National Science Board

Abstract This paper presents a comprehensive survey of the applications, challenges, and limitations of Generative AI (GenAI) in enhancing threat intelligence within cybersecurity, supported by real-world case studies. We examine a wide range of data sources in Cyber Threat Intelligence (CTI), including security reports, blogs, social media, network traffic, malware samples, dark web data, and threat intelligence platforms (TIPs). This survey provides a full reference for integrating GenAI into CTI. We discuss various GenAI models such as Large Language Models (LLMs) and Deep Generative Models (DGMs) like Variational Autoencoders (VAEs), Generative Adversarial Networks (GANs), and Diffusion Models, explaining their roles in detecting and addressing complex cyber threats. The survey highlights key applications in areas such as malware detection, network traffic analysis, phishing detection, threat actor attribution, and social engineering defense. We also explore critical challenges in deploying GenAI, including data privacy, security concerns, and the need for interpretable and transparent models. As regulations like the European Commission’s AI Act emerge, ensuring trustworthy AI solutions is becoming more crucial. Real-world case studies, such as the impact of the WannaCry ransomware, the rise of deepfakes, and AI-driven social engineering, demonstrate both the potential and current limitations of GenAI in CTI. Our goal is to provide foundational insights and strategic direction for advancing GenAI’s role in future cybersecurity frameworks, emphasizing the importance of innovation, adaptability, and ongoing learning to enhance resilience against evolving cyber threats. Ultimately, this survey offers critical insights into how GenAI can shape the future of cybersecurity by addressing key challenges and providing actionable guidance for effective implementation.

Just as cell phones will soon deliver TV programming and analog TVs will disappear, the PS3 represents another mutation in the evolution of entertainment: game consoles transformed into media centers. Whatever form they might take in 2009, these entertainment systems will be in a world strangely different from 1967, when consoles, the Internet, Wi-Fi, smart cards, DVDs, digital video recorders, MP3 players, and microprocessors had yet to be invented

These remarks will provide a brief preview of some results from a major national field study commissioned as background material for the National Science Board 14th Annual Report, University-Industry Research Relationships: Myths, Realities and Potentials. The Board Report will contain some historical considerations, a fairly comprehensive data analysis of trends over the past 20 years, a discussion of the federal role, and a hypothesis about the future of university/industry relations. The report from the field study will be published separately together with five other specially commissioned studies. The limited time available during this symposium permits presentation of only a few of the interesting statistics generated in the course of the field study, and it should be understood that they remain provisional until final publication of the study. During the field study interviews were conducted at a sample of forty universities and seventy companies. Over 400 instances of research relationships were

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