21 citations · 46 across the 15 of their papers we have counts for
18 papers
Correcting Subverted Random Oracles
Alexander Russell, Qiang Tang, Moti Yung +2
The random oracle methodology has proven to be a powerful tool for designing and reasoning about cryptographic schemes. In this paper, we focus on the basic problem of correcting f…
Dumbo-NG: Fast Asynchronous BFT Consensus with Throughput-Oblivious Latency
Yingzi Gao, Yuan Lu, Zhenliang Lu +3
Despite recent progresses of practical asynchronous Byzantine fault tolerant (BFT) consensus, the state-of-the-art designs still suffer from suboptimal performance. Particularly, t…
Leopard: Towards High Throughput-Preserving BFT for Large-scale Systems
Kexin Hu, Kaiwen Guo, Qiang Tang +3
With the emergence of large-scale decentralized applications, a scalable and efficient Byzantine Fault Tolerant (BFT) protocol of hundreds of replicas is desirable. Although the th…
Efficient Asynchronous Byzantine Agreement without Private Setups
Yingzi Gao, Yuan Lu, Zhenliang Lu +3
Efficient asynchronous Byzantine agreement (BA) protocols were mostly studied with private setups, e.g., pre-setup threshold cryptosystem. Challenges remain to reduce the large com…
Bolt-Dumbo Transformer: Asynchronous Consensus As Fast As the Pipelined BFT
Yuan Lu, Zhenliang Lu, Qiang Tang
An urgent demand of deploying BFT consensus over the Internet is raised for implementing blockchain services. The deterministic (partial) synchronous protocols can be simple and fa…
Fair Peer-to-Peer Content Delivery via Blockchain
Songlin He, Yuan Lu, Qiang Tang +2
Peer-to-peer (p2p) content delivery is promising to provide benefits like cost-saving and scalable peak-demand handling in comparison with conventional content delivery networks (C…
Another Look at Privacy-Preserving Automated Contact Tracing
Qiang Tang
In the current COVID-19 pandemic, manual contact tracing has been proven very helpful to reach close contacts of infected users and slow down virus spreading. To improve its scalab…
Privacy-Preserving Contact Tracing: current solutions and open questions
Qiang Tang
The COVID-19 pandemic has posed a unique challenge for the world to find solutions, ranging from vaccines to ICT solutions to slow down the virus spreading. Due to the highly conta…
Generic Superlight Client for Permissionless Blockchains
Yuan Lu, Qiang Tang, Guiling Wang
We conduct a systematic study on the light client of permissionless blockchains, in the setting where the full nodes and the light clients are rational. Under such a game-theoretic…
Dragoon: Private Decentralized HITs Made Practical
Yuan Lu, Qiang Tang, Guiling Wang
With the rapid popularity of blockchain, decentralized human intelligence tasks (HITs) are proposed to crowdsource human knowledge without relying on vulnerable third-party platfor…
Privacy-preserving and yet Robust Collaborative Filtering Recommender as a Service
Qiang Tang
Collaborative filtering recommenders provide effective personalization services at the cost of sacrificing the privacy of their end users. Due to the increasing concerns from the s…
Towards Blockchain-enabled Searchable Encryption
Qiang Tang
Distributed Leger Technologies (DLTs), most notably Blockchain technologies, bring decentralised platforms that eliminate a single trusted third party and avoid the notorious singl…
ZebraLancer: Decentralized Crowdsourcing of Human Knowledge atop Open Blockchain
Yuan Lu, Qiang Tang, Guiling Wang
We design and implement the first private and anonymous decentralized crowdsourcing system ZebraLancer, and overcome two fundamental challenges of decentralizing crowdsourcing, i.e…
CryptoRec: Privacy-preserving Recommendation as a Service
Jun Wang, Afonso Arriaga, Qiang Tang +1
Recommender systems rely on large datasets of historical data and entail serious privacy risks. A server offering Recommendation as a Service to a client might leak more informatio…
Together or Alone: The Price of Privacy in Collaborative Learning
Balazs Pejo, Qiang Tang, Gergely Biczok
Machine learning algorithms have reached mainstream status and are widely deployed in many applications. The accuracy of such algorithms depends significantly on the size of the un…
A Probabilistic View of Neighborhood-based Recommendation Methods
Jun Wang, Qiang Tang
Probabilistic graphic model is an elegant framework to compactly present complex real-world observations by modeling uncertainty and logical flow (conditionally independent factors…
Differentially Private Neighborhood-based Recommender Systems
Jun Wang, Qiang Tang
Privacy issues of recommender systems have become a hot topic for the society as such systems are appearing in every corner of our life. In contrast to the fact that many secure mu…
On the Security of Key Extraction from Measuring Physical Quantities
Matt Edman, Aggelos Kiayias, Qiang Tang +1
Key extraction via measuring a physical quantity is a class of information theoretic key exchange protocols that rely on the physical characteristics of the communication channel t…