Digital Forensics, and in a specific way Multimedia Forensics, has grown significantly in the last years. Digital Forensics is defined as the branch of Forensic Science which scientifically analyzes a digital evidence in order to obtain information about it. The Digital 2021 Global Overview Report 1 published in January 2021 certifies that the world’s population has reached the number of 7.83 billion. The 66.6% (i.e. 5.22 billion) use a mobile phone, the 59.5% (i.e. 4.66 billion) use internet and the 53.6% (i.e. 4.2 billion) are social media users. The same report declares that from 2015 to 2020 the daily time spent with social media increased of 34 minutes (it was 1 hours and 51 minutes in 2015) and that it’s destined to rise. In the described scenario the number of shared images, video and audio (or Multimedia) contents become difficult to manage. The described numbers and types of digital evidences have led to the birth of several fields of Digital Forensics, faced from different communities: Multimedia Security, Computer Forensics and Signal Processing. Image Forensics has the goal to obtain information about the most popular digital evidence: images. Developing new algorithms for forensic purposes was the main focus of my Ph.D.. In this thesis some advanced methods will be presented about two specific tasks: the first one is related to the Camera Model Identification (CMI) with the goal to identify the quantization table employed during the first JPEG compression; the second one exploits the image as the digitization of a real paper sheet in order to extract a unique fingerprint. Both the tasks produced relevant methods, widely compared with state-of-the-art to demonstrate their scientific goodness.

Advanced Methods for Image Forensics: First Quantization Estimation and Document Authentication / Guarnera, Francesco. - (2022 May 02).

Advanced Methods for Image Forensics: First Quantization Estimation and Document Authentication

GUARNERA, FRANCESCO
2022

Abstract

Digital Forensics, and in a specific way Multimedia Forensics, has grown significantly in the last years. Digital Forensics is defined as the branch of Forensic Science which scientifically analyzes a digital evidence in order to obtain information about it. The Digital 2021 Global Overview Report 1 published in January 2021 certifies that the world’s population has reached the number of 7.83 billion. The 66.6% (i.e. 5.22 billion) use a mobile phone, the 59.5% (i.e. 4.66 billion) use internet and the 53.6% (i.e. 4.2 billion) are social media users. The same report declares that from 2015 to 2020 the daily time spent with social media increased of 34 minutes (it was 1 hours and 51 minutes in 2015) and that it’s destined to rise. In the described scenario the number of shared images, video and audio (or Multimedia) contents become difficult to manage. The described numbers and types of digital evidences have led to the birth of several fields of Digital Forensics, faced from different communities: Multimedia Security, Computer Forensics and Signal Processing. Image Forensics has the goal to obtain information about the most popular digital evidence: images. Developing new algorithms for forensic purposes was the main focus of my Ph.D.. In this thesis some advanced methods will be presented about two specific tasks: the first one is related to the Camera Model Identification (CMI) with the goal to identify the quantization table employed during the first JPEG compression; the second one exploits the image as the digitization of a real paper sheet in order to extract a unique fingerprint. Both the tasks produced relevant methods, widely compared with state-of-the-art to demonstrate their scientific goodness.
MULTIMEDIA FORENSICS, JPEG, FIRST QUANTIZATION ESTIMATION, DOUBLE QUANTIZATION DETECTION, COMPUTER VISION, DOCUMENT AUTHENTICATION
Advanced Methods for Image Forensics: First Quantization Estimation and Document Authentication / Guarnera, Francesco. - (2022 May 02).
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.11769/539559
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