Security – serie

The Internet of Things (IoT) - the emerging global interconnection of billions of 'smart' devices - will be collecting increasing amounts of private and sensitive data about our lives, and will require increasing degrees of reliability and trustworthiness in terms of the levels of assurance provided with respect to confidentiality, integrity and availability. This book examines these important security considerations for the IoT.Topics covered include a security survey of middleware for the IoT; privacy in the IoT; privacy and consumer IoT - a sensemaking perspective; a secure platform for smart cities and IoT; model - based security engineering for the IoT; federated identity and access management in IoT systems; the security of the MQTT protocol; securing communications among severely constrained, wireless embedded devices; lightweight cryptographic identity solutions for the IoT; and a reputation model for the IoT.

Mobile biometrics - the use of physical and/or behavioral characteristics of humans to allow their recognition by mobile/smart phones - aims to achieve conventional functionality and robustness while also supporting portability and mobility, bringing greater convenience and opportunity for its deployment in a wide range of operational environments from consumer applications to law enforcement. But achieving these aims brings new challenges such as issues with power consumption, algorithm complexity, device memory limitations, frequent changes in operational environment, security, durability, reliability, and connectivity. Mobile Biometrics provides a timely survey of the state of the art research and developments in this rapidly growing area.Topics covered in Mobile Biometrics include mobile biometric sensor design, deep neural network for mobile person recognition with audio-visual signals, active authentication using facial attributes, fusion of shape and texture features for lip biometry in mobile devices, mobile device usage data as behavioral biometrics, continuous mobile authentication using user phone interaction, smartwatch-based gait biometrics, mobile four-fingers biometrics system, palm print recognition on mobile devices, periocular region for smartphone biometrics, and face anti-spoofing on mobile devices.

Iris recognition technologies for identity management are already deployed globally in several large-scale nationwide biometric projects and are currently entering the mobile market. More recently, periocular recognition has been employed to augment the biometric performance of the iris in unconstrained environments where only the ocular region is present in the image.Iris and Periocular Biometric Recognition provides an overview of scientific fundamentals and principles of iris and periocular biometric recognition over six broad areas: an introduction to iris and periocular recognition; a selective overview of issues and challenges; soft biometric classification; security aspects; privacy protection and forensics; and future trends. With contributions from experts in industry and academia, this book is essential reading for researchers, graduate students and practitioners in biometrics and related fields.

Cloud Computing has already been embraced by many organizations and individuals due to its benefits of economy, reliability, scalability and guaranteed quality of service among others. But since the data is not stored, analysed or computed on site, this can open security, privacy, trust and compliance issues. This one-stop reference covers a wide range of issues on data security in Cloud Computing ranging from accountability, to data provenance, identity and risk management.Data Security in Cloud Computing covers major aspects of securing data in Cloud Computing. Topics covered include NOMAD: a framework for ensuring data confidentiality in mission-critical cloud based applications; 3DCrypt: privacy-preserving pre-classification volume ray-casting of 3D images in the cloud; multiprocessor system-on-chip for processing data in Cloud Computing; distributing encoded data for private processing in the cloud; data protection and mobility management for cloud; understanding software defined perimeter; security, trust and privacy for Cloud Computing in transportation cyber-physical systems; review of data leakage attack techniques in cloud systems; Cloud Computing and personal data processing: sorting out legal requirements; the Waikato data privacy matrix; provenance reconstruction in clouds; and security visualization for Cloud Computing.

Hand-based biometrics identifies users by unique features in their hands, such as fingerprints, palmprints, hand geometry, and finger and palm vein patterns. This book explores the range of technologies and methods under development and in use for hand-based biometrics, with evaluations of the advantages and performance of each. The inclusion of significant material on the relevant aspects of the physiology of the hand is a particularly useful and innovative feature.Topics covered in this book include inner and outer hand physiology and diseases; nail structure and common disorders; fingerprint recognition; synthetic fingerprints; finger vein recognition; palm vein biometrics; hand shape recognition and palm print recognition; 3D hand shape recognition; and spoofing and anti-spoofing methods.With contributions from an international panel of experts in this field, Hand-Based Biometrics is essential reading for researchers, students and engineers working in biometrics and security.

Critical systems and infrastructure rely heavily on ICT systems and networks where security issues are a major concern. Authentication methods verify that messages come from trusted sources and guarantee the smooth flow of information and data. In this edited reference, the authors present state-of-art research and development in authentication technologies including challenges and applications for Cloud Technologies, IoT and Big Data. Topics covered include authentication; cryptographic algorithms; digital watermarking; biometric authentication; block ciphers with applications in IoT; identification schemes for Cloud and IoT; authentication issues for Cloud applications; cryptography engines for Cloud based on FPGA; and data protection laws.

With the rapid evolution of cyberspace, computing, communications and sensing technologies, organizations and individuals rely more and more on new applications such as fog and cloud computing, smart cities, Internet of Things (IoT), collaborative computing, and virtual and mixed reality environments. Maintaining their security, trustworthiness and resilience to cyber-attacks has become crucial which requires innovative and creative cyber security and resiliency solutions. Computing algorithms have been developed to mimic the operation of natural processes, phenomena and organisms such as artificial neural networks, swarm intelligence, deep learning systems, biomimicry, and more. The amazing characteristics of these systems offer a plethora of novel methodologies and opportunities to cope with emerging cyber challenges.This edited book presents a timely review of the fundamentals, latest developments and diverse applications of nature-inspired algorithms in cyber security and resiliency. Topics include bio-inspired collaboration and cyber security; immune-based defense and resiliency; bio-inspired security and resiliency of network traffic; nature inspired machine learning approach for cyber security; nature-inspired algorithms in A.I. for malicious activity detection; DNA-inspired characterization and detection of novel social Twitter spambots; nature-inspired approaches for social network security; bio-inspired cyber-security for smart grid; nature-inspired cryptography and cryptanalysis, and more.

Voice biometrics are being implemented globally in large scale applications such as remote banking, government e-services, transportation and building security access, autonomous vehicles, and healthcare. They have been integrated in numerous apps, often coupled with face biometrics and artificial intelligence methods. Voice biometrics products and solutions must meet three key requirements for the success in their deployment: they must be highly trustable regarding privacy protection; easy to use and always be available.This edited book presents the state of the art in voice biometrics research and technologies including implementation and deployment challenges in terms of interoperability, scalability and performance, and security. The team of editors and chapter authors combine a wealth of expertise from academia and the industry. Topics covered include the fundamentals of voice biometrics; design of countermeasures for replay attack; attacker's perspective for voice biometrics; voice biometrics; speaker de-identification; performance evaluation of voice biometrics solutions; standardization of voice biometrics technology; industry perspectives; joining forces of voice and facial biometrics; and future trends and challenges in voice biometrics.Providing comprehensive coverage of the field of voice biometrics, this authoritative volume will be of great interest to researchers, scientists, engineers, practitioners and advanced students involved in the fields of security, biometrics, forensic sciences, human computer interaction, speech processing, acoustics, multimedia, pattern recognition, and privacy-preserving, digital signal processing and speech technologies. It will also be of interest to researchers and professionals working in law and criminology.

As AI technologies progress and influence more facets of our lives, the requirement for openness and interpretability becomes increasingly important. Explainable AI (XAI) has the potential to be a paradigm shift in the next generation of AI systems. XAI strives to make AI algorithms and methods understandable by tackling trust, bias, compliance, and accountability challenges. XAI improves model disclosure, produces intrinsically interpretable deep learning approaches, offers real-time rationales, and promotes legitimate AI practice. These advances assist in the development of a more ethically sound AI ecosystem.As the IoT evolves and supply chains become more complex, novel avenues for attack arise. The ever-changing threat landscape includes powerful adversaries such as malicious actors and hackers who are always refining their strategies, and demand ongoing monitoring and adaptive responses. Cybersecurity helps safeguard data, identify fraud, protect vital infrastructure, and ensure confidentiality. Considering the dynamic nature of the cybersecurity battlefront, a holistic approach must include pre-emptive threat intelligence, staff training, effective security tools, regular upgrades, and global collaboration. Explainable AI (XAI) explains security alerts, reduces false positives and enables faster incident response.The objective of this book is to explore how the integration of XAI-based cybersecurity algorithms and methods support threat detection and decision-making by preserving privacy and trust, ensuring interpretability and accountability, and optimizing computational and communication costs.This book will be a useful reference for computing and security researchers, scientists, and IT professionals in academia and industry, who are developing and designing innovative cyber threat and vulnerability detection systems and solutions, as well as advanced students and lecturers to better understand AI and XAI algorithms for cybersecurity applications.

Technology plays a pivotal role in today's financial landscape. Ensuring cybersecurity and safety in the banking sector has become paramount. The pervasive integration of technology in banking operations has brought unprecedented convenience but also heightened the vulnerability of financial institutions to cyber threats. High-profile breaches and the potential consequences of compromised financial data have underscored the urgency of comprehensively addressing cyber security and safety in banking.Cybersecurity in banking faces unique challenges due to the complex nature of financial transactions and the attractiveness of banks as prime targets for cybercriminals. The challenges include the constant evolution of cyber threats, insider threats, and the need to balance security measures with customer convenience. Educating customers about cyber threats and safe online practices is a critical component of cyber security in banking. Banks must actively engage in awareness campaigns, providing customers with information on identifying phishing attempts, secure online banking practices, and the importance of regularly updating passwords.This book aims to dissect the multifaceted challenges posed by cyber threats in today's dynamic banking landscape and propose novel fintech approaches to fortify the security fabric of the banking sector. The ultimate aim is to raise awareness about the challenges, promote proactive measures, and contribute to the safeguarding and integrity of the financial sector. Researchers, engineers and scientists in academia and industry working in the fields of cybersecurity and fintech, and in related areas of computing, data science, artificial intelligence, mobile and wireless computing and networking, will find this book to be a useful source of information on developments in its field.

We are living in an AI and data-driven era. A huge volume of data is generated from all sectors including smart cities, intelligent transportation systems, smart healthcare, education, smart agriculture and smart industrial processes. This information comprises multiple modalities such as textual data, images, sound, gestures and genetic sequences, which are generated through various sources.The internet of multimedia things (IoMT) is one of the key contributors to the collection, analysis and management of voluminous multimodal data. The dominating features of IoMTs are well-timed delivery of data and dependability, but they require high levels of memory and computational power, which requires higher bandwidth and more power. Therefore, they require rigorous quality of service (QoS) and efficient, reliable and secure network frameworks.The objective of this book is to explore machine learning (ML) and deep learning (DL) techniques for securing data with multiple modalities in a wide range of data-centric smart applications in the IoMT framework. In all data-centric application domains where on-time availability of data and reliability are the major concerns, IoMT is contributing significantly. The authors present the challenges faced to organize and process multimodal data in data-centric applications, several types of data modalities, and innovative IoMT frameworks. A particular focus is placed on the role of ML and DL techniques in securing multi-modal data for real-time monitoring in smart environment applications.Machine Learning and Deep Learning Driven Techniques for Multimodal Data Security in the Internet of Multimedia Things caters to the needs of AI, big data and IoT advanced students, academic and industry researchers, engineers, security experts, data analysts, and AI and data-centric application developers.

Emerging and pivotal technologies such as artificial intelligence and deep learning, cloud computing, internet of things, blockchain, encryption, and quantum cryptography are required to meet multimedia data's evolving needs and security requirements. In digital imaging, a pixel is the smallest element of an image that can be manipulated through software. Pixels within a digital image or graphical user interface must be secured to control unauthorized access or manipulation.In this edited book, the contributors investigate the design and implementation of effective security solutions and their integration in multimedia applications to ensure authenticity and integrity in the digital age. Coverage includes how to secure pixels within a digital image or graphical user interface to control unauthorized access or manipulation.Fortressing Pixels: Information security for images, videos, audio and beyond is intended to equip readers with the knowledge and mechanisms required to safeguard assets and protect their innovative creations, business interests, and private sensitive data. Academic researchers and engineers, will find a useful resource in this book, as will industry technology professionals working in cybersecurity, forensics, computing, networking, image processing and multimedia data science.

Privacy by design is a proactive approach that promotes privacy and data protection compliance throughout project lifecycles when storing or accessing personal data. Privacy by design is essential for the Internet of Things (IoT) as privacy concerns and accountability are being raised in an increasingly connected world. What becomes of data generated, collected or processed by the IoT is clearly an important question for all involved in the development, manufacturing, applications and use of related technologies. But this IoT concept does not work well with the 'big data' trend of aggregating pools of data for new applications. Developers need to address privacy and security issues and legislative requirements at the design stage, and not as an afterthought.In this edited book, the authors draw on a wealth of interdisciplinary research to delineate the challenges of building accountability into the Internet of Things and solutions for delivering on this critical societal challenge. This advanced book brings together legal-tech scholars, computer scientists, human computer interaction researchers and designers and socials scientists to address these challenges and elaborate solutions. It articulates the accountability principle in law and how it impacts IoT development, presents empirical studies of accountability in action and its implications for IoT development, brings technological responses to the requirements of GDPR and ways of building accountability into the IoT, and covers compliant IoT application development, privacy-preserving data analytics, human-centred IoT security, human-data interaction, and the methodological challenge of understanding and responding to the adoption of future technologies in everyday life.

Internet of Things (IoTs) are now being integrated at a large scale in fast-developing applications such as healthcare, transportation, education, finance, insurance and retail. The next generation of automated applications will command machines to do tasks better and more efficiently. Both industry and academic researchers are looking at transforming applications using machine learning and deep learning to build better models and by taking advantage of the decentralized nature of Blockchain. But the advent of these new technologies also brings very high expectations to industries, organisations and users. The decrease of computing costs, the improvement of data integrity in Blockchain, and the verification of transactions using Machine Learning are becoming essential goals.This edited book covers the challenges, opportunities, innovations, new concepts and emerging trends related to the use of machine learning, Blockchain and Big Data analytics for IoTs. The book is aimed at a broad audience of ICTs, data science, machine learning and cybersecurity researchers interested in the integration of these disruptive technologies and their applications for IoTs.

Wireless physical layer (PHY) security has attracted much attention due to the broadcast nature of the wireless medium and its inherent vulnerability to eavesdropping, jamming, and interference.Physical Layer Security for Wireless Sensing and Communication covers both communication and sensing security from a broad perspective. The main emphasis is on PHY security, although other security measures are covered for the sake of completeness and as a step towards cross-layer security and cognitive security vision. After discussing the features of wireless channels from both the communication and sensing perspectives, the book details their exploitation for secure transmission utilizing various approaches. Wireless sensing and radio environment concepts are also addressed, along with the related security implications in terms of eavesdropping, disruption, manipulation, and, in general, the exploitation of wireless sensing by unauthorised users. Several solutions for these threats from the domains of wireless communication, military radars, and machine learning, are discussed.The book provides valuable information to researchers in academia and industry, as well as engineers, developers, and advanced students in the field of cybersecurity.

Blockchain is a digital ledger of transactions duplicated and distributed across an entire network of computer systems on the blockchain which makes it more difficult to hack or tamper with. The popularity of blockchain has been increasing with the growth of social media and the internet of things (IoT). Social media are interactive digitally mediated technologies that facilitate the creation or sharing and exchange of information, ideas, opinions and interests via virtual communities and social network platforms. However, unmonitored social accounts can be the target of hackers who post fraudulent messages or virus-infected links that spread to contacts and followers, and "employee weakness" is responsible for 20% of cyberattacks in companies. So, it has become essential to secure both personal and professional social media networks, accounts and data.Blockchain Technology for Secure Social Media Computing covers recent advances, trends and future opportunities in the security framework of social media-computing. The contributors focus on how to protect social media platforms, and present methods for making social media computing more reliable and effective to achieve trusted IoT-based social computing with blockchain technology.The book is aimed at an advanced research audience in industry and academia focused on blockchain technology and social media computing working in cybersecurity, security data analytics, computer science, distributed computing, networking, internet of things and related fields of applications. It will be also of interest to application and software developers and project managers using blockchain technology and multiple encryptions.

The integration of new technologies is resulting in an increased demand for security and authentication in all types of data communications. Cybersecurity is the protection of networks and systems from theft. Biometric technologies use unique traits of particular parts of the body such facial recognition, iris, fingerprints and voice to identify individuals' physical and behavioural characteristics. Although there are many challenges associated with extracting, storing and processing such data, biometric and cybersecurity technologies along with artificial intelligence (AI) are offering new approaches to verification procedures and mitigating security risks.This book presents cutting-edge research on the use of AI for biometrics and cybersecurity including machine and deep learning architectures, emerging applications and ethical and legal concerns. Topics include federated learning for enhanced cybersecurity; artificial intelligence-based biometric authentication using ECG signal; deep learning for email phishing detection methods; biometrics for secured IoT systems; intelligent authentication using graphical one-time-passwords; and AI in social cybersecurity.Artificial Intelligence for Biometrics and Cybersecurity: Technology and applications is aimed at artificial intelligence, biometrics and cybersecurity experts, industry and academic researchers, network security engineers, cybersecurity professionals, and advanced students and newcomers to the field interested in the newest advancements in artificial intelligence for cybersecurity and biometrics.

Fifth generation (5G) wireless networks are now commercialized, and the research focus has shifted towards sixth generation (6G) wireless systems. The integration of sensor nodes and massive machine type communication (MTC) devices (MDs) in ubiquitous 5G networks has facilitated the design of critical enabling technologies to support billions of data-hungry applications. By leveraging sensor nodes in wireless sensor networks (WSNs), sensitive user information can be harvested and transmitted to receivers via WSN-assisted channels, which are often not well secured. Consequently, sensitive user information can be intercepted and used unlawfully. The security and confidentiality measures used for data transmission over existing 5G WSN-assisted channels are limited. 6G systems are envisaged to face fiercer security challenges. In 6G wireless networks, a new set of sensing and precise localization techniques are predicted. Thus, the need to secure user information against adversarial attacks needs to be implemented at the design stage.The book proposes viable solutions to revamp traditional security architecture by addressing critical security challenges in commercialized 5G and envisioned 6G wireless communication systems. Expert contributors bring new insights into real-world scenarios for the deployment, applications and management of robust, secure, and efficient security schemes for massive devices in 6G wireless networks. Finally, the book discusses critical security and privacy issues affecting the wireless ecosystem and provides practical AI-based solutions.Security and Privacy Schemes for Dense 6G Wireless Communication Networks is an essential reference for industry and academic researchers; scientists, engineers, lecturers and advanced students in the fields of cybersecurity wireless communication and networking, network security, computing, data science, AI/ML/DL, and sensing, as well as cybersecurity professionals and 6G standardization experts.

In the context of information security, social engineering is the manipulation of people into performing actions or divulging information for the purpose of gathering, defrauding, or gaining unauthorized system access. While some of the most common forms of social engineering involve telephone or social networks where criminals pose as employees of targeted organizations, phishing accounts for 96% of all successful cyber-attacks. Governments and private organizations have responded through various means such as training employees, executing internal vulnerability assessments, and ad campaigns. Despite all these efforts, phishing continues to provide the primary cyber-attack vector for nefarious entities.Phishing attacks continue to escalate, with over 300,000 reported incidents in the US alone last year. This book provides an in-depth look at the anatomy of modern phishing threats and how they are evolving with AI technologies. Readers will learn about the latest social engineering tactics used by cybercriminals, including deepfakes for audio/video manipulation and AI-generated spear-phishing campaigns, and discover emerging defensive tools that leverage machine learning to detect anomalies and protect against hyper-personalized phishing attempts. With phishing losses averaging millions per breach, this book equips readers with the knowledge to identify risks and implement robust countermeasures as these attacks become increasingly sophisticated and difficult to spot.Written by two experts in the field, bringing together their wide experience in academic research, security engineering, incident response and cyber forensics, this book offers valuable insights for researchers, engineers, cybersecurity professionals and organizational leaders working in cyber security, information technology, network and infrastructure security, endpoint protection, data governance, risk and compliance, digital forensics, incident response, operational technology and industrial control systems.

A consensus mechanism is the core component of a blockchain network, which ensures that every participant agrees on the state of the network in trustless environments. Until now, current blockchain networks have been using the proof-of-work (PoW) consensus mechanism, which has serious limitations such as huge energy consumption, low transaction processing capabilities, and centralization and scalability issues. To overcome these problems, a new consensus mechanism entitled proof-of-stake (PoS) has been developed. PoS has many advantages, including negligible energy consumption and very low consensus delay. Ethereum (the largest decentralized global software platform to create secured digital technology powered by blockchain technology and the blockchain of choice globally for all developers and enterprises) has just switched from PoW to PoS. As a result, this mechanism is expected to become a cutting-edge technology for future blockchain networks.This book provides a comprehensive discussion of the PoS consensus mechanism for blockchain networks. Starting with an overview of blockchain technology and consensus mechanisms, including basic concepts and network architecture, the book provides a review of the PoS consensus mechanism, including PoS consensus security and PoS performance and scalability issues.Proof-of-Stake for Blockchain Networks: Fundamentals, challenges and approaches is a valuable resource for researchers, engineers, and postgraduate students who are interested in advanced PoS consensus mechanisms, as well as developers and entrepreneurs who are interested in developing applications using the PoS consensus mechanism.

New approaches in federated learning and split learning have the potential to significantly improve ubiquitous intelligence in internet of things (IoT) applications. In split federated learning, the machine learning model is divided into smaller network segments, with each segment trained independently on a server using distributed local client data.The split learning method mitigates two fundamental drawbacks of federated learning: affordability, and privacy and security. When running machine learning computation on devices with limited resources, assigning only a portion of the network to train at the client-side minimizes the processing burden, compared to running a complete network as in federated learning. In addition, neither client nor server has full access to the other, which is more secure.This book reviews cutting edge technologies and advanced research in split federated learning. Coverage includes approaches to realizing and evaluating the effectiveness and advantages of federated learning and split-fed learning, the role of this technology in advancing and securing IoTs, advanced research on emerging AI models for preserving the privacy of the data owned by the clients, and the analysis and development of AI mechanisms in IoT architectures and applications. The use of split federated learning in natural language processing, recommendation systems, healthcare systems, emotion detection, smart agriculture, smart transportation and smart cities is discussed.Split Federated Learning for Secure IoT Applications: Concepts, frameworks, applications and case studies offers useful insights to the latest developments in the field for researchers, engineers and scientists in academia and industry, who are working in computing, AI, data science and cybersecurity with a focus on federated learning, machine learning and deep learning.

As biometrics-based identification and identity authentication become increasingly widespread in their deployment, it becomes correspondingly important to consider more carefully issues relating to reliability, usability and inclusion. One factor which is particularly important in this context is that of the relationship between the nature of the measurements extracted from a particular biometric modality and the age of the sample donor, and the effect which age has on physiological and behavioural characteristics invoked in a biometric transaction.In Age Factors in Biometric Processing an international panel of experts explore the implications of ageing on biometric technologies, and how such factors can be managed in practical situations. Topics include understanding the impact of ageing on biometric measurements; age factors as barriers/opportunities in relation to performance; modality-related approaches to management of age factors; implications for practical application; and future trends and research challenges.Age Factors in Biometric Processing provides an outstanding overview of this topic for the rapidly expanding community of stakeholders in biometrics based identification solutions in academia, industry and government.