智能系统学报2025，Vol.20Issue(5)：1112-1122,11.DOI:10.11992/tis.202412025
融合多维特征的电诈犯罪时空预测研究
Spatiotemporal prediction of telecommunications network fraud crime with multidimensional feature fusion
摘要
Abstract
Spatiotemporal prediction of telecommunications fraud crimes can substantially enhance targeted antifraud efforts.However,existing methods suffer from poor performance due to sparse and periodic incident time-series data,as well as the heterogeneity of spatial environmental factors.Aiming to address these challenges,this paper proposes a multidimensional feature-integrated telecom fraud spatiotemporal prediction(MF-TSP)model.First,a spatial feature se-lection module was constructed by integrating regional topological graphs to effectively incorporate neighborhood crime patterns.A time-sliding window technique,combined with a multidimensional temporal feature extraction module and an inverted Transformer,addresses data sparsity while capturing periodicity,global dependencies,and complex mul-tivariate correlations.Furthermore,deep spatiotemporal fusion and nonlinear mapping notably improve prediction accur-acy.Experiments on real-world telecom fraud data from City B demonstrate that MF-TSP outperforms seven baseline models under three different input time-step conditions.关键词
电诈犯罪时空预测/多维特征/时空特征融合/空间环境特征因子/图注意力网络/时间滑动窗口/iTransformerKey words
spatiotemporal fraud prediction/multidimensional features/spatio-temporal feature fusion/spatial environ-mental feature factors/graph attention networks/time-sliding window/iTransformer分类
信息技术与安全科学引用本文复制引用
周璟昊,石磊,石拓,陈鹏..融合多维特征的电诈犯罪时空预测研究[J].智能系统学报,2025,20(5):1112-1122,11.基金项目
国家自然科学基金项目(62406023). （62406023）
