Demo Data from VLDB 2026 / reviewers in the wild / expert
Xiaoze Ni
dblp:273/0259
· DBLP profile ↗
6ranked-venue papers
3as first author
5since 2021 · last 2023
0009-0006-9039-1384ORCID · corroborated
Domains — the database's venue-derived domains; a paper can count in several
Artificial intelligence and machine learning · 3 · 2 first-author · 2 since 2021Computer networks · 1 · 1 since 2021Security and privacy · 1 · 1 since 2021Applied, interdisciplinary, general and emerging computing · 1 · 1 first-author · 1 since 2021
Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.
| Network and information security
1 paper |
Blockchain and cryptocurrency security · 100% |
Topics — the 2 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Blockchain and cryptocurrency security
decentralized finance |
0.7 | 1 | 2023 | Demystifying DeFi MEV Activities in Flashbots Bundle · CCS 2023 |
Blockchain and cryptocurrency security
maximal extractable value |
0.7 | 1 | 2023 | Demystifying DeFi MEV Activities in Flashbots Bundle · CCS 2023 |
Methods — techniques the papers use, named apart from their topics
iterative clustering · 0.7automated transaction analysis · 0.7
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2023 | Demystifying DeFi MEV Activities in Flashbots BundleabstractDecentralized Finance, mushrooming in permissionless blockchains, has attracted a recent surge in popularity. Due to the transparency of permissionless blockchains, opportunistic traders can compete to earn revenue by extracting Miner Extractable Value (MEV), which undermines both the consensus security and efficiency of blockchain systems. The Flashbots bundle mechanism further aggravates the MEV competition because it empowers opportunistic traders with the capability of designing more sophisticated MEV extraction. In this paper, we conduct the first systematic study on DeFi MEV activities in Flashbots bundle by developing ActLifter, a novel automated tool for accurately identifying DeFi actions in transactions of each bundle, and ActCluster, a new approach that leverages iterative clustering to facilitate us to discover known/unknown DeFi MEV activities. Extensive experimental results show that ActLifter can achieve nearly 100% precision and recall in DeFi action identification, significantly outperforming state-of-the-art techniques. Moreover, with the help of ActCluster, we obtain many new observations and discover 17 new kinds of DeFi MEV activities, which occur in 53.12% of bundles but have not been reported in existing studies. Zihao Li 0001, Jianfeng Li 0006, Zheyuan He, Xiapu Luo, Ting Wang 0006, Xiaoze Ni, Wenwu Yang, Ting Chen 0002 |
CCS | 6 |
| 2023 | Blockchain-Based Access and Timeliness Control for Administrative Punishment Market SupervisionabstractAdministrative punishment is one of the most important ways of enforcing administrative law in the field of market supervision in China. However, at the current stage, the abuse of data access permission and the difficulty in managing timeliness in administrative punishment still remain unresolved, which hinders the legalization and standardization of the administrative punishment system. Inspired by blockchain, which is inherently traceable, tamper-proof, and transparent, we design a system, punishment supervisor (PEATS), which is suitable for administrative punishment and technically overcomes the defects of the traditional administrative punishment procedure. To prevent the abuse of data access permission, we innovatively introduce the ACG (authorization control gateway) to verify the access permission of users based on the records in the MSD (market supervision department) contract. To ensure the timeliness of the administrative punishment procedure, we design a special case contract that has the same status as the general case processing state of administrative punishment to track case progress on the blockchain. We experiment and evaluate PEATS in terms of functionality and performance and find that PEATS provides traceability, transparency, and timeliness assurance. In addition, PEATS has 80.9% of the throughput of a traditional server with no more than an additional 3% latency and at most 60 KB additional storage space per case. Yajie He, Renkai Jiang, Xiaoze Ni, Shubin Xu, Ting Chen 0002, Jian Feng 0005 |
IEEE Internet Things J. | 3 |
| 2023 | A License Management and Fine-Grained Verifiable Data Access Control System for Online CateringabstractTo address the law enforcement challenges arising from the rapid expansion of the online catering industry, China’s market regulatory authorities are pursuing countermeasures through legislative efforts and innovative regulatory models. At present, administrative law enforcement for online catering faces difficulties in license management and ensuring the authenticity and security of data. Specifically, there is a prevalence of fraudulent licenses in the industry, and the market supervision department struggles to verify the authenticity of the data gathered during investigations and evidence collection. The tamper-proof and transparent features of blockchain technology cannot be directly applied to the online catering domain. Consequently, to attain trusted license management and secure data-sharing measures, further system design is necessary. To achieve trusted license management, we employ blockchain technology for managing qualification certificates and delineate the format for valid certificates and the application process. The secure data-sharing protocol is divided into two stages. In the first stage, we ensure data authenticity before uploading it to the blockchain through a consensus process involving platforms, users, and merchants. In the second stage, we implement fine-grained access control based on the on-chain data from the previous stage, utilizing conditional proxy reencryption and ultimately employing the data digest on the blockchain for verification. The experiment thoroughly validates the system’s functionality, which is traceable, transparent, and scalable. Moreover, the minimal delay introduced by ensuring data authenticity is virtually negligible. The system’s additional storage overhead does not surpass 10%, remaining within acceptable limits. Xiaoze Ni, Jian Feng 0005, Renkai Jiang, Yajie He, Ting Chen 0002, Sen Qiu |
IEEE Trans. Comput. Soc. Syst. | 1 |
| 2022 | Observer-Based Adaptive Synchronization of Multiagent Systems With Unknown Parameters Under AttacksabstractThis article studies the observer-based adaptive synchronization of multiagent systems (MASs) with unknown parameters under attacks. First, to estimate the state of agents, the observer for MAS is introduced. When disturbance, nonlinear function, and system model uncertainty are not considered, the nominal controller is proposed to achieve synchronization and state estimation. Then, in order to eliminate the effect of unknown parameters in the disturbance, nonlinear function, and system model uncertainty, the adaptive controller with switching term is introduced. However, the attack will lead to the destruction of the network topology so as the destruction of the nominal controller. By constructing an appropriate Lyapunov function, we analyze the effect caused by attacks, and the security control law is given to make sure the synchronization of the MASs under attacks. Finally, a numerical simulation is given to verify the validness of the obtained theorem. Shiping Wen 0001, Xiaoze Ni, Huamin Wang 0002, Song Zhu, Kaibo Shi, Tingwen Huang |
IEEE Trans. Neural Networks Learn. Syst. | 2 |
| 2021 | Observer-Based Quasi-Synchronization of Delayed Dynamical Networks With Parameter Mismatch Under Impulsive EffectabstractThis article focuses on the observer-based quasi-synchronization problem of delayed dynamical networks with parameter mismatch under impulsive effect. First, since the state of each node is unknown in the real situation, the state estimation strategy is proposed to estimate the state of each node, so as to design an appropriate synchronization controller. Then, the corresponding controller is constructed to synchronize the slave nodes with their leader node. In this article, we take the impulsive effect into consideration, which means that an impulsive signal will be applied to the system every so often. Due to the existence of parameter mismatch and time-varying delay, by constructing an appropriate Lyapunouv function, we will eventually obtain a differential equation with constant and time-varying delay terms. Then, we analyze its trajectory by introducing the Cauchy matrix and prove its boundedness by contradiction. Finally, a numerical simulation is presented to illustrate the validness of obtained results. Xiaoze Ni, Shiping Wen 0001, Huamin Wang 0002, Zhenyuan Guo, Song Zhu, Tingwen Huang |
IEEE Trans. Neural Networks Learn. Syst. | 1 |
| 2020 | Global exponential anti-synchronization for delayed memristive neural networks via event-triggering method
Xiaoze Ni, Yuting Cao, Zhenyuan Guo, Tingwen Huang, Shiping Wen 0001 |
Neural Comput. Appl. | 1 |