Dr. Fanxin Kong

Interests: Cyber-Physical Systems and Internet-of-Things. (i) Security: attack detection and real-time recovery. (ii) Real-time and resource management: energy-efficiency, workload scheduling, and mechanism design. (iii) Intelligent CPS: trajectory planning and task allocation.

Techniques: Machine learning, formal methods, control, optimization, and algorithm design.

Applications: Autonomous systems including autonomous vehicles and drones.

Email: fkong03 at syr dot edu

Other profiles: Google Scholar, dblp Entry

  • Short Bio

Dr. Fanxin Kong is a tenure-track assistant professor in the Department of Electrical Engineering and Computer Science at Syracuse University. Before that, he worked with Prof. Insup Lee as a postdoctoral researcher in the PRECISE Center at University of Pennsylvania. He obtained his Ph.D. in Computer Science at McGill University under the supervision of Prof. Xue Liu. He is serving as the Information Director of ACM SIGBED.

New! I am looking for self-motivated PhD students. Visiting students and scholars are all welcome. If you are interested in my research and working with me, please directly contact me with your CV.

  • Testbdes and Demos (More)

Autonomous system testbeds: self-driving car, drone, self-balancing two wheeler, indoor localization

No recovery vs real-time attack recovery, SVL simulator

No recovery vs real-time attack recovery, indoor autonomous vehicles

Drone path recovery under GPS attacks, Quad_SimCon simulator

[Nov. 2022] Travel grant: Mengyu has received the travel grant to RTSS 2022. Congratulations!

[Otc. 2022] Demo: our new demos on real-time and trusted attack recovery for autonomous cyber-physical systems are online! [Link]

[Oct. 2022], Award: our Real-Time Attack Recovery work has won the Best Scientific Research Award at ACM SIGBED Student Research Competition (SRC) 2022. Congratulations to Lin!

[Sep. 2022], Paper: our paper "Fail-Safe: Securing Cyber-Physical Systems against Hidden Sensor Attacks", is accepted by the 43rd IEEE Real-Time Systems Symposium (RTSS), 2022. Congratulations to Mengyu and all! See you at Houston!

[Sep. 2022], Award: I receive the Extension Award of AFRL VFRP! Many thanks, AFRL!!!

[Aug. 2022], Service: Invited to serve as a TPC member for the 14th ACM International Conference on Future Energy Systems (ACM E-Energy 2023). Please consider to submit your best work!

[July 2022], Service: Invited to serve as a TPC member for the 29th IEEE Real-Time and Embedded Technology and Applications Symposium (RTAS 2023). Please consider to submit your best work!

[July 2022], Grant: our project on Sensor Attack Detection and Recovery in Cyber-Physical Systems is funded by NSF! Many thanks, NSF!!!

[July 2022], Talk: I gave two talks, "Real-time Attack-Resilient Cyber-Physical Systems", at the Information Institute and the Fifth International Workshop on Design Automation for Cyber-Physical Systems (DACPS) @DAC'22.

[July 2022], Service: I will serve as a session co-chair for "Can We Achieve a Secure, Robust, and Energy-efficient Cloud-Edge Continuum?" at DAC'22. See you at San Francisco!

[June 2022], Workshop: I organized NSF Workshop on Towards Scalable Design of Resilient Mission-Critical IoT Systems.

[June 2022], Award: I receive the award of AFRL VFRP! Many thanks, AFRL!!!

[March 2022], Award: our work "Adaptive Window-Based Sensor Attack Detection for Cyber-Physical Systems" has won the first place in Oral Presentation Competition at 2022 ECS Research Day. Congratulation to Lin!

Attack Recovery:

  1. [EMSOFT'21] Lin Zhang, Pengyuan Lu, Fanxin Kong, Xin Chen, Oleg Sokolsky and Insup Lee, "Real-Time Attack-Recovery for Cyber-Physical Systems using Linear-Quadratic Regulator", in the 21st ACM SIGBED International Conference on Embedded Software, 2021.

  2. [RTSS'20] Lin Zhang, Xin Chen, Fanxin Kong, and Alvaro A. Cardenas, "Real-Time Recovery for Cyber-Physical Systems using Linear Approximations", in the 41st IEEE Real-Time Systems Symposium, 2020.

  3. [ICCPS'18] Fanxin Kong, Meng Xu, James Weimer, Oleg Sokolsky, and Insup Lee, "Cyber-Physical System Checkpointing and Recovery", in the 9th ACM/IEEE International Conference on Cyber-Physical Systems, 2018.

Attack Detection:

  1. [DAC'22] Lin Zhang, ZifanWang, Mengyu Liu, and Fanxin Kong, "Adaptive Window-Based Sensor Attack Detection for Cyber-Physical Systems", in the 59th Design Automation Conference (DAC), 2022.

  2. [RTAS'21] Francis Akowuah and Fanxin Kong, "Real-Time Adaptive Sensor Attack Detection in Autonomous Cyber-Physical Systems", in the 27th IEEE Real-Time and Embedded Technology and Applications Symposium, 2021.

  3. [DAC'20] Tianjia He, Lin Zhang, Fanxin Kong, and Asif Salekin, "Exploring Inherent Sensor Redundancy for Automotive Anomaly Detection", in the 57th Design Automation Conference, 2020.

Hidden Attack Defense:

  1. [RTSS'22] Mengyu Liu, Lin Zhang, Pengyuan Lu, Kaustubh Sridhar, Fanxin Kong, Oleg Sokolsky and Insup Lee, "Fail-Safe: Securing Cyber-Physical Systems against Hidden Sensor Attacks", in the 43rd IEEE Real-Time Systems Symposium (RTSS), 2022.

Intelligent CPS:

  1. [ICAR'21] Chen Luo, Qinwei Huang, Fanxin Kong, Simon Khan, Qinru Qiu, "Applying Machine Learning in Designing Distributed Auction for Multi-agent Task Allocation with Budget Constraints", in the 20th International Conference on Advanced Robotics, 2021.

  2. [DASC'21] Mohamad Hani Sulieman, M Cenk Gursoy and Fanxin Kong, "Antenna Pattern Aware UAV Trajectory Planning Using Artificial Potential Field", in the IEEE/AIAA 40th Digital Avionics Systems Conference, 2021.

  • Grants

  1. PI, Sensor Attack Detection and Recovery in Cyber-Physical Systems, NSF, 07/2022 - 06/2025.

  2. PI, Real-Time and Trusted Recovery for Complex Cyber-Physical Systems, AFRL, 09/2022 - 10/2022.

  3. PI, Real-Time Attack-Resilience for Cyber-Physical Systems, AFRL, 06/2022 - 08/2022.

  4. PI, Towards Scalable Design of Resilient Mission-Critical IoT Systems, NSF, 10/2020 - 09/2022.

  5. Co-PI, Efficient and Fair Decentralized Task Allocation Algorithms for Autonomous Vehicles: A Machine Learning Based Approach, AFOSR, 10/2020 - 09/2022.

  6. PI, Techniques for Deploying Mission Critical IoT Applications, transferred, NSF, 03/2017 - 02/2021.