A Detection Method of Temporally Operated Videos Using Robust Hashing

TL;DR

This paper introduces a robust hashing-based detection method for identifying tampered videos, including temporal operations like frame insertion and permutation, even after resizing and compression.

Contribution

It presents a novel robust hashing algorithm specifically designed to detect temporal manipulations in videos despite common video processing operations.

Findings

Effective detection of temporally operated videos.

Robust against resizing and compression.

Improves over conventional detection methods.

Abstract

SNS providers are known to carry out the recompression and resizing of uploaded videos/images, but most conventional methods for detecting tampered videos/images are not robust enough against such operations. In addition, videos are temporally operated such as the insertion of new frames and the permutation of frames, of which operations are difficult to be detected by using conventional methods. Accordingly, in this paper, we propose a novel method with a robust hashing algorithm for detecting temporally operated videos even when applying resizing and compression to the videos.