Abstract: In recent years,malicious video tampering has become increasingly prevalent,posing severe challenges to the authenti-city and reliability of electronic evidence.Among such tampering methods,video frame deletion,which can obscure factual truth,proves particularly destructive to video-based electronic evidence.Consequently,frame deletion detection has attracted growing research attention.Current mainstream detection methods primarily rely on identifying content continuity degradation in the temporal domain caused by frame deletion.However,the complexity of temporal information in videos makes such temporal continuity-based detection approaches unstable.To address this issue,this paper focuses on motion patterns of objects in videos.By establi-shing a first-order Markov model,it derives frequency-domain Markov continuity decay traces.Subsequently,based on these frequency-domain traces,this paper proposes a video frame deletion detection algorithm utilizing time-frequency analysis techniques.Experimental results demonstrate that compared with temporal continuity decay traces,the frequency-domain continuity decay-based detection algorithm exhibits superior forensic performance.Building upon this technical advancement,this research further constructs a legal framework from perspectives of evidence legality,evidence authenticity,and evidence relevance,providing theoretical references for improving electronic evidence regulations in the digital era.This dual approach achieves both technological justice and procedural justice objectives.

Key words: Frame deletion detection, Passive evidence collection, Markov model, Continuous attenuation traces, Time-frequency analysis, Evidentiary validit