The fully accomplished standardization of the new mobile generation has led to the deployment of fifth-generation (5G) wireless networks to gratify enormous traffic volume for Internet services. The current centralized mobility system could not be sufficient to manage an explosive increase in data volume and is considered a steadily rising issue in modern wireless communication. A new technique that can affluently handle traffic problems and completely avoid network breakdown chances is indispensable. Recently, distributed mobility management (DMM) was introduced to overcome the inevitable obstacles that destructively impact the existing networks. Specifically, a novel design based on the deployment of distributed mobility anchors, closer to the terminal points, was introduced. Several works have been proposed to build DMM solutions with different focuses for 5G-and-beyond networks (B5G), which are also referred to as sixth-generation solutions (6G). In this paper, we present the potential and benefits of flat network design for efficient and fast routing of traffic and furnish the effectiveness of the scheme toward mobility management in B5G by delineating recent research works. We also present the current limitations, challenges, and future research directions for seamless mobility to achieve the desired objectives in the current 5G and upcoming 6G cellular communications.

An era marked by revolutionary advancements in miniaturization and artificial intelligence has ushered in the age of drone swarms. These formations characterized by coordinated fleets of miniature aerial vehicles (MAVs) offer undeniable potential for unparalleled efficiency in diverse applications. Therefore, the field of “swarm security” delves into how drone swarms have reshaped the security landscape. Compared to lone drones, infected drones within a swarm could potentially seize control of the entire group, posing the chilling risk of coordinated attacks on critical infrastructure or densely populated areas. To strengthen cybersecurity frameworks, this study investigates the intertwined complexities of legal frameworks and technological advancements. The authors explore modern defenses like signal jamming and AI-powered threat detection, while also raising ethical concerns about weapons and responsible use. Moreover, a future where the revolutionary potential of drone swarms is harnessed for the benefit of society has been explored through understanding and mitigating risks. Request access from your librarian to read this chapter's full text.

In most decision-based security applications Deep Learning (DL) algorithms have been widely using for improvement. For better performance, a large amount of dataset has been used for training the DL algorithms. As DL has been remained a key element in the performance of the application, hence, several privacy and security issues have reported, which have affected the performance. Such security attacks have also affected the performance by taking the advantage of the huge dataset, because it is easy for an attacker to add executable noise into the dataset to get the information of the dataset and the model used. Most common security attacks like poisoning and evasion attacks have been considered challenging attacks that have caused misclassification and wrong prediction. Hence, a secure metric is needed to mitigate the effects of such attacks from the dataset. Therefore, in this paper, a light-weight watermarking framework has been proposed that provides security to the dataset before training the DL algorithms. We have implemented our proposed framework using the most common Convolutional Neural Network (CNN) and Artificial Neural Network (ANN) against security attacks. The proposed framework has been evaluated based on accuracy, precision, and computational cost, and has maintained the accuracy up to 98.89% and a precision of 0.96, which has maintained the level as in recent literature. We have also reduced the computational cost for the proposed framework. We believed that the proposed framework can be used to mitigate the security issues in DL algorithms and enhanced toward other security applications.

The rapid integration of internet and technological advancements over the past two decades has reshaped the global landscape, leading to transformative changes in various sectors.The emergence of Industry 4.0, conceptualized in 2011, has particularly revolutionized manufacturing and logistics by advocating for systematic digitalization technology integration to enhance efficiency and reduce costs. However, this technological evolution, while fostering efficiency and process optimization, also introduces vulnerabilities to cyber threats. The logistics sector, heavily reliant on interconnected systems like internet of things, faces potential risks from cyberattacks that target sensitive data across the interconnected supply chain. This chapter aims to address the intricate relationship between digitalization and the logistics sector, emphasizing the crucial role of digital safeguards in navigating cyber dangers. Furthermore, the chapter delves into the significance of visibility in supply-chain operations and explores technologies and practices for enhancing supply-chain visibility.

The integration of Industry 4.0 and sustainability has paved the way for transformative practices in manufacturing, leading to the development of smart factories with a focus on greener futures. This chapter explores the synergy of Industry 4.0 technologies and sustainability. It emphasizes the collective potential of the two paradigms for the optimization of production processes, energy efficiency, and waste management. The integration of Industry 4.0 technologies including artificial intelligence, internet of things, big data analytics, robotics, and automation is playing a pivotal role in transforming the manufacturing processes and enabling the environmentally sustainable operations. The development of smart factories aligning with the sustainability goals has led to eco-efficiency and greener futures. In this chapter, responsible sourcing, circular economy, and energy management have been investigated along with the implementation opportunities and challenges. Request access from your librarian to read this chapter's full text.