Automatic Forgery Localization via Artifacts Analysis of JPEG and Resampling

被引:3
|
作者
Wei, Hongbin [1 ]
Yao, Heng [1 ,2 ]
Qin, Chuan [1 ]
Tang, Zhenjun [2 ]
机构
[1] Univ Shanghai Sci & Technol, Sch Opc Elect & Comp Engn, Shanghai 200093, Peoples R China
[2] Guangxi Normal Univ, Guangxi Key Lab Multisource Informat Min & Secur, Guilin 541004, Peoples R China
来源
SECURITY WITH INTELLIGENT COMPUTING AND BIG-DATA SERVICES | 2020年 / 895卷
基金
中国国家自然科学基金;
关键词
Digital forensics; JPEG compression; Resampling effect; Operation chain; PERIODIC PROPERTIES; COMPRESSION; AUTHENTICATION;
D O I
10.1007/978-3-030-16946-6_18
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
With the availability of highly sophisticated editing tools, the authenticity of digital images has now become questionable. The level of image tampering is getting higher and higher, and the tampering procedures become more and more complicated. To recognize the tampering area of the original image, the tampered image is usually executed a series of post-processing. This behavior has greatly increased the difficulty of forgery detection. In this paper, a blind JPEG image forgery detection and localization technique based on JPEG and resampling artifacts analysis is proposed. The process of tampering is to first tamper with JPEG images by bitmaps. Then original JPEG image and tampered area are manipulated by a series of operations, that is, the image is enlarged and then saved as JPEG. A novel tampering localization method is presented based on resampling and JPEG blockness artifacts. Theoretical analysis and experimental results show that the proposed method can effectively identify and locate the tampered region of a spliced image with a JPEG-resampling-JPEG operation chain.
引用
收藏
页码:221 / 234
页数:14
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