| Full text | |
| Author(s): |
Total Authors: 4
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| Affiliation: | [1] Univ Estadual Campinas, Reasoning Complex Data Lab RECOD, Inst Comp, BR-13083970 Campinas, SP - Brazil
[2] Univ Colorado, Vis & Scur Technol Lab VAST, Colorado Springs, CO 80933 - USA
Total Affiliations: 2
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| Document type: | Journal article |
| Source: | ACM COMPUTING SURVEYS; v. 43, n. 4 OCT 2011. |
| Web of Science Citations: | 85 |
| 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. (AU) | |
| FAPESP's process: | 07/52015-0 - Approximation methods for visual computing |
| Grantee: | Jorge Stolfi |
| Support Opportunities: | Research Projects - Thematic Grants |
| FAPESP's process: | 08/08681-9 - Digital Image Forensics: Forgery and spoofing detection |
| Grantee: | Anderson de Rezende Rocha |
| Support Opportunities: | Scholarships in Brazil - Post-Doctoral |
| FAPESP's process: | 05/58103-3 - Classifiers and machine learning techniques for image processing and computer vision |
| Grantee: | Anderson de Rezende Rocha |
| Support Opportunities: | Scholarships in Brazil - Doctorate |
| FAPESP's process: | 10/05647-4 - Digital forensics: collection, organization, classification and analysis of digital evidences |
| Grantee: | Anderson de Rezende Rocha |
| Support Opportunities: | Research Grants - Young Investigators Grants |