Contextual biometric watermarking of fingerprint images

This research presents contextual digital watermarking techniques using face and demographic text data as multiple watermarks for protecting the evidentiary integrity of fingerprint image. The proposed techniques embed the watermarks into selected regions of fingerprint image in MDCT and DWT domains. A general image watermarking algorithm is developed to investigate the application of MDCT in the elimination of blocking artifacts. The application of MDCT has improved the performance of the watermarking technique compared to DCT. Experimental results show that modifications to fingerprint image are visually imperceptible and maintain the minutiae detail. The integrity of the fingerprint image is verified through high matching score obtained from the AFIS system. There is also a high degree of correlation between the embedded and extracted watermarks. The degree of similarity is computed using pixel-based metrics and human visual system metrics. It is useful for personal identification and establishing digital chain of custody. The results also show that the proposed watermarking technique is resilient to common image modifications that occur during electronic fingerprint transmission

A Framework to Detect Presentation Attacks

Biometric-based authentication systems are becoming the preferred choice to replace password-based authentication systems. Among several variations of biometrics (e.g., face, eye, fingerprint), iris-based authentication is commonly used in every day applications. In iris-based authentication systems, iris images from legitimate users are captured and certain features are extracted to be used for matching during the authentication process. Literature works suggest that iris-based authentication systems can be subject to presentation attacks where an attacker obtains printed copy of the victim’s eye image and displays it in front of an authentication system to gain unauthorized access. Such attacks can be performed by displaying static eye images on mobile devices or iPad (known as screen attacks). As iris features are not changed, once an iris feature is compromised, it is hard to avoid this type of attack. Existing approaches relying on static features of the iris are not suitable to prevent presentation attacks. Feature from live Iris (or liveness detection) is a promising approach. Further, additional layer of security from iris feature can enable hardening the security of authentication system that existing works do not address. To address these limitations, this thesis proposed iris signature generation based on the area between the pupil and the cornea . Our approach relies on capturing iris images using near infrared light. We train two classifiers to capture the area between the pupil and the cornea. The image of iris is then stored in the database. This approach generates a QR code from the iris. The code acts as a password (additional layer of security) and a user is iii required to provide it during authentication. The approach has been tested using samples obtained from publicly available iris database. The initial results show that the proposed approach has lower false positive and false negative rates

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 communications means for most users, it has also become integral part of most innovative applications in the digital information ecosystem that serves various sectors of society, from the entertainment, to journalism, to politics. Undoubtedly, the advances in deep learning and computational imaging contributed significantly to this outcome. The underlying technologies that drive this trend, however, also pose a profound challenge in establishing trust in what we see, hear, and read, and make media content the preferred target of malicious attacks. In this new threat landscape powered by innovative imaging technologies and sophisticated tools, based on autoencoders and generative adversarial networks, this book fills an important gap. It presents a comprehensive review of state-of-the-art forensics capabilities that relate to media attribution, integrity and authenticity verification, and counter forensics. Its content is developed to provide practitioners, researchers, photo and video enthusiasts, and students a holistic view of the field

Biometric Verification System for Automated Teller Machine (ATM)

Biometric Verification System for Automated Teller Machine (ATM) will serve as an alternative for the current verification system that uses ATM card and personal identification number (PIN) to protect against fraud and effectively eliminating most common attempts to gain unauthorized access. With biometric technology, customer can gain access to their account through smart card approach combined with biometric technology to automatically identify individuals using their distinct physical or behavioral characteristics. The main objective of this project is to solve the problems that arise from using PIN as the base of ATM verification system. These include unauthorized access into financial accounts, stealing money, ATM fraud and many more. To ensure a reliable project output, the author had outlined the scope of study for the proposed project. It involves the study of ATM system, biometrics technology, architecture, the benefits and the drawback of each approach and the current trend in the market. The development of this system will be based on the RAD methodology

Defending Against Insider Use of Digital Steganography

The trusted insider is among the most harmful and difficult to detect threats to information security, according to the Federal Plan for Information Assurance and Cyber Security Research and Development released in April 2006. By default, employees become trusted insiders when granted the set of privileges needed to do their jobs, which typically includes access to the Internet. It is generally presumed the insiders are loyally working to achieve the organization’s goals and objectives and would not abuse the privileges given to them. However, some insiders will inevitably abuse some of their privileges. For example, a trusted insider might abuse their privilege of access to the Internet to download, install, and use an information hiding tool, such as one of the hundreds of digital steganography applications available on the Internet, to steal sensitive, classified, or proprietary information. Effective countermeasures to this threat must begin with an organizational policy prohibiting installation of information hiding tools on user workstations and must also include automated tools capable of detecting attempts to download and use digital steganography applications. This paper will describe the threat from insider use of digital steganography applications; a new approach to detecting the presence or use of these applications; and extraction of hidden information when a known signature of one of these applications is detected. The analytical approach to steganalysis involves the development and use of computer forensic tools that can detect fingerprints and signatures of digital steganography applications. These tools can be employed in both an off-line forensic-based mode as well as a real-time network surveillance mode. Detection of fingerprints or signatures in either mode may lead to the discovery and extraction of hidden information. Accordingly, this approach represents a significant improvement over traditional blind detection techniques which typically only provide a probability that information may be hidden in a given file without providing a capability to extract any hidden information. Keywords: insider, steganography, steganalysis, computer forensics, artifacts, fingerprints, hash values, signature

Application of Digital Fingerprinting: Duplicate Image Detection

Identifying the content automatically is the most necessary condition to detect and fight piracy. Watermarking the image is the most basic and common technique to fight piracy. But the effectiveness of watermark is limited. Image fingerprinting provides an alternate and efficient solution for managing and identifying the multimedia content. After registering the original image contents, by comparing the colluded image with the original one, the percentage of distortion can be calculated. In this paper presented are one such fingerprinting-based forensic application: Duplicate image detection. To authenticate image content perceptual hash is an efficient solution. Perceptual hashes of almost similar images or near duplicate images are very similar to each other making it easier to compare images unlike cryptographic hashes which vary very radically even in the case of small distortions. Potential applications are unlimited including digital forensics, protection of copyrighted material etc. However, conventional image hash algorithms only offer a limited authentication level for the protection of overall content. In this work, we compared and contrasted different perceptual hashes and proposed a image hashing algorithm which is an excellent trade off of accuracy and speed

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 communications means for most users, it has also become integral part of most innovative applications in the digital information ecosystem that serves various sectors of society, from the entertainment, to journalism, to politics. Undoubtedly, the advances in deep learning and computational imaging contributed significantly to this outcome. The underlying technologies that drive this trend, however, also pose a profound challenge in establishing trust in what we see, hear, and read, and make media content the preferred target of malicious attacks. In this new threat landscape powered by innovative imaging technologies and sophisticated tools, based on autoencoders and generative adversarial networks, this book fills an important gap. It presents a comprehensive review of state-of-the-art forensics capabilities that relate to media attribution, integrity and authenticity verification, and counter forensics. Its content is developed to provide practitioners, researchers, photo and video enthusiasts, and students a holistic view of the field