Over the past few decades, we have witnessed a huge increase in the use of multimedia content on the internet, for multiple applications ranging from innocuous to critical ones. This development has led to threats posed when content can be manipulated/used for malicious purposes. For example, fake media can be used to drive personal opinions, or for criminal activities such as terrorist propaganda and cyberbullying. This research and practice activity gave rise to the creation of the multimedia forensics field.
In this survey, the latest trends and deep-learning-based techniques for multimedia forensics are introduced, in both architectural and data-processing. Firstly, different techniques used to manipulate content are presented, followed by image and video forgery techniques. Thereafter, deep learning methods for source identification and recent solutions for deepfake detection are covered. Datasets and evaluation metrics are included, and conclusions are presented.
The publication is intended for researchers, students and professionals active in the fields of Deep Learning and Multimedia Forensics.
Over the past few decades, we have witnessed a huge increase in the use of multimedia content on the internet, for multiple applications ranging from innocuous to critical ones. This development has led to threats posed when content can be manipulated/used for malicious purposes. For example, fake media can be used to drive personal opinions, or for criminal activities such as terrorist propaganda and cyberbullying. This research and practice activity gave rise to the creation of the multimedia forensics field.
In this survey, the latest trends and deep-learning-based techniques for multimedia forensics are introduced, in both architectural and data-processing. Firstly, different techniques used to manipulate content are presented, followed by image and video forgery techniques. Thereafter, deep learning methods for source identification and recent solutions for deepfake detection are covered. Datasets and evaluation metrics are included, and conclusions are presented.
The publication is intended for researchers, students and professionals active in the fields of Deep Learning and Multimedia Forensics.
This book is open access. Media forensics has never been more relevant to societal life. Not only media content represents an ever-increasing share of the data traveling on the net and the preferred...
This book presents recent applications and approaches as well as challenges in digital forensic science. One of the evolving challenges that is covered in the book is the cloud forensic analysis...
Developing a knowledge model helps to formalize the difficult task of analyzing crime incidents in addition to preserving and presenting the digital evidence for legal processing. The use of data...
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