15 Security-Focused Articles

Organizes the 10 generative AI security requirements that CISOs and DX executives should understand, and provides decision criteria for selection, implementation, and operation.

Redefines incorrect AI answers not as an accuracy issue, but as safety incidents that can lead to equipment accidents, regulatory violations, and liability.

Organizes business areas such as design information, partner information, and regulated information that are difficult to productionize with a cloud-only configuration.

Organizes practical measures to prevent accidental input of design information, partner information, contracts, and personal information.

Organizes persistence, integrity, and verifiability for recording AI decision processes as internal control evidence.

Presents a solution to personal AI use that cannot be stopped by bans alone: providing safe official AI that can be used for work.

Organizes information classification, input monitoring, permission management, and log aggregation required to protect design information and partner data.

Organizes practical AI evidence management that can withstand internal and external audits from selection, operation, and audit-response perspectives.

Organizes simultaneous compliance with GDPR, China’s Data Security Law, PIPL, CCPA, and export controls.

Organizes a 25-item checklist covering information protection, access management, audit support, incorrect-answer suppression, and incident response.

Organizes next-generation security operations that automate vulnerability monitoring, impact assessment, patch generation, and validation through JVN integration.

Explains how a three-layer AI monitoring architecture improves the safety and reliability of autonomous operations.

Provides a practical framework for defining the boundary between AI autonomy and human review based on business risk.

Explains how SIers and SaaS providers can redesign security operations through AI agent automation to improve efficiency and SLA compliance.

Introduces an AI-agent-driven approach that automates vulnerability detection, patch generation, validation, and risk assessment.