Errin Fulp

Dr. Errin Fulp  is a Professor in the Department of Computer Science at Wake Forest University. He earned his PhD in Computer and Electrical Engineering from North Carolina State University in 1999. His professional experience includes roles as a Research Scientist at Pacific Northwest National Laboratory (PNNL) and Cisco Systems, and he currently serves as the Scholar in Residence at Centripetal Networks.

Dr. Fulp’s research focuses on intelligence-driven approaches to computer security and the development of resilient, dynamically managed computer networks. His work has been supported by a range of public agencies and private companies, including the Department of Energy (DOE), National Science Foundation (NSF), Defense Advanced Research Projects Agency (DARPA), Cisco Systems, and Centripetal Networks.

Dr. Fulp’s contributions have been recognized with several prestigious awards, including the Wake Forest Reid-Doyle Prize, the URECA Mentorship Award for Undergraduate Research, the DOE CAREER Award, the IEEE ACSOS Award, and the IEEE MILCOM Best Paper Award. He is also the author of multiple security- and network-oriented patents and co-founder of a start-up specializing in computer security.

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Teaching

Classes taught:

• CSC 250 – Computer Systems I
• CSC 343 – Internet Protocols
• CSC 348 – Computer Security

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Publications

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Research

Intelligence-driven security leverages Cyber Threat Intelligence (CTI) to enhance situational awareness and inform proactive defense strategies. By analyzing diverse intelligence sources, such as Indicators of Compromise (IoCs), attack patterns, and adversary Tactics, Techniques, and Procedures (TTPs), organizations can identify threats in real time and adapt defenses accordingly. Moving beyond reactive measures, intelligence-driven security enables predictive and autonomic responses to emerging threats. To address the growing challenges of scale and the increasing sophistication of adversarial tactics, we are investigating the use of nature-inspired design principles, such as genetic algorithms for optimizing defense strategies, ant colony optimization for dynamic resource allocation in response to attacks, and AI agency for autonomous decision-making in threat detection and mitigation. These approaches enhance adaptability and efficiency, enabling defenses to process large volumes of data from multiple sources with minimal latency. By facilitating timely, automated decisions, intelligence-driven strategies mitigate risks, counter sophisticated threats, and build resilience across diverse operational environments.