Identification of smartphone-image source and manipulation

Qingzhong Liu, Xiaodong Li, Lei Chen, Hyuk Cho, Peter A. Cooper, Zhongxue Chen, Mengyu Qiao, Andrew H. Sung

Research output: Contribution to book or proceedingConference articlepeer-review

17 Scopus citations

Abstract

As smartphones are being widely used in daily lives, the images captured by smartphones become ubiquitous and may be used for legal purposes. Accordingly, the authentication of smartphone images and the identification of post-capture manipulation are of significant interest in digital forensics. In this paper, we propose a method to determine the smartphone camera source of a particular image and operations that may have been performed on that image. We first take images using different smartphones and purposely manipulate the images, including different combinations of double JPEG compression, cropping, and rescaling. Then, we extract the marginal density in low frequency coordinates and neighboring joint density features on intra-block and inter-block as features. Finally, we employ a support vector machine to identify the smartphone source as well as to reveal the operations. Experimental results show that our method is very promising for identifying both smartphone source and manipulations. Our study also indicates that applying unsupervised clustering and supervised classification together (clustering first, followed by classification) leads to improvement in identifying smartphone sources and manipulations and thus provides a means to address the complexity issue of intentional manipulation.

Original languageEnglish
Title of host publicationAdvanced Research in Applied Artificial Intelligence - 25th International Conference on Industrial Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2012, Proceedings
Pages262-271
Number of pages10
DOIs
StatePublished - 2012
Event25th International Conference on Industrial Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2012 - Dalian, China
Duration: Jun 9 2012Jun 12 2012

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume7345 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference25th International Conference on Industrial Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2012
Country/TerritoryChina
CityDalian
Period06/9/1206/12/12

Scopus Subject Areas

  • Theoretical Computer Science
  • General Computer Science

Keywords

  • Image forensics
  • JPEG images
  • classification
  • hierarchical clustering
  • neighboring joint density
  • operation
  • smartphone identification
  • source
  • support vector machine

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