The pervasive availability of the Internet, allied with the spread of increasingly powerful digital facilities, has led digital multimedia to be the primary source of visual information in many aspect of our society, including media, politics, national security and advertisement. However, the historical assumption that photographs can be trusted as a true representation of reality does not hold anymore. Nowadays, affordable and sophisticated graphics editing software allow for the creation of sophisticated and visually compelling photographic fakes, which easily puzzle our perception of reality. Trustworthiness of the information conveyed by digital media is becoming one of the key challenges for our information society, strongly affecting the success and penetration of future multimedia applications. The urgent need of efficient techniques to cope with security issues related with multimedia data motivates the MMLab research. Multimedia forensics techniques are particularly relevant as they deal with the recovery of information that can be directly used to authenticate and estimate the trustworthiness of digital multimedia contents.
Digital forensics is rapidly emerging as an effective solution to cope with multimedia security issues, developing powerful techniques to detect a wide-variety of tampering in ordinary images. The inspiring principle behind passive forensics techniques is that although most forms of tampering may not leave any obvious visual traces, they may disturb some inherent properties of the image. To the extent that these perturbations can be quantified and detected, they can be used to invalidate or authenticate a digital content. This technology is said to be passive, since it can operate where no prior information about the content is available or no integrity protection mechanisms (e.g. digital watermarking) have been previously applied.
Digital Source Identification
Source identification for digital content is one of the branches of digital image forensics, whose aim is to establish a link between an image and its acquisition device (e.g., camera, mobile phone, scanner), by exploiting traces left by the different steps taken during the image acquisition process. The basic assumption is that digital contents are overlaid by a characteristic noise-like pattern that represents a unique intrinsic fingerprint of the specific acquisition device. Such a noise is invisible to the human eye, but it can be analysed to successfully contribute to identification.
Computer Generated vs Natural Imagery
Counter-forensics (or anti-forensics) is a brand new research field in digital forensic science, which aims at identifying weaknesses in existing forensic techniques so to find a way to fool them. The basic assumption is that forensic techniques can be deceived whenever the forger is aware of the forensic tools and adopts speciﬁc countermeasures, namely counter-forensic attacks. Such kind of attacks are usually targeted to a single or a class of forensic tools and try to conceal the traces of a speciﬁc manipulation.
Digital watermarking is referred to as the procedure of embedding some information (watermark) into digital multimedia content (image, video or audio), possibly in an imperceptible way not to degrade the quality of the content. Such embedded information can be extracted or detected at any later stage for different purposes, including ownership proof, copyright protection, access control and tamper detection. This technology is said to be active, since it requires a known information to be embedded onto the content at the time of recording ( or a person to embed it at the time of sending).