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Dalin Huang

dblp:283/1469 · DBLP profile ↗
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2ranked-venue papers
0as first author
1since 2021 · last 2022
—ORCID · none

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

Artificial intelligence and machine learning · 1Graphics, computer vision, multimedia, augmented reality and games · 1Applied, 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.

Artificial intelligence
1 paper
Multi-agent systems · 100%
Computer architecture, parallel and distributed computing, and storage systems
1 paper
Distributed systems · 50% Embedded and real-time systems · 50%
Network and information security
1 paper
Cyber-physical and IoT security · 100%

Topics — the 3 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Cyber-physical and IoT security › deception attacks
false data injection attack
0.212022
Secure output synchronization of heterogeneous multi-agent systems against false data injection attacks · Sci. China Inf. Sci. 2022
Distributed systems
fault tolerance
0.212022
Secure output synchronization of heterogeneous multi-agent systems against false data injection attacks · Sci. China Inf. Sci. 2022
Embedded and real-time systems › cyber-physical systems
resilient control
0.212022
Secure output synchronization of heterogeneous multi-agent systems against false data injection attacks · Sci. China Inf. Sci. 2022

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

heterogeneous multi-agent control · 1.7
YearPublicationVenuePosition
2022 Secure output synchronization of heterogeneous multi-agent systems against false data injection attacks
Shicheng Huo, Dalin Huang, Ya Zhang 0001
Sci. China Inf. Sci.2
2020 Cooperative Control Based on Distributed Attack Identification and Isolation
abstract
This paper studies the secure consensus control of multi-agent systems where some agents are injected into malicious attacks and compromised. We focus on the distributed detection and identification of attacks on agents and the realization of consensus of agents against attacks. Firstly, we design monitors that can perform precise distributed attack detection. Then, we propose a distributed attack identification algorithm by constructing distributed observers. After that, a cooperative controller is proposed which ensures the normal control of systems by means of isolating the agents which are attacked. Finally, we validate our results through simulation examples.
Hailing Liu, Dalin Huang, Ya Zhang 0001
ICARCV2