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Jianhua Li

Researcher at Shanghai Jiao Tong University

Publications -  295
Citations -  4861

Jianhua Li is an academic researcher from Shanghai Jiao Tong University. The author has contributed to research in topics: Computer science & The Internet. The author has an hindex of 27, co-authored 278 publications receiving 3330 citations.

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A New Intrusion Detection System Based on KNN Classification Algorithm in Wireless Sensor Network

TL;DR: This system can separate abnormal nodes from normal nodes by observing their abnormal behaviors, and it has achieved efficient, rapid intrusion detection by improving the wireless ad hoc on-demand distance vector routing protocol (Ad hoc On-Demand Distance the Vector Routing, AODV).
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Blockchain-Based On-Demand Computing Resource Trading in IoV-Assisted Smart City

TL;DR: A Peer-to-Peer (P2P) computing resource trading system to balance computing resource spatio-temporal dynamic demands in IoV-assisted smart city and security analysis shows the security performance of the system and numerical simulations show that the strategies can encourage the collaboration between the buyer and smart vehicles.
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Big Data Analysis-Based Secure Cluster Management for Optimized Control Plane in Software-Defined Networks

TL;DR: An ant colony optimization approach that enables big data analysis scheme and the implementation system that optimizes the control plane is proposed and is significant in improving the security and efficiency SDN control plane.
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FCSS: Fog-Computing-based Content-Aware Filtering for Security Services in Information-Centric Social Networks

TL;DR: A fog-computing-based content-aware filtering method for security services, FCSS, is proposed in information centric social networks and shows the advantages of FCSS in terms of hit ratio, filtering delay, and filtering accuracy.
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A New Ultralightweight RFID Authentication Protocol with Permutation

TL;DR: Security analysis shows that RAPP achieves the functionalities of the authentication protocol and is resistant to various attacks, and performance evaluation illustrates that R APP uses fewer resources on tags in terms of computation operation, storage requirement and communication cost.