Defending and Maintaining Artificial Intelligence
AI is transforming cybersecurity by enhancing defensive capabilities while also introducing new threats. CyberEd.io equips enterprises with specialized training in AI security, focusing on strategies to protect against adversarial AI attacks, strengthen AI-driven defenses, and navigate regulatory considerations effectively.
AI brings transformative capabilities, from predictive analytics to automated response.
But it also introduces new risks: adversarial prompts, poisoned datasets, and opaque decision-making that regulators are now scrutinizing. CyberEd.io sessions prepare enterprises to both adopt AI responsibly and defend against AI-enabled threats. Leaders gain governance frameworks; technical teams learn how to red-team models, secure pipelines, and operationalize AI for defense.
Enterprise challenges we address:
Adversarial AI
Attacks on models via poisoning, evasion, and manipulation.
AI Vulnerability Management
Identifying, assessing, and addressing emerging weaknesses in AI systems to ensure security and reliability.
Regulation & governance
Meeting ethical and legal standards for AI adoption.
AI Third-Party Risks
Managing vulnerabilities and threats from external AI solutions that impact organizational integrity.
Secure deployment
Protecting AI/ML pipelines and models in production.
Data integrity & privacy
Safeguarding training datasets from tampering and unauthorized exposure.
Preview Artificial Intelligence (AI) security courses on CyberEd.io
Secure AI 2025: Lessons We've Learned
Dr. Anton Chuvakin of Google Cloud shares insights on securing AI in production environments, adversarial AI use, emerging governance best practices, agentic AI risks, and AI’s impact on cybersecurity resilience in 2025 and beyond.
Establishing Trust & Safety in AI Development
Snyk’s Lawrence Crowther discusses security vulnerabilities in AI development, cloud security best practices, and AI’s role in future cybersecurity developments.
Ethical AI in Cybersecurity
Jayant Narayan and Pedro Tavares examine ethical considerations in AI-powered cybersecurity, focusing on identifying and mitigating bias, enhancing transparency in AI models, and balancing robust security with privacy protection.
How CyberEd.io supports enterprises
With CyberEd Enterprise & CyberEd Custom, organizations gain:
Curated learning paths
For AI security engineers, CISOs, and compliance leaders.
Hands-on labs and simulations
Exploring adversarial ML and secure AI deployments.
Executive briefings
On regulatory and ethical imperatives.
Custom modules
Aligned to industry-specific AI use cases.
At-a-glance
Bundle AI security training into your enterprise program.