The field of computer science is witnessing significant advancements in AI-driven security and hardware design. Researchers are focusing on developing innovative solutions to mitigate cybersecurity threats and improve the performance of hardware systems. A notable trend is the integration of artificial intelligence and machine learning into medical devices, which enhances diagnostic and treatment facilities but also introduces serious cybersecurity risks. To address these challenges, researchers are proposing novel approaches, such as systems-theoretic and data-driven security analysis, to ensure the security of these devices from the design phase. Additionally, there is a growing emphasis on developing proprietary foundation models in healthcare, which enables organizations to achieve superior clinical performance, maintain robust data governance, and create sustainable competitive advantages. Furthermore, researchers are exploring new methods for detecting hardware trojans and rowhammer attacks, using techniques such as hardware error correction code-based modules and coalescing activation counts. Noteworthy papers include:

• CnC-PRAC, which proposes a novel PRAC implementation that addresses both performance and energy overheads,
• Offensive Robot Cybersecurity, which introduces a groundbreaking approach by advocating for offensive security methods empowered by automation.