The advent of artificial intelligence (AI) has revolutionized the practice of cyber adversary engagement. This approach, which focuses on active defense and deception strategies, leverages AI technologies to proactively combat threats and gain a strategic advantage in the cyber domain.
AI-powered deception techniques have emerged as a game-changer in cyber adversary engagement. By creating adaptive decoys, and other deceptive assets, defenders can lure adversaries away from critical resources and gather valuable intelligence on their tactics, techniques, and procedures (TTPs)¹. These AI-driven deception systems can dynamically adjust their behavior and appearance to maintain a convincing facade, making it increasingly difficult for attackers to distinguish between real and fake assets².
Moreover, AI algorithms can analyze the vast amounts of data generated by deception environments to identify patterns, anomalies, and potential threats³. This real-time threat intelligence enables defenders to proactively detect and respond to emerging threats, minimizing the impact of successful attacks. By integrating AI-powered deception with other active defense measures, such as threat hunting and incident response, organizations can create a multi-layered, adaptive security posture that keeps pace with evolving adversary tactics.
However, the use of AI in cyber adversary engagement is not limited to defensive applications. Attackers are also leveraging AI to enhance their offensive capabilities, developing smart malware, automated social engineering tools, and other AI-powered threats⁴. This has led to an escalating arms race between attackers and defenders, with each side constantly innovating to outmaneuver the other.
To effectively counter AI-powered threats, human-machine teaming has become a critical aspect of cyber adversary engagement. By combining the intuition, creativity, and contextual understanding of human analysts with the speed, scalability, and pattern recognition capabilities of AI systems, organizations can develop more robust and resilient defenses⁵. This collaborative approach allows human experts to guide and oversee AI-driven active defense and cyber deception strategies, ensuring that they remain aligned with organizational objectives and ethical principles.
As AI continues to transform the cyber adversary engagement landscape, organizations must adapt their active defense and deception strategies to stay ahead of the curve. This requires continuous investment in AI research and development, at HypergameAI we are leading the charge. By embracing AI-driven cyber adversary engagement, organizations can proactively defend against evolving threats and maintain a strong security posture in the face of increasingly sophisticated adversaries.
References:
1. Fraunholz, D., & Schotten, H. D. (2018). Defending web servers with feints, distraction and obfuscation. In International Conference on Computer Network Security (pp. 203-227). Springer, Cham.
2. Bilinski, M., Ferguson-Walter, K., Fugate, S., Gabrys, R., Mauger, J., & Souza, B. (2019). You only lie twice: A multi-round cyber deception game of questionable veracity. In Artificial Intelligence and Machine Learning for Multi-Domain Operations Applications (Vol. 11006, pp. 62-73). SPIE.
3. Ferguson-Walter, K., Fugate, S., Mauger, J., & Major, M. (2019). Game theory for adaptive defensive cyber deception. In Proceedings of the 6th Annual Symposium on Hot Topics in the Science of Security (pp. 1-8).
4. Brundage, M., Avin, S., Clark, J., Toner, H., Eckersley, P., Garfinkel, B., ... & Amodei, D. (2018). The malicious use of artificial intelligence: Forecasting, prevention, and mitigation. arXiv preprint arXiv:1802.07228.
5. Carroll, T. E., & Grosu, D. (2021). Incentive Compatible Online Adversarial Deception for Cyber Human-Machine Teaming Against Insider Threats. In Proceedings of the 11th ACM Workshop on Moving Target Defense (pp. 19-28).
