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Pei-Jie Chang

dblp:428/3636 · DBLP profile ↗
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1ranked-venue papers
0as first author
1since 2021 · last 2026
—ORCID · none

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

Computer networks · 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.

Theoretical computer science
1 paper
Quantum computing and quantum information · 100%
Network and information security
1 paper
Authentication and access control · 62% Network security · 38%

Topics — the 5 heaviest of 5, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Authentication and access control › authentication
message authentication
1.012026
Tamper-Proof Quantum Communication Network Enhanced by Machine Learning · IEEE J. Sel. Areas Commun. 2026
Quantum computing and quantum information
quantum communication
1.012026
Tamper-Proof Quantum Communication Network Enhanced by Machine Learning · IEEE J. Sel. Areas Commun. 2026
Quantum computing and quantum information
quantum network
1.012026
Tamper-Proof Quantum Communication Network Enhanced by Machine Learning · IEEE J. Sel. Areas Commun. 2026
Network security › intrusion detection and prevention › intrusion detection › attack detection
machine learning-based detection
0.312026
Tamper-Proof Quantum Communication Network Enhanced by Machine Learning · IEEE J. Sel. Areas Commun. 2026
Network security › intrusion detection and prevention › intrusion detection › network intrusion detection
malicious node detection
0.312026
Tamper-Proof Quantum Communication Network Enhanced by Machine Learning · IEEE J. Sel. Areas Commun. 2026

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

unsupervised learning · 2.0supervised learning · 2.0simulation · 2.0
YearPublicationVenuePosition
2026 Tamper-Proof Quantum Communication Network Enhanced by Machine Learning
abstract
Quantum cryptography provides a feasible approach to achieving information-theoretic security in point-to-point communication. In contrast to point-to-point protocols, end-to-end secure quantum communication is particularly promising for large-scale quantum networks. Here, we propose a scheme for end-to-end secure communication with private message authentication. For practical purposes, we demonstrate the scheme in a quantum communication network with optical fibers or free-space links that integrate secure repeaters. Furthermore, we present a route proposal model for routing private messages in a quantum network based on the scheme. As messages are routed through a network, malicious nodes may tamper with the messages passing through them with some probability. Based on authentication results, we use machine learning methods to detect malicious nodes, including supervised and unsupervised algorithms. The simulation results in specific networks show that our methods can effectively detect malicious nodes under different tamper probabilities.
Yuan-Bin Cheng, Ze-Zhou Sun, Pei-Jie Chang, Gui-Lu Long 0001
IEEE J. Sel. Areas Commun.3