Practical implementation of a methodology for digital images authentication using forensics techniques Francisco Rodríguez-Santos 1 , Guillermo Delgado-Gutierréz 1 , Leonardo Palacios-Luengas 1 and Rubén Vazquéz-Medina 1,2 1 ESIME Culhuacan, Instituto Politécnico Nacional, Coyoacán, D. F. 04430, México frodriguezs0901@alumno.ipn.mx 2 CMP+L, Instituto Politécnico Nacional, Ticoman, D.F. 07340, México ruvazquez@ipn.mx Abstract This work presents a forensics analysis methodology implemented to detect modifications in JPEG digital images by analyzing the image’s metadata, thumbnail, camera traces and compression signatures. Best practices related with digital evidence and forensics analysis are considered to determine if the technical attributes and the qualities of an image are consistent with each other. This methodology is defined according to the recommendations of the Good Practice Guide for Computer- Based Electronic Evidence defined by Association of Chief Police Officers of UK; the methodology certainty level is verified by an efficiency coefficient, calculated by the quotient of the number of correct resolutions and the total number of analyzed images. This methodology can help to determine if a specific digital image can be used as evidence, and thereby, help to clarify events or incidents with legal, civil, administrative or criminal implications. Another advantage of the methodology is that it can be applied with open source software tools. Keywords: Forensic Science, Digital Evidence, Image Authenticity, Forensic Analysis Methodology, Digital Image Processing, Image Technical Attributes. 1. Introduction Today it is very common to find digital images due to the high availability of digital cameras in mobile phones. For some people, a picture may be irrelevant, but for some others, it may represent evidence which could be used to clarify facts with legal, civil, administrative or criminal implications. Therefore, a digital image could have a really high impact in our life and it could be much more representative than the oral or written description of an event, especially if it is considered that the description of that event could be distorted by a person, since time causes human memory deficiencies. With the technological advancement in mobile devices, the digital images have become ubiquitous today. However, modifying a digital image without any obvious traces is not a difficult task with the image editing software available these days. Grabler et al. [1] proposed a demonstration-based system for a visual step-by-step succinct generation tutorials of photo manipulations, which include changing the color of the eyes, teeth bleaching and enhancement of the sun setting, among others. Specialized software tools for digital images edition have potentiated the techniques of image manipulation. These tools allow almost everyone being able to improve the visual quality of an image in an effortless way according to their preferences, needs or interests. Also, these tools allow changing the perception of an event captured in a digital image. The motivations for these changes in digital images could be diverse. Some persons might edit a picture to have fun or to sell something. However, some others may try to involve someone in a wrongful act, or to obtain an illegal benefit. Garry and Gerrie [2] showed that changing an image or improving its quality, may cause distortion of the reality perception, creating false records and affecting the memory of the people who watch it. Considering digital images that contain sensitive information that could be used as evidence, it is necessary to ensure the images’ authenticity, in order to prevent that they are used in a malicious way to damage others. Farid and collaborators in different works showed techniques to determine if an image has been modified or not. Johnson and Farid in 2007 [3] described how such composites can be detected by estimating a camera’s intrinsic parameters from the image of a person’s eyes; Farid in 2009 [4] presented an overview of the passive techniques for detecting images forgery considering an image forensics context; Farid and Bravo in 2010 [5] showed that the visual system is remarkably inept at detecting simple geometric inconsistencies in shadows, reflections and perspective distortions, and they showed computational methods that can be applied to detect the inconsistencies that seem to elude the human visual system; Kee and Farid in 2010 [6] described a technique for measuring lighting conditions in an image, and described its use for detecting photographic composites; and finally, O´Brien and Farid in 2012 [7] described the existence of forensic techniques to detect geometric or statistical inconsistencies that result from specific forms of photo manipulation. Particularly, they ACSIJ Advances in Computer Science: an International Journal, Vol. 4, Issue 6, No.18 , November 2015 ISSN : 2322-5157 www.ACSIJ.org 180 Copyright (c) 2015 Advances in Computer Science: an International Journal. All Rights Reserved.