Fuxiang Yuan

dblp:237/5095 · DBLP profile ↗
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4ranked-venue papers
0as first author
4since 2021 · last 2026
0000-0002-2106-755XORCID · corroborated

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Computer networks · 4 · 4 since 2021
YearPublicationVenuePosition
2026 Large-Scale BGP Routing Anomaly Detection Based on Graph Attention Auto-Encoder
Zekang Wang 0001, Fuxiang Yuan, Han Qiu 0004, Yan Liu 0057, Xiangyang Luo 0001
IEEE Trans. Netw. Serv. Manag.2
2025 Hidden AS link prediction based on random forest feature selection and GWO-XGBoost model
Zekang Wang 0001, Fuxiang Yuan, Meng Zhang 0044, Xiangyang Luo 0001
Comput. Networks2
2025 GDD-Geo: IPv6 geolocation by graph dual decomposition
Ruosi Cheng, Fuxiang Yuan, Shichang Ding, Yan Liu 0057, Xiangyang Luo 0001
Comput. Commun.3
2024 6Subpattern: Target Generation Based on Subpattern Analysis for Internet-Wide IPv6 Scanning
abstract
IP scanning is crucial for network management and security. However, the brute-force scanning is infeasible in IPv6 networks due to the vast address space. Consequently, target generation algorithms (TGAs) have become necessary to address this issue. Nevertheless, existing algorithms often struggle with low hit rates due to coarse-grained pattern mining. To address this problem, we propose 6Subpattern, a target generation algorithm based on subpattern analysis for Internet-wide IPv6 scanning. 6Subpattern first clusters seeds into high-density regions according to the seed structure information. Subsequently, pattern mining and subpattern analysis are carried out in these regions. Different from previous works, 6Subpattern can obtain all fine-grained patterns while automatically avoiding the influence of outlier addresses and the quandary of setting heuristic thresholds through subpattern analysis. Moreover, pattern refining is conducted based on the distribution of nibbles in address regions to further narrow the scanning space. Finally, targets are effectively generated according to the density of the patterns. Experimental results on real-world networks demonstrate that the address patterns discovered by 6Subpattern provide a superior scanning space than existing algorithms. Further results of hit rates on nine candidate seed sets reveal that 6Subpattern can achieve a 53%-315% improvement over the static TGAs on all seed sets and achieve a 15%-25% improvement on all randomly sampled seed sets compared with dynamic TGAs in Internet-wide IPv6 scanning.
Fuxiang Yuan, Shichang Ding, Yan Liu 0057, Xiangyang Luo 0001
IEEE Trans. Netw. Serv. Manag.3