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Guiling “Grace” Wang
Research Areas: Deep learning, FinTech, blockchain technologies, intelligent transportation systems
To realize the full potential of connected and automated vehicles to transform the US transportation system, it is important to ensure the vehicle communication is secure and privacy-preserving. In this situation, a digital certificate is critical to provide communication integrity, authenticity and privacy. Existing solutions based on centralized security credential management systems are inherently vulnerable to emerging cyber-security risk and single-point failure. To address the weakness of centralized systems being adopted, this project seeks to utilize the recent breakthrough of blockchain technology, in particular the consortium blockchain, to design and implement an innovative decentralized vehicle credential management system. The proposed decentralized credential management system based on consortium blockchain can not only greatly improve the robustness and security of the credential management system for vehicles and thus realizes high-security assurance for authentic V2V and V2I communication, but also incorporate state-of-the-art achievements in cryptography to ensure strong anonymity to prevent hackers from tracing the locations of vehicles and ensuring vehicle privacy. This project was one of the four awardees among 122 proposals submitted to FHWA.
Blockchain-Based P2P Content Delivery
Peer-to-peer (P2P) content delivery provides many benefits compared with centralized content delivery networks (CDNs) and is complementary to popular decentralized storage networks such as Filecoin. However, reliable P2P delivery demands proper enforcement of delivery fairness. Still, most existing studies on delivery fairness are based on non-cooperative game- theoretic assumptions that are arguably unrealistic in the ad-hoc P2P setting. We propose an expressive yet minimalist security requirement for desired fair P2P content delivery and give two efficient blockchain-enabled and monetary-incentivized solutions FairDownload and FairStream, for P2P downloading and P2P streaming scenarios, respectively. Our designs not only ensure delivery fairness where deliverers are paid (nearly) proportional to their in-time delivery but also guarantee exchange fairness where content consumers and content providers are fairly treated. (This is a collaborative work of Dr. Wang and Dr. Wu.)
Research Areas: Big data, machine learning, green computing and networking, parallel and distributed computing
A Blockchain-Based Decentralized IIoT Management System
Blockchain has been increasingly used to secure data collection, storage and transfer in various Industrial Internet of Things (IIoT) environments. We design a blockchain-based decentralized IIoT management system for censorship resistance, which employs a diffusion mechanism to deliver messages from sensors to full nodes, an augmented consensus protocol to check data losses and facilitate opportunistic outcome delivery, and a public key-based aggregation method to reduce communication complexity and signature verification.