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Lin Wang 0041

dblp:17/6729-41 · DBLP profile ↗
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4ranked-venue papers
0as first author
4since 2021 · last 2026
0000-0002-9111-2723ORCID · conflict

Domains — the database's venue-derived domains; a paper can count in several

Computer networks · 1 · 1 since 2021Security and privacy · 1 · 1 since 2021Databases, data management, data science and information retrieval · 1 · 1 since 2021Applied, interdisciplinary, general and emerging computing · 1 · 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.

Computer architecture, parallel and distributed computing, and storage systems
1 paper
Distributed systems · 100%
Network and information security
1 paper
Privacy and data protection · 77% Network security · 12% Systems and software security · 12%

Topics — the 7 heaviest of 7, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Privacy and data protection › differential privacy › distributed differential privacy
differentially private consensus
1.012026
Differentially Private Event-Triggered Average Consensus for Multi-Agent Systems Under f-Local Byzantine Attacks: An Improved Resilient Protocol · IEEE Trans. Inf. Forensics Secur. 2026
Privacy and data protection
differential privacy
1.012026
Differentially Private Event-Triggered Average Consensus for Multi-Agent Systems Under f-Local Byzantine Attacks: An Improved Resilient Protocol · IEEE Trans. Inf. Forensics Secur. 2026
Distributed systems
consensus
1.012026
Differentially Private Event-Triggered Average Consensus for Multi-Agent Systems Under f-Local Byzantine Attacks: An Improved Resilient Protocol · IEEE Trans. Inf. Forensics Secur. 2026
Distributed systems
distributed coordination
1.012026
Differentially Private Event-Triggered Average Consensus for Multi-Agent Systems Under f-Local Byzantine Attacks: An Improved Resilient Protocol · IEEE Trans. Inf. Forensics Secur. 2026
Distributed systems › consensus › fault-tolerant consensus
resilient consensus
1.012026
Differentially Private Event-Triggered Average Consensus for Multi-Agent Systems Under f-Local Byzantine Attacks: An Improved Resilient Protocol · IEEE Trans. Inf. Forensics Secur. 2026
Systems and software security › distributed system security
byzantine attack
0.312026
Differentially Private Event-Triggered Average Consensus for Multi-Agent Systems Under f-Local Byzantine Attacks: An Improved Resilient Protocol · IEEE Trans. Inf. Forensics Secur. 2026
Network security › attack strategy
denial-of-service attack
0.312026
Differentially Private Event-Triggered Average Consensus for Multi-Agent Systems Under f-Local Byzantine Attacks: An Improved Resilient Protocol · IEEE Trans. Inf. Forensics Secur. 2026

Methods — techniques the papers use, named apart from their topics

lyapunov analysis · 2.0event-triggered control · 2.0
YearPublicationVenuePosition
2026 Game-Based Event-Triggered Privacy-Preserving Consensus Control of Nonlinear Multiagent Systems With Nonuniform Decomposition
Yang Yang 0052, Yizhou Wu, Jinwei Li 0004, Lin Wang 0041, Wenbin Yue
IEEE Internet Things J.5
2026 CADF: Real-time multi-biosignal modal recognition with causality-aware dimension fusion
Lin Wang 0041, Dahua Shou 0001
Inf. Process. Manag.3
2026 Differentially Private Event-Triggered Average Consensus for Multi-Agent Systems Under f-Local Byzantine Attacks: An Improved Resilient Protocol
abstract
Multi-agent systems (MASs) in open networks face dual security threats: Byzantine attacks that steer malicious consensus and eavesdroppers that steal private information. Existing resilient consensus protocol isolates Byzantine attacks by relying on (2f+1)-robust networks, which imposes stringent topological constraints and fails to provide privacy preservation simultaneously. To address this issue, an improved resilient consensus protocol withf(IRCP-f) is proposed, via absolute values of relative states, to defend againstf-local Byzantine attacks. This protocol only requires that an undirected and connected graph is (f+ 1)-robust instead of (2f+ 1)-robust. The properties of the dynamic network processed by the IRCP-fare analyzed, and the graph conditions for achieving average consensus are consequently satisfied. A fully distributed differentially private event-triggered average consensus (DPETAC) control scheme is then developed. With the DPETAC control scheme, convergence analysis, Zeno behavior analysis, accuracy analysis and privacy analysis are presented for the MAS. Finally, a numerical simulation illustrates the feasibility and effectiveness of the proposed privacy-preserving average consensus control scheme.
Yang Yang 0052, Xinghai Yu, Lin Wang 0041
IEEE Trans. Inf. Forensics Secur.4
2022 Linear Active Disturbance Rejection Control for Two-Mass Systems Via Singular Perturbation Approach
abstract
This article presents a linear active disturbance rejection control (LADRC) scheme for two-mass systems (TMSs) based on a singular perturbation (SP) approach. In the proposed scheme, the dynamics of TMSs are separated into a quasi-steady-state system at a slow time scale and a boundary-layer system at a fast time scale via the SP method. The quasi-steady-state model is used as the nominal model to design the LADRC, where internal model control (IMC) rules are employed for prescribed tracking performance. This not only reduces the model order but also makes the gain tuning straightforward, which is crucial for practical use. Based on the boundary-layer model, the active damping method is designed for vibration suppression, which aims at achieving a higher stable bandwidth of the IMC to better attenuate the residual disturbance of linear extended state observer such that the tracking accuracy can be improved. Stability of the full system was analyzed via the extended Tikhonov's theorem. Comparative experiments were carried out to verify the effectiveness of the proposed scheme.
Ping Li 0031, Lin Wang 0041, Bin Zhong, Mingming Zhang 0001
IEEE Trans. Ind. Informatics2