The cybersecurity industry has utilized Artificial Intelligence (AI) for over two decades, applying it across various domains such as spam filtering, malware detection, and intrusion detection to enhance performance through automation, speed, scalability, and adaptability. While AI's impact has been predominantly in reactive cybersecurity measures, new AI technologies are promising for proactive security efforts, including advanced threat intelligence, security risk management, and heightened security awareness.
Nevertheless, the path to successfully using AI for cybersecurity is paved with many pitfalls, and successful applications have been developed at the cost of many failures. This success requires advanced knowledge, skills and experience in both AI and cybersecurity, which a few specialized organizations have been able to gather and reap the benefits from. In the context of the current AI hype, a widespread interest has risen into exploring the possible applications of AI, including those to cybersecurity. Many organizations seek to know if and how they could use AI to improve their security posture. This turns out to be challenging without field experience, considering the shortage of skilled AI and security experts.
This report aims to provide organizations with insights into AI's capabilities and potential benefits for cybersecurity, detailing existing applications, their maturity levels, and associated challenges. AI's effectiveness in improving threat detection and endpoint security is noted, though its applications in threat intelligence and vulnerability management remain nascent. The report emphasizes the importance of a meticulous development process and the integration of AI into security measures, underscoring the necessity of aligning AI solutions with business objectives, thorough understanding of data, and testing early prototypes in real-world settings. Developing cross-competency among experts in AI and cybersecurity is crucial for success.
Looking ahead, emerging AI technologies like Large Language Models (LLMs) are set to revolutionize cybersecurity applications by supporting security education, analytics, threat intelligence, and vulnerability management. These models promise to enhance the processing and correlation of information from vast amounts of unstructured data, potentially leading to more autonomous and complex task management. Nonetheless, as AI applications evolve, they will encounter new ethical, technical, and regulatory challenges that could impede progress.
The report was conducted in collaboration with the National Emergency Supply Agency.