To protect their AI systems, businesses can adopt several strategies. These include subjecting models to adversarial training, securing virtual repositories, training employees, masking AI models, using multilayered threat detection, and embedding security and privacy. The article emphasizes the importance of adapting new protocols and applying technical controls and security education to build a resilient defense against attacks on AI models.
Key takeaways:
- Cybercriminals can exploit AI models through methods such as data poisoning, evasion attacks, model theft, supply chain compromise, and backdoor AI models.
- About 20% of businesses have suffered an attack on their AI models in the past 12 months.
- Organizations can protect their AI systems by subjecting models to adversarial training, securing virtual repositories, training employees, masking AI models, using multilayered threat detection, and embedding security and privacy.
- AI models share an attack surface just like unpatched software and human error, and anything subject to manipulation should bring mindful awareness to the need for applying technical controls and security education.