四川轻化工大学学报（自然科学版）2026，Vol.39Issue(3)：103-118,16.DOI:10.11863/j.suse.2026.03.11
跨模态深度伪造检测技术综述
Review of Cross-modal Deepfake Detection Technologies
摘要
Abstract
With the rapid development of generative adversarial networks,diffusion models,and multimodal generation technologies,the realism of deepfake content in images,videos,and audio has been continuously improving,posing significant challenges to digital media authenticity verification.Focusing on research progress in deepfake detection,this paper constructs a comprehensive analytical framework that combines signal layer artifacts with semantic layer inconsistencies features,based on the anomalous formation process of deepfake content in the"generation-rendering-encoding-dissemination"chain.First,from the perspectives of image,video,and audio as single modalities,the study systematically reviews detection methods utilizing clues such as frequency domain statistics,device fingerprints,resampling traces,lighting geometry,physiological signals,and temporal structures.Second,for cross-modal scenarios,key evidence including temporal mismatches,violations of biological and physical constraints,and semantic/emotional conflicts is summarized,along with implementation paths for temporal alignment modeling,joint constraint modeling,anomaly distribution learning,and multi-level fusion.Furthermore,an analysis of existing benchmark datasets and evaluation metrics reveals shortcomings in current assessment systems regarding long temporal sequences,open scenarios,and system-level security evaluation.The review indicates that deepfake detection is transitioning from a discriminative model relying on intra-modal statistical anomalies to a comprehensive detection paradigm emphasizing cross-modal consistency constraints and risk-sensitive evaluation.关键词
深度伪造检测/信号层伪影/语义一致性约束/跨模态一致性/多模态生成Key words
deepfake detection/signal layer artifacts/semantic consistency constraints/cross-modal consistency/multimodal generation分类
信息技术与安全科学引用本文复制引用
车召旭,周顺勇,谢乐惠,刘盈盈,梁蔚,林伟..跨模态深度伪造检测技术综述[J].四川轻化工大学学报（自然科学版）,2026,39(3):103-118,16.基金项目
国家自然科学基金项目(61801319) （61801319）
四川省科技厅项目(2024ZYD0265) （2024ZYD0265）
四川轻化工大学科研项目(2023RC24) （2023RC24）
