As enterprises increasingly adopt application-driven business models, security issues have become increasingly prominent. Many network security measures focus too much on human identity and ignore the management of machine identity. This provides opportunities for hackers and may lead to deep system attacks, ultimately leading to network attacks and data leaks. 

In the current digital economy, secure machine-to-machine communications have become even more important. However, with the widespread application of artificial intelligence (AI), new risks also arise. AI's automation and decision-making capabilities, if not properly managed, can lead to management vulnerabilities in TLS certificates and machine identities, increasing security threats.

Participants will gain an in-depth understanding of the challenges posed by rapidly growing machines and the complexities of cloud environments. We will explore the risks that AI can cause in TLS certificate lifecycle management (CLM), including potential errors in automated processes, insufficient anomaly detection, and errors in vulnerability prediction. This workshop will provide attendees with key insights and tools to strengthen their cybersecurity defenses and effectively manage machine identities in an AI-driven environment