing new assets like model artifacts and attack vectors such as model inversion and extraction. Organizations can safeguard sensitive AI data by securing the entire data supply chain, employing privacy-preserving techniques, and ensuring governance and monitoring across the AI lifecycle. Duality Technologies offers solutions to enhance AI data security by using privacy-enhancing technologies, allowing organizations to collaborate and gain insights without compromising data integrity or compliance.
| Trend | Post Mentions | Total Month Mentions | Posts | Companies | MoM |
|---|---|---|---|---|---|
| Vector Search | 16 | 3,215 | 679 | 175 | +33% |
| RAG | 5 | 2,000 | 386 | 114 | +12% |
| AI Model Fine-tuning | 2 | 1,167 | 231 | 79 | +5% |
| LLM | 2 | 7,531 | 1,250 | 268 | +26% |
| Observability | 2 | 4,660 | 984 | 209 | +14% |
| Secrets Management | 2 | 1,946 | 398 | 127 | +28% |
| AI Guardrails | 1 | 479 | 187 | 58 | +7% |
| Data Pipeline | 1 | 1,290 | 393 | 99 | +171% |
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