
Collaborator(s): Prof. Show-Shiow Tzeng
In recent years, DAG-based distributed ledger systems have emerged as a promising approach to improving blockchain scalability. However, existing studies largely focus on specific protocols or simulation-based comparisons, leaving their structural properties under stochastic growth insufficiently understood. This research models DAGs as stochastic dynamic systems, investigates the evolution of key metrics such as transaction height, growth rate, and node density, and develops an extensible theoretical framework for systematic analysis.
| [C02] | S.W. Wang, Y.X. Chen, and S.S. Tzeng, "HS-TSA: Avoidance of Deanonymization Attack in Unstructured DAG-based DLTs with Light Nodes," in 2026 IEEE International Conference on Communications (ICC 2026), Glasgow, Scotland, United Kingdom, May 24-28, 2026. |
| [C01] | S.W. Wang, P.Y. Chuang, and S.S. Tzeng, "A Two-Stage DTMC Modeling Approach for Tip Count Distributions in Generalized IOTA Tangles," in 2025 IEEE Global Communication Conference (Globecom 2025), Taipei, Taiwan, December 8-12, 2025. |
| [S02] | S.W. Wang, P.Y. Chuang, and S.S. Tzeng, "Stochastic Modeling of Structural Dynamics in Unstructured DAG Networks for Distributed Ledgers," under review by IEEE Transactions on Network Science and Engineering, (Last update: 2026-07-01 Undergoing review after Revise and Resubmit ) |
| [S01] | S.W. Wang, Y.X. Chen, and S.S. Tzeng, "Privacy-Preserving Tip Selection under Exact and Partial Deanonymization Attacks in Unstructured DAG-based DLTs," under review by IEEE Transactions on Dependable and Secure Computing, (Last update: 2026-05-06 Under review in 1st round ) |