Integration of biometrics and steganography: A comprehensive review

The use of an individual’s biometric characteristics to advance authentication and verification technology beyond the current dependence on passwords has been the subject of extensive research for some time. Since such physical characteristics cannot be hidden from the public eye, the security of digitised biometric data becomes paramount to avoid the risk of substitution or replay attacks. Biometric systems have readily embraced cryptography to encrypt the data extracted from the scanning of anatomical features. Significant amounts of research have also gone into the integration of biometrics with steganography to add a layer to the defence-in-depth security model, and this has the potential to augment both access control parameters and the secure transmission of sensitive biometric data. However, despite these efforts, the amalgamation of biometric and steganographic methods has failed to transition from the research lab into real-world applications. In light of this review of both academic and industry literature, we suggest that future research should focus on identifying an acceptable level steganographic embedding for biometric applications, securing exchange of steganography keys, identifying and address legal implications, and developing industry standards

A Bimodal Biometric Student Attendance System

A lot of attempts have been made to use biometrics in class attendance systems. Most of the implemented biometric attendance systems are unimodal. Unimodal biometric systems may be spoofed easily, leading to a reduction in recognition accuracy. This paper explores the use of bimodal biometrics to improve the recognition accuracy of automated student attendance systems. The system uses the face and fingerprint to take students’ attendance. The students’ faces were captured using webcam and preprocessed by converting the color images to grey scale images. The grey scale images were then normalized to reduce noise. Principal Component Analysis (PCA) algorithm was used for facial feature extraction while Support Vector Machine (SVM) was used for classification. Fingerprints were captured using a fingerprint reader. A thinning algorithm digitized and extracted the minutiae from the scanned fingerprints. The logical technique (OR) was used to fuse the two biometric data at the decision level. The fingerprint templates and facial images of each user were stored along with their particulars in a database. The implemented system had a minimum recognition accuracy of 87.83%

Multimedia security and privacy protection in the internet of things: research developments and challenges

With the rapid growth of the internet of things (IoT), huge amounts of multimedia data are being generated from and/or exchanged through various IoT devices, systems and applications. The security and privacy of multimedia data have, however, emerged as key challenges that have the potential to impact the successful deployment of IoT devices in some data-sensitive applications. In this paper, we conduct a comprehensive survey on multimedia data security and privacy protection in the IoT. First, we classify multimedia data into different types and security levels according to application areas. Then, we analyse and discuss the existing multimedia data protection schemes in the IoT, including traditional techniques (e.g., cryptography and watermarking) and emerging technologies (e.g., blockchain and federated learning). Based on the detailed analysis on the research development of IoT-related multimedia security and privacy protection, we point out some open challenges and provide future research directions, aiming to advance the study in the relevant fields and assist researchers in gaining a deeper understanding of the state of the art on multimedia data protection in the IoT

Watermarking techniques for genuine fingerprint authentication.

Fingerprints have been used to authenticate people remotely and allow them access to a system. However, the fingerprint-capture sensor is cracked easily using false fingerprint features constructed from a glass surface. Fake fingerprints, which can be easily obtained by attackers, could cheat the system and this issue remains a challenge in fingerprint-based authentication systems. Thus, a mechanism that can validate the originality of fingerprint samples is desired. Watermarking techniques have been used to enhance the fingerprint-based authentication process, however, none of them have been found to satisfy genuine person verification requirements. This thesis focuses on improving the verification of the genuine fingerprint owner using watermarking techniques. Four research issues are being addressed to achieve the main aim of this thesis. The first research task was to embed watermark into fingerprint images collected from different angles. In verification systems, an acquired fingerprint image is compared with another image, which was stored in the database at the time of enrolment. The displacements and rotations of fingerprint images collected from different angles lead to different sets of minutiae. In this case, the fingerprint-based authentication system operates on the ‘close enough’ matching principle between samples and template. A rejection of genuine samples can occur erroneously in such cases. The process of embedding watermarks into fingerprint samples could make this worse by adding spurious minutiae or corrupting correct minutiae. Therefore, a watermarking method for fingerprint images collected from different angles is proposed. Second, embedding high payload of watermark into fingerprint image and preserving the features of the fingerprint from being affected by the embedded watermark is challenging. In this scenario, embedding multiple watermarks that can be used with fingerprint to authenticate the person is proposed. In the developed multi-watermarks schema, two watermark images of high payloads are embedded into fingerprints without significantly affecting minutiae. Third, the robustness of the watermarking approach against image processing operations is important. The implemented fingerprint watermarking algorithms have been proposed to verify the origin of the fingerprint image; however, they are vulnerable to several modes of image operations that can affect the security level of the authentication system. The embedded watermarks, and the fingerprint features that are used subsequently for authentication purposes, can be damaged. Therefore, the current study has evaluated in detail the robustness of the proposed watermarking methods to the most common image operations. Fourth, mobile biometrics are expected to link the genuine user to a claimed identity in ubiquitous applications, which is a great challenge. Touch-based sensors for capturing fingerprints have been incorporated into mobile phones for user identity authentication. However, an individual fake fingerprint cracking the sensor on the iPhone 5S is a warning that biometrics are only a representation of a person, and are not secure. To make thing worse, the ubiquity of mobile devices leaves much room for adversaries to clone, impersonate or fabricate fake biometric identities and/or mobile devices to defraud systems. Therefore, the integration of multiple identifiers for both the capturing device and its owner into one unique entity is proposed

Cybersecurity: Past, Present and Future

The digital transformation has created a new digital space known as cyberspace. This new cyberspace has improved the workings of businesses, organizations, governments, society as a whole, and day to day life of an individual. With these improvements come new challenges, and one of the main challenges is security. The security of the new cyberspace is called cybersecurity. Cyberspace has created new technologies and environments such as cloud computing, smart devices, IoTs, and several others. To keep pace with these advancements in cyber technologies there is a need to expand research and develop new cybersecurity methods and tools to secure these domains and environments. This book is an effort to introduce the reader to the field of cybersecurity, highlight current issues and challenges, and provide future directions to mitigate or resolve them. The main specializations of cybersecurity covered in this book are software security, hardware security, the evolution of malware, biometrics, cyber intelligence, and cyber forensics. We must learn from the past, evolve our present and improve the future. Based on this objective, the book covers the past, present, and future of these main specializations of cybersecurity. The book also examines the upcoming areas of research in cyber intelligence, such as hybrid augmented and explainable artificial intelligence (AI). Human and AI collaboration can significantly increase the performance of a cybersecurity system. Interpreting and explaining machine learning models, i.e., explainable AI is an emerging field of study and has a lot of potentials to improve the role of AI in cybersecurity.Comment: Author's copy of the book published under ISBN: 978-620-4-74421-

Data Hiding and Its Applications

Data hiding techniques have been widely used to provide copyright protection, data integrity, covert communication, non-repudiation, and authentication, among other applications. In the context of the increased dissemination and distribution of multimedia content over the internet, data hiding methods, such as digital watermarking and steganography, are becoming increasingly relevant in providing multimedia security. The goal of this book is to focus on the improvement of data hiding algorithms and their different applications (both traditional and emerging), bringing together researchers and practitioners from different research fields, including data hiding, signal processing, cryptography, and information theory, among others