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20232026
most citedOverview of AI and Communication for 6G Network: Fundamentals, Challenges, and Future Research Opportunities

198 citations · 220 across the 29 of their papers we have counts for

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Showing 2023Show all

8 papers · 1 filter

cs.LG2023★ 1 cited

Refining Latent Homophilic Structures over Heterophilic Graphs for Robust Graph Convolution Networks

Chenyang Qiu, Guoshun Nan, Tianyu Xiong +6

Graph convolution networks (GCNs) are extensively utilized in various graph tasks to mine knowledge from spatial data. Our study marks the pioneering attempt to quantitatively inve…

cs.CL2023

DocMSU: A Comprehensive Benchmark for Document-level Multimodal Sarcasm Understanding

Hang Du, Guoshun Nan, Sicheng Zhang +6

Multimodal Sarcasm Understanding (MSU) has a wide range of applications in the news field such as public opinion analysis and forgery detection. However, existing MSU benchmarks an…

eess.SP2023

Passive Eavesdropping Can Significantly Slow Down RIS-Assisted Secret Key Generation

Ningya Xu, Guoshun Nan, Xiaofeng Tao

Reconfigurable Intelligent Surface (RIS) assisted physical layer key generation has shown great potential to secure wireless communications by smartly controlling signals such as p…

cs.CR2023

SemProtector: A Unified Framework for Semantic Protection in Deep Learning-based Semantic Communication Systems

Xinghan Liu, Guoshun Nan, Qimei Cui +6

Recently proliferated semantic communications (SC) aim at effectively transmitting the semantics conveyed by the source and accurately interpreting the meaning at the destination.…

cs.CR2023★ 15 cited

3D-IDS: Doubly Disentangled Dynamic Intrusion Detection

Chenyang Qiu, Yingsheng Geng, Junrui Lu +8

Network-based intrusion detection system (NIDS) monitors network traffic for malicious activities, forming the frontline defense against increasing attacks over information infrast…

eess.SP2023★ 2 cited

Physical-layer Adversarial Robustness for Deep Learning-based Semantic Communications

Guoshun Nan, Zhichun Li, Jinli Zhai +7

End-to-end semantic communications (ESC) rely on deep neural networks (DNN) to boost communication efficiency by only transmitting the semantics of data, showing great potential fo…

cs.CR2023

Securing Semantic Communications with Physical-layer Semantic Encryption and Obfuscation

Qi Qin, Yankai Rong, Guoshun Nan +4

Deep learning based semantic communication(DLSC) systems have shown great potential of making wireless networks significantly more efficient by only transmitting the semantics of t…

eess.SP2023★ 1 cited

Boosting Physical Layer Black-Box Attacks with Semantic Adversaries in Semantic Communications

Zeju Li, Xinghan Liu, Guoshun Nan +4

End-to-end semantic communication (ESC) system is able to improve communication efficiency by only transmitting the semantics of the input rather than raw bits. Although promising,…