Minimizing block incentive volatility through Verkle tree-based dynamic transaction storage
We address volatile, fee-only incentives in consortium blockchains. Dynamic Transaction Storage (DTS) stabilizes block rewards by combining Verkle tree–based storage with optimization framed as a Vehicle Routing Problem. Verkle trees reduce bandwidth and speed propagation. We evaluate multiple optimizers and datasets, including historical Bitcoin transactions and ICBC remittance records. Results show a time-priority inclusion policy—without reserving block space for low-fee transactions—found by a gradient-based optimizer, best reduces incentive volatility. DTS maintains stable miner revenue across transaction types and bidding behaviors, while prioritizing higher-fee, typically smaller transactions further decreases propagation delays and fork risk, discouraging manipulative mining and improving network robustness.
Mitigating Blockchain Extractable Value threats by Distributed Transaction Sequencing Strategy
This exquisite compilation showcases a diverse array of photographs that capture the essence of different eras and cultures, reflecting the unique styles and perspectives of each artist. Fleckenstein’s evocative imagery, Strand’s groundbreaking modernist approach, and Kōno’s meticulous documentation of Japanese life come together in a harmonious blend that celebrates the art of photography. Each image in “The Stories Book” is accompanied by insightful commentary, providing historical context and revealing the stories behind the photographs. This collection is not only a visual feast but also a tribute to the power of photography to preserve and narrate the multifaceted experiences of humanity.
An efficient dynamic transaction storage mechanism for sustainable high-throughput Bitcoin
As block subsidies decline, transaction fees become Bitcoin’s key mining incentive. We propose Efficient Dynamic Transaction Storage (EDTS) to dynamically allocate transactions across blocks for efficient storage and scalable propagation. EDTS combines Cuckoo Filters with Dynamic Transaction Storage (DTS) strategies, sustaining performance in a fee-only regime while discouraging deviant mining. It enables differentiated transmission priority by fee and encourages higher-fee pledging. We use the multi-objective optimizer U-NSGA-III to select optimal DTS policies and parameters. Experiments show EDTS with optimized DTS reaches 325.3 TPS, matches Graphene-level scalability, and surpasses most recent scaling solutions by at least 11.6%, maintaining sustainability under fee-driven incentives.
CDGAT: a graph attention network method for credit card defaulters prediction
Identifying potential defaulters is vital for financial institutions, yet traditional credit scoring often ignores customer interactions (e.g., transfers, remittances) that increasingly shape risk in online banking. We present CDGAT, a scalable graph attention–based method for predicting credit card defaulters. CDGAT computes a customer’s score from transaction embeddings and neighborhood embeddings. It builds customer-specific subgraphs via Amount-bias Sampling (AbS), then aggregates neighbors’ features using learned influence weights through attention. Evaluated on Industrial and Commercial Bank of China (Macau) data, CDGAT significantly outperforms strong baselines and multiple state-of-the-art GCN variants, delivering superior scalability and predictive performance for real-world credit risk assessment.
Conference Proceedings
X. Zhao and Y. -W. Si, “NFTCert: NFT-Based Certificates With Online Payment Gateway,”
2021 IEEE International Conference on Blockchain (Blockchain), Melbourne, Australia, 2021, pp. 538-543, doi: 10.1109/Blockchain53845.2021.00081.
Available Online.
X. Zhao and Y. -W. Si, “Dynamic Transaction Storage Strategies for a Sustainable Blockchain,”
International Conference on Services Computing (SCC), Chicago, IL, USA, 2021, pp. 309-318, doi: 10.1109/SCC53864.2021.00044.
Available Online.
X. Zhao and Y. -W. Si, “Challenges of Blockchain adoption in financial services in China’s Greater Bay Area,”
2023 Fifth International Conference on Blockchain Computing and Applications (BCCA), Kuwait, Kuwait, 2023, pp. 68-75, doi: 10.1109/BCCA58897.2023.10338862.
Available Online.
H. -W. Long, X. Zhao & Y. -W. Si, “Dynamic Mining Interval to Improve Blockchain Throughput,”
International Conference on Big Data (BigData), Sorrento, Italy, 2023, pp. 46-55, doi: 10.1109/BigData59044.2023.10386281.
Available Online.