Mingming Chen

Mingming Chen

Assistant Professor at Kansas State University

Biography

I am an assistant professor in Computer Science at Kansas State University. I recently earned my Ph.D. in Computer Science and Engineering from Penn State University. I was honored to be advised by Tom La Porta and Trent Jaeger. I am also grateful for the IBM Research collaboration and guidance from Teryl Taylor and Fred Araujo. My research focuses on the security and trustworthiness of Software-Defined Networking (SDN) control planes. I study how autonomous, software-defined control systems perceive global state, make decisions, and can be misled or protected under adversarial manipulation. Using SDN as a concrete systems substrate, my work uncovers architectural vulnerabilities in centralized control planes and develops built-in defenses that make system perception and actuation trustworthy by construction. My work has appeared in ACM CCS and USENIX Security and has led to the disclosure of multiple CVEs affecting widely used SDN controllers. I have hands-on experience with open-source SDN platforms, having contributed code to OpenDaylight earlier in my career. I also serve on program committees and artifact evaluation boards in the security community.

PhD Openings

I am recruiting 2-3 fully funded PhD students for Fall 2026 and Spring 2027 to design and build a next-generation SDN testbed. Research topics include:

  • Security & Privacy of next-G Network Slicing: Study topology abstraction as a foundational security and privacy interface in network slicing, where incorrect or overly revealing abstractions can lead to SLA violations, isolation failures, and information leakage.
  • Secure-by-Design SDN Control-Plane Mechanisms: Investigate principled redesigns of SDN control-plane mechanisms to address architectural vulnerabilities in network discovery and state maintenance, aiming for security by construction rather than reactive defenses.
  • Information-Flow–Based Security Analysis of SDN Control Planes: Study SDN control-plane security through the lens of information flow, focusing on how operational data propagate across controller components and the data plane, and how violations of intended information boundaries lead to architectural misuse cases.
  • Language-Based Security for Programmable Data Planes: Develop language- and type-based approaches to improve the safety of programmable data planes, with a focus on reasoning about stateful network behavior and preventing unintended data dependencies across network functions.

How to apply: Please email your CV, transcript, and a brief research statement. Email subject: Prospective PhD application.

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