Cong Pu

Assistant Professor, Marshall University

Talk Title: Detect Me If You Can: Mitigating DoS Attacks in the Energy Harvesting Internet of Things

 

Biography:

CONG PU received the B.S. degree in Computer Science and Technology from Zhengzhou University, China, in 2009, and the M.S. and Ph.D. degrees in Computer Science from Texas Tech University in 2013 and 2016, respectively. From 2014 to 2016, he was an Instructor with the Department of Computer Science, Texas Tech University, while he was working towards Ph.D. degree. He is currently an Assistant Professor with the Department of Computer Sciences and Electrical Engineering, Marshall University, Huntington, WV, USA. His primary research interests include cryptography, network security, wireless networks, mobile computing, and information-centric networking. He served as a technical program committee member in many international conferences. He was a reviewer for many IEEE, ACM, Elsevier, and Springer journals. He is also serving as Associate Editor of several journals. He received 2015 Helen Devitt Jones Excellence in Graduate Teaching Award at Texas Tech University. He was the recipient of 2018 NASA WVSGC Research Initiation Grant, 2020 NASA EPSCoR Research Seed Grant, 2020 Open Education Resources (OER) Grant Award, 2018 John Marshall Summer Scholar Award. He received 2019 IEEE ICDIS Best Paper Award. He was the Winner of 2017 Design for Delight (D4D) Innovation Challenge Competition as a Faculty Coach (Marshall University and Intuit Inc.). He was a member of Computer Science Workgroup for West Virginia Department of Education to increase and strengthen computer science education in West Virginia. He was nominated by West Virginia Department of Education to participate in Educational Testing Services Standard Setting Study in EST.

Abstract:

Internet-of-Things (IoT) and its applications are increasingly popular, where a myriad of multi-scale devices and sensors are seamlessly blended for realizing a ubiquitous computing and communication infrastructure. Due to the limited battery power, Energy Harvesting Internet of Things (EHIoT) are rapidly emerging, where a set of self-sustainable nodes communicate directly or indirectly via multi-hop relays. However, EHIoT is vulnerable to Denial-of-Service (DoS) attacks because of the lack of resources, centralized coordination, physical protection, and security requirement of inherent routing protocols. In this talk, we discuss a novel countermeasure, called CAM, to the forwarding misbehaviors of malicious node in EHIoT. Under the charge-and-spend energy harvesting policy, we first establish a set of adversarial scenarios, analyze its forwarding operations, and identify vulnerable cases of possible forwarding misbehaviors. In the CAM, each node actively disguises itself as an energy harvesting node, stealthily monitors the forwarding operations of adjacent nodes, and detects the forwarding misbehaviors of lurking deep malicious node. The proposed scheme can efficiently detect the forwarding misbehaviors of malicious node and quickly isolate it from the network.