Supply chains are experiencing a seismic shift towards customer-centricity and sustainability and the challenges that are bound to arise will require innovative solutions. The escalating complexities of logistics, exacerbated by the profound impacts of the pandemic, underscore the urgency for a paradigm shift. Every industry is grappling with unprecedented disruptions from shortages in essential components to workforce deficits. Navigating Cyber Threats and Cybersecurity in the Logistics Industry serves as a beacon of insight and solutions in this transformative landscape. This groundbreaking book, a result of an in-depth study evaluating 901 startups and scale-ups globally, delves into the Top Logistics Industry Trends & Startups. It unveils the pivotal role of the Insights Discovery Platform, powered by Big Data and Artificial Intelligence, covering over 2 million startups and scale-ups worldwide. This platform offers an immediate and comprehensive assessment of innovations, facilitating the early identification of startups and scale-ups that hold the key to revolutionizing logistics.

Web engineering faces a pressing challenge in keeping pace with the rapidly evolving digital landscape. Developing, designing, testing, and maintaining web-based systems and applications require innovative approaches to meet the growing demands of users and businesses. Generative Artificial Intelligence (AI) emerges as a transformative solution, offering advanced capabilities to enhance web engineering models and methodologies. This book presents a timely exploration of how Generative AI can revolutionize the web engineering discipline, providing insights into future challenges and societal impacts. Generative AI for Web Engineering Models offers a comprehensive examination of integrating AI-driven generative approaches into web engineering practices. It delves into methodologies, models, and the transformative impact of Generative AI on web-based systems and applications. By addressing topics such as web browser technologies, website scalability, security, and the integration of Machine Learning, this book provides a roadmap for researchers, scientists, postgraduate students, and AI enthusiasts interested in the intersection of AI and web engineering.

In the past several years, artificial intelligence (AI) has upended and transformed the private and public sectors. AI techniques have shown significant promise in securing sensitive data and ensuring compliance with regulatory standards. In medical practices, AI can enhance patient confidentiality through advanced encryption methods. Similarly, in business environments, AI-driven security protocols can protect against cyber threats and unauthorized access, safeguarding both intellectual property and customer information. By leveraging AI for these purposes, organizations can not only enhance their operational efficiency but also build trust and credibility with their stakeholders. AI Techniques for Securing Medical and Business Practices provides real-world case studies and cutting-edge research to demonstrate how AI is enhancing threat detection and risk management in cybersecurity. Beyond cybersecurity, this book explores the broader applications of AI in fields such as healthcare, finance, and creative industries. It examines innovations in medical imaging, financial modeling, and content creation, while addressing critical ethical issues like data privacy and algorithmic bias. Aimed at researchers, postgraduate scholars, industry professionals, and the general public, it provides a thorough understanding of AI's transformative potential and its implications for various sectors.

Cybersecurity Issues and Challenges in the Drone Industry is a comprehensive exploration of the critical cybersecurity problems faced by the rapidly expanding drone industry. With the widespread adoption of drones in military, commercial, and recreational sectors, the need to address cybersecurity concerns has become increasingly urgent. In this book, cybersecurity specialists collaborate to present a multifaceted approach to tackling the unique challenges posed by drones. They delve into essential topics such as establishing robust encryption and authentication systems, conducting regular vulnerability assessments, enhancing software security, advocating industry-wide standards and best practices, and educating drone users about the inherent cybersecurity risks. As drones, or unmanned aerial vehicles (UAVs), gain popularity and are deployed for various applications, ranging from aerial photography and surveillance to delivery services and infrastructure inspections, this book emphasizes the criticality of safeguarding the security, integrity, and privacy of drone systems and the data they handle. It highlights the growing vulnerability of drones to cybersecurity threats as these devices become increasingly connected and integrated into our everyday lives. This book is an invaluable resource for drone manufacturers, government agencies, regulators, cybersecurity professionals, and academia and research institutions invested in understanding and mitigating the cybersecurity risks in the drone industry.

In the dynamic environment of healthcare, the fusion of Computational Intelligence and Healthcare Industry 4.0 has enabled remarkable advancements in disease detection and analysis. However, a critical challenge persists – the limitations of current computational intelligence approaches in dealing with small sample sizes. This setback hampers the performance of these innovative models, hindering their potential impact on medical applications. As we stand at the crossroads of technological innovation and healthcare evolution, the need for a solution becomes paramount. Advances in Computational Intelligence for the Healthcare Industry 4.0 is a comprehensive guide addressing the very heart of this challenge. Designed for academics, researchers, healthcare professionals, and stakeholders in Healthcare Industry 4.0, this book serves as a source of innovation. It not only illuminates the complexities of computational intelligence in healthcare but also provides a roadmap for overcoming the limitations posed by small sample sizes. From fundamental principles to innovative concepts, this book offers a holistic perspective, shaping the future of healthcare through the lens of computational intelligence and Healthcare Industry 4.0.

Global supply chains are becoming more customer-centric and sustainable thanks to next-generation logistics management technologies. Automating logistics procedures greatly increases the productivity and efficiency of the workflow. There is a need, however, to create flexible and dynamic relationships among numerous stakeholders and the transparency and traceability of the supply chain. The digitalization of the supply chain process has improved these relationships and transparency; however, it has also created opportunities for cybercriminals to attack the logistics industry. Cybersecurity Measures for Logistics Industry Framework discusses the environment of the logistics industry in the context of new technologies and cybersecurity measures. Covering topics such as AI applications, inventory management, and sustainable computing, this premier reference source is an excellent resource for business leaders, IT managers, security experts, students and educators of higher education, librarians, researchers, and academicians.

The constantly changing digital environment of today makes cybersecurity an ever-increasing concern. With every technological advancement, cyber threats become more sophisticated and easily exploit system vulnerabilities. This unending attack barrage exposes organizations to data breaches, financial losses, and reputational harm. The traditional defense mechanisms, once dependable, now require additional support to keep up with the dynamic nature of modern attacks. Reshaping CyberSecurity With Generative AI Techniques offers a transformative solution to the pressing cybersecurity dilemma by harnessing the power of cutting-edge generative AI technologies. Bridging the gap between artificial intelligence and cybersecurity presents a paradigm shift in defense strategies, empowering organizations to safeguard their digital assets proactively. Through a comprehensive exploration of generative AI techniques, readers gain invaluable insights into how these technologies can be leveraged to mitigate cyber threats, enhance defense capabilities, and reshape the cybersecurity paradigm.

As cybersecurity threats continue to grow in scale and complexity, it is crucial to explore new and innovative solutions to combat them. The application of computer vision (CV) techniques in cybersecurity offers a promising solution to protect sensitive data and systems from malicious attacks. By leveraging CV algorithms, cybersecurity professionals and researchers can design more efficient and effective cybersecurity solutions, making them better equipped to handle the growing number of cyber threats. Global Perspectives on the Applications of Computer Vision in Cybersecurity is a comprehensive guide that offers practical insights into the principles and techniques of computer vision for cybersecurity. The book highlights the real-world applications of CV in various domains, including computer system security, web security, network security, IoT security, and digital forensics. It also emphasizes the importance of responsible CV for cybersecurity, ensuring that CV models adhere to ethical principles and are transparent and interpretable. By reading this book, cybersecurity professionals and researchers can gain a better understanding of how to use CV techniques to design solid cybersecurity solutions and address the challenges involved. With the guidance of the editors, Franklin Tchakounte and Marcellin Atemkeng, who are experts in both cybersecurity and computer vision, readers can leverage the power of CV to secure the future of our digital world. Join the movement today to revolutionize the field of cybersecurity and protect against the growing threat of cyber-attacks.

In the relentless battle against escalating cyber threats, data security faces a critical challenge – the need for innovative solutions to fortify encryption and decryption processes. The increasing frequency and complexity of cyber-attacks demand a dynamic approach, and this is where the intersection of cryptography and machine learning emerges as a powerful ally. As hackers become more adept at exploiting vulnerabilities, the book stands as a beacon of insight, addressing the urgent need to leverage machine learning techniques in cryptography. Machine Learning and Cryptographic Solutions for Data Protection and Network Security unveil the intricate relationship between data security and machine learning and provide a roadmap for implementing these cutting-edge techniques in the field. The book equips specialists, academics, and students in cryptography, machine learning, and network security with the tools to enhance encryption and decryption procedures by offering theoretical frameworks and the latest empirical research findings. Its pages unfold a narrative of collaboration and cross-pollination of ideas, showcasing how machine learning can be harnessed to sift through vast datasets, identify network weak points, and predict future cyber threats.

As the demand for data security intensifies, the vulnerabilities become glaring, exposing sensitive information to potential threats. In this tumultuous landscape, Generative Adversarial Networks (GANs) emerge as a groundbreaking solution, transcending their initial role as image generators to become indispensable guardians of data security. Within the pages of Enhancing Security in Public Spaces Through Generative Adversarial Networks (GANs), readers are guided through the intricate world of GANs, unraveling their unique design and dynamic adversarial training. The book presents GANs not merely as a technical marvel but as a strategic asset for organizations, offering a comprehensive solution to fortify cybersecurity, protect data privacy, and mitigate the risks associated with evolving cyber threats. It navigates the ethical considerations surrounding GANs, emphasizing the delicate balance between technological advancement and responsible use.