A universal forensics approach based on steganographic models: image manipulation detection

Inderscience is a global company, a dynamic leading independent journal publisher disseminates the latest research across the broad fields of science, engineering and technology; management, public and business administration; environment, ecological economics and sustainable development; computing, ICT and internet/web services, and related areas.

Authors

Publication Details

Journal
International Journal of Electronic Security and Digital Forensics
Published
2025-01-16
DOI
https://doi.org/10.1504/ijesdf.2027.10068886
Primary Topic
Digital Media Forensic Detection
Type
article
Field-Weighted Citation Impact
0.00
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article

A universal forensics approach based on steganographic models: image manipulation detection

Xiaoyan Liu, Ling Yang, Long Liu
International Journal of Electronic Security and Digital Forensics
Digital Media Forensic Detection
article

A universal forensics approach based on steganographic models: image manipulation detection

Xiaoyan Liu, Ling Yang, Long Liu
article en

Abstract

Inderscience is a global company, a dynamic leading independent journal publisher disseminates the latest research across the broad fields of science, engineering and technology; management, public and business administration; environment, ecological economics and sustainable development; computing, ICT and internet/web services, and related areas.

International Journal of Electronic Security and Digital ForensicsVol. 1(1)
Openalex Percentile: Top 99%
Digital Media Forensic Detection
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A universal forensics approach based on steganographic models: image manipulation detection — Xiaoyan Liu, Ling Yang, et al. · International Journal of Electronic Security and Digital Forensics (2025) | TGRS Research Map | TGRS