SaTC: EDU: Learning Moving Target Defense Concepts: Teaching and Training Curricula Development Based on Software Defined Networking and Network Function Virtualization

Moving Target Defense (MTD) is a new security concept to increase uncertainty and complexity for attackers, reduce their window of opportunity and increase the costs of their attack efforts. MTD solutions involve a wide-range of advanced technical expertise, which current education models lack. The project from Arizona State University proposes to develop an MTD courseware for both senior undergraduate level and graduate level in computer science focusing on network-based MTD technologies. Additionally, a cloud-based hands-on laboratory will be established to support MTD labs, which will increase access to students and educators in lab environments with limited computer networking and system security capabilities. The proposed MTD curricula will be published as a textbook associating with a MTD lab repository allowing instructors to build a new MTD course or pick part of the teaching materials to incorporate them into their current curricula. The project team will also work with industry partners to develop the course content and provide a Teacher Training workshop to disseminate the course materials. All the created course content and labs will be freely downloadable by instructors and students.

MTD solutions involve technologies in machine learning, artificial intelligence, and big data analysis models, and current education resources in this realm should address these fields. The proposed project will address the research challenge on how to build-out a much-needed hands-on learning module that can be easily deployed on existing cloud service platforms to learn and experiment with new computer networking and security technologies such as Software Defined Networking (SDN), Network Function Virtualization (NFV), and MTD. This project will focus on four interdependent tasks: (a) building the MTD education capability by creating software components to support SDN, NFV, and MTD, and establishing MTD lab repository and APIs to enhance MTD learning outcomes; (b) developing both long-term semester-based course curriculum, and short-term training oriented MTD teaching contents; (c) conducting a comprehensive evaluation plan by involving both internal and external independent evaluators to use the developed course content and labs; and (d) working with industry partners and hosting a Teacher Training workshop to maximally disseminate developed MTD learning contents and hands-on exercises.

Dijiang Huang

Dr. Huang received his Bachelor of Science degree in Telecommunications from Beijing University of Posts & Telecommunications in 1995. He received his Master of Science and PhD degrees from University of Missouri-Kansas City in 2001 and 2004, respectively. Both majored in Computer Science and Telecommunications. He joined ASU in 2005 in the Department of Computer Science and Engineering as an assistant professor. From 2011, he has been an associate Professor in the School of Computing Informatics and Decision Systems Engineering. His current research interests are in computer and network security, mobile ad hoc networks, network virtualization, and mobile cloud computing. Dr. Huang's research is supported by federal agencies NSF, ONR, ARO, and NATO, and organizations such as Consortium of Embedded System (CES), Hewlett-Packard. He is a recipient of ONR Young Investigator Award and HP Innovation Research Program (IRP) Award. He is currently leading the Secure Networking and Computing (SNAC) research group at ASU.