Vision of the unseen

Author:

Rocha Anderson1,Scheirer Walter2,Boult Terrance2,Goldenstein Siome1

Affiliation:

1. University of Campinas, São Paulo, Brazil

2. University of Colorado at Colorado Springs, Colorado Springs

Abstract

Digital images are everywhere—from our cell phones to the pages of our online news sites. How we choose to use digital image processing raises a surprising host of legal and ethical questions that we must address. What are the ramifications of hiding data within an innocent image? Is this an intentional security practice when used legitimately, or intentional deception? Is tampering with an image appropriate in cases where the image might affect public behavior? Does an image represent a crime, or is it simply a representation of a scene that has never existed? Before action can even be taken on the basis of a questionable image, we must detect something about the image itself. Investigators from a diverse set of fields require the best possible tools to tackle the challenges presented by the malicious use of today's digital image processing techniques. In this survey, we introduce the emerging field of digital image forensics, including the main topic areas of source camera identification, forgery detection, and steganalysis. In source camera identification, we seek to identify the particular model of a camera, or the exact camera, that produced an image. Forgery detection's goal is to establish the authenticity of an image, or to expose any potential tampering the image might have undergone. With steganalysis, the detection of hidden data within an image is performed, with a possible attempt to recover any detected data. Each of these components of digital image forensics is described in detail, along with a critical analysis of the state of the art, and recommendations for the direction of future research.

Funder

Fundação de Amparo à Pesquisa do Estado de São Paulo

Conselho Nacional de Desenvolvimento Científico e Tecnológico

U.S. Air Force

Publisher

Association for Computing Machinery (ACM)

Subject

General Computer Science,Theoretical Computer Science

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