Research Mentor: Bing Wang

The mobile era is underway. We are increasing relying on mobile devices in our daily life and work. Our research on secure mobile computing runs the gamut from wireless networks to secure delivery of the correct information at the specific time to targeted users. We focus on two possible REU projects.

Mobile Malware Detection

Mobile malware poses serious threats to personal information and creates challenges in securing network. Traditional network services provide connectivity but do not have any di- rect mechanism for security protection. The emergence of Software-Defined Networking (SDN) provides a unique opportunity to achieve network security in a more efficient and flexible manner. In the first project, we analyze the behaviors of mobile malware, propose several mobile malware detection algorithms, and design and implement a malware detection system using SDN. Our system detects mobile malware by identifying suspicious network activities through real-time traffic analysis, which only requires connection establishment packets. Specifically, our detection algorithms are implemented as modules inside the Open- Flow controller, and the security rules can be imposed in real time. We have tested our system prototype using both a local testbed and GENI infrastructure. Test results confirm that our approach is promising.

Security of Software Defined Networking

Software defined networking (SDN) is a new paradigm in computer networking. It decouples a computer system into a control plane and a data plane: control plane decides how to forward data, while data plane simply forwards data based on decision from the control plane. Existing studies and systems have demonstrated that SDN can bring significant benefits in simplifying network management, enhancing security, virtualizing network functions, and many more. On the other hand, SDN may introduce new security vulnerabilities. In this project, students will explore using SDN for security applications, or explore potential attacks to SDN and counter measures.

Components for Student Participation

Research tasks for REU participants will include learning about smartphone security, security in vehicular ad-hoc networks, building secure networking protocols and eval- uating various security algorithms using simulation, local testbed and GENI infrastructure, a unique virtual laboratory for at-scale networking experimentation that is supported by NSF. Project supervisors along with senior graduate students will work closely with the REU students and provide mentorship.