The AI-Cybersecurity Nexus - Opportunities, Challenges, and Solutions Artificial Intelligence (AI) is revolutionizing cybersecurity, offering enhanced threat detection, proactive prevention, and streamlined response mechanisms. In this keynote, we will explore how AI is reshaping the cybersecurity landscape, especially IoT security, enabling faster incident resolution, more intuitive security tools, and greater overall efficiency. We will share key insights into what works, what doesn’t, and lessons learned from real-world implementations. However, while AI strengthens cybersecurity, it also introduces new vulnerabilities—adversarial AI, automated cyberattacks, and novel threat vectors that traditional defenses struggle to address. We will examine these emerging risks and the evolving tactics of malicious actors who leverage AI against security systems. Finally, this session will present actionable solutions to mitigate AI-driven threats, including fighting AI with AI, platformization, precision AI, adaptive defense strategies, responsible AI deployment, and the integration of AI with human intelligence to create more resilient security frameworks. Join us as we navigate the AI-cybersecurity nexus and chart a course toward a safer digital future.

Speaker's Biography: Dr. May Wang is the Chief Technology Officer for IoT Security at Palo Alto Networks, where she leads innovation in AI-driven cybersecurity solutions. She is the co-founder of Zingbox, the industry’s first AI-powered IoT security company, which was acquired by Palo Alto Networks in 2019. Before founding Zingbox, Dr. Wang served as a Principal Architect in the Cisco CTO Office. Dr. Wang holds a Ph.D. in Electrical Engineering from Stanford University and has received numerous accolades, including being recognized as the 2023 AI Entrepreneur of the Year by VentureBeat.

View More Papers

L-HAWK: A Controllable Physical Adversarial Patch Against a Long-Distance...

Taifeng Liu (Xidian University), Yang Liu (Xidian University), Zhuo Ma (Xidian University), Tong Yang (Peking University), Xinjing Liu (Xidian University), Teng Li (Xidian University), Jianfeng Ma (Xidian University)

Read More

Sheep's Clothing, Wolf's Data: Detecting Server-Induced Client Vulnerabilities in...

Fangming Gu (Institute of Information Engineering, Chinese Academy of Sciences), Qingli Guo (Institute of Information Engineering, Chinese Academy of Sciences), Jie Lu (Institute of Computing Technology, Chinese Academy of Sciences), Qinghe Xie (Institute of Information Engineering, Chinese Academy of Sciences), Beibei Zhao (Institute of Information Engineering, Chinese Academy of Sciences), Kangjie Lu (University of Minnesota),…

Read More

Evaluating LLMs Towards Automated Assessment of Privacy Policy Understandability

Keika Mori (Deloitte Tohmatsu Cyber LLC, Waseda University), Daiki Ito (Deloitte Tohmatsu Cyber LLC), Takumi Fukunaga (Deloitte Tohmatsu Cyber LLC), Takuya Watanabe (Deloitte Tohmatsu Cyber LLC), Yuta Takata (Deloitte Tohmatsu Cyber LLC), Masaki Kamizono (Deloitte Tohmatsu Cyber LLC), Tatsuya Mori (Waseda University, NICT, RIKEN AIP)

Read More