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Yuanjiaoyang Li

dblp:440/5632 · DBLP profile ↗
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1ranked-venue papers
0as first author
1since 2021 · last 2026
0009-0001-1844-9944ORCID · reported

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

Security and privacy · 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 networks
1 paper
Network optimization and economics · 67% Edge and fog computing · 33%
Network and information security
1 paper
Network security · 100%

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

TopicWeightPapersLastEvidence papers
Network optimization and economics › game theory
game-theoretic networking
1.012026
QoE-Ensured DDoS Mitigation in NOMA-Assisted Edge Computing: A Game-Theoretical Approach · IEEE Trans. Dependable Secur. Comput. 2026
Edge and fog computing
mobile edge computing
1.012026
QoE-Ensured DDoS Mitigation in NOMA-Assisted Edge Computing: A Game-Theoretical Approach · IEEE Trans. Dependable Secur. Comput. 2026
Network optimization and economics › game theory
potential game
1.012026
QoE-Ensured DDoS Mitigation in NOMA-Assisted Edge Computing: A Game-Theoretical Approach · IEEE Trans. Dependable Secur. Comput. 2026
Network security › attack resilience › attack mitigation › denial-of-service defense
DDoS defense
1.012026
QoE-Ensured DDoS Mitigation in NOMA-Assisted Edge Computing: A Game-Theoretical Approach · IEEE Trans. Dependable Secur. Comput. 2026
Network security › attack resilience › attack mitigation
denial-of-service defense
1.012026
QoE-Ensured DDoS Mitigation in NOMA-Assisted Edge Computing: A Game-Theoretical Approach · IEEE Trans. Dependable Secur. Comput. 2026

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

game theory · 2.0best-response dynamics · 1.0best response dynamics · 1.0
YearPublicationVenuePosition
2026 QoE-Ensured DDoS Mitigation in NOMA-Assisted Edge Computing: A Game-Theoretical Approach
abstract
In Multi-access Edge Computing (MEC) environments, Non-Orthogonal Multiple Access (NOMA) technology significantly improves spectrum efficiency and system access capacity through power-domain multiplexing. However, it also exposes edge servers to more complex resource contention and security risks. In particular, during Distributed Denial-of-Service (DDoS) attacks, conventional mitigation mechanisms often overlook users' quality of experience (QoE), which can lead to prolonged service degradation. To address this challenge, this paper investigates a QoE-guaranteed Edge DDoS Mitigation problem (QEDM) in NOMA-assisted MEC systems by jointly considering request scheduling and power allocation. First, the QEDM problem is modeled as a finite-strategy potential game, and a distributed game-theoretic algorithm, QEDMGame, is proposed. Then, through a multi-player best-response mechanism, the system converges to a Nash equilibrium, thereby achieving joint optimization of service rate and QoE. Next, experimental results on real-world base station deployment data demonstrate that QEDMGame outperforms several representative baseline methods. Additionally, theoretical analysis shows that QEDMGame exhibits strong convergence properties and performance guarantees.
Aiping Wang, Guangming Cui, Yuanjiaoyang Li, Ruichen Zhang 0001
IEEE Trans. Dependable Secur. Comput.4