SUSELive: Smarter Defense-AI’s Role in Stopping Emerging Security Threats скачать в хорошем качестве

SUSELive: Smarter Defense-AI’s Role in Stopping Emerging Security Threats

As technology evolves at lightning speed, security challenges are constant, shifting from centralized architectures to cloud native, distributed environments. Protecting critical applications and data requires a multi-faceted approach, combining best practices, machine learning for dynamic threat detection, and AI-driven automation to overcome the limitations of static defenses. Join Brent Schroeder, Head of Office of CTO of SUSE and Michael Geller, Distinguished Cyber Security Architect at Radware for this discussion about emerging security challenges in a rapidly changing technological landscape. Key takeaways from this SUSELive include AI/ML is powering Efficacy: Traditional static security models (like signature-based detection) are insufficient against dynamic, evolving attacks. Machine learning and AI-driven solutions are vital for dynamic threat detection and mitigation, as seen in behavioral DDoS protection and bot management, moving beyond static thresholds to adapt to changing attack patterns. Automation: Critical to Beat Evolving Threats : While core security problems remain, their manifestation changes with technological agility. Protecting data and ensuring application resilience under attack are paramount. Automation is crucial for managing the complexity of modern, distributed environments, especially with the high frequency of application updates. Defense-in-Depth and Collaboration: No single solution provides complete enterprise security. A "defense-in-depth" strategy, combining best practices for various components (routers, Kubernetes, APIs, etc.) with automated solutions, is essential. Leveraging partnerships (like SUSE and Radware) and open-source intelligence can significantly enhance threat intelligence and enable faster, more effective responses.