Advances on Sensor Pattern Noise used in Multimedia Forensics and Counter Forensic

Dear Colleauges,

Digital multimedia contents (images, audio, video, etc.) now play an important role in people’s daily lives, in part due to the increasing popularity of smartphones and the consistent capacity improvement of personal computers and network infrastructure. Even today, it is still common for people to trust what they see, rather than what they read. Multimedia Forensics (MF) deals with the recovery of information that can be directly used to measure the trustworthiness of digital multimedia content.

The authenticity of a digital image can be verified through the noise characteristics of an imaging sensor. In particular, sensor pattern noise (SPN) has been used in source camera identification (SCI) and forgery detection. However, this technique can be used maliciously to track or inculpate innocent people. Accordingly, in the last years, the security issues related to multimedia contents have attracted much attention from both academic researchers and industrial practitioners.

Based on this motivation, this Special Issue invites researchers in all related fields (including but not limited to image and video signal processing, machine learning, computer vision and pattern recognition, cyber security, digital forensics) to join us in a quest for pinpointing the next-generation image and video forensics solutions of tomorrow, capable of processing image and video data using the recently-developed deep learning paradigm and other new modelling and learning techniques. The core data used in your work should be visual data (images and videos). The potential topics of interest of this Special Issue are listed below. Submissions can contemplate original research, serious dataset collection and benchmarking, or critical surveys.

Potential topics include, but are not limited to:

• Camera sensor fingerprint recognition
• Camera identification from sensor fingerprints
• Counter forensics
• Cyber threat analysis for image and video data
• Digital image and video forgeries using Sensor Pattern Noise
• Forensic classification of imaging sensor types
• Image and video forgery detection
• Image sensor forgery
• Machine learning techniques in image and video forensics
• Metadata generation, video database indexing, searching and browsing
• Mobile device sensor forensic analysis
• Multi-camera systems in mobile devices
• Multimedia authentication using sensor pattern noise
• Multimedia fingerprinting in mobile devices
• Multimedia processing history identification in mobile devices
• Multimedia source identification in mobile devices
• PRNU-based forgery detection
• PRNU pattern in multimedia forensics
• Sensitive content detection (porn and child porn detection, violence detection)
• Sensor imperfections used in counter forensics techniques
• Source identification of digital image and video
• Surveillance for forensics and security applications
• Sensor format and image and video quality
• Visual analytics for forensics and security applications
• Visual information hiding: Designs and attacks

Prof. Luis Javier García Villalba
Dr. Mario Blaum
Dr. Julio Hernandez-Castro
Dr. Ana Lucila Sandoval Orozco
Guest Editors

Manuscript Submission Information

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Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.