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The Internet of Things (IoT) has brought about significant changes to various domains such as healthcare, transportation, and manufacturing. However, security remains a critical challenge in IoT due to the large number of connected devices with varying processing capabilities and memory constraints. Traditional cryptographic algorithms are not well-suited for IoT devices due to their high computational and memory requirements. Lightweight cryptography algorithms have emerged as a promising solution for securing IoT devices with limited resources. In this abstract, we provide an overview of lightweight cryptography algorithms for IoT, including their design principles, security properties, and performance evaluation.

Datafication has emerged as a key driver of the digital economy, enabling businesses, governments, and individuals to extract value from the growing flood of data. In this comprehensive survey, we explore the various dimensions of datafication, including the technologies, practices, and challenges involved in turning information into structured data for analysis and decision-making. We begin by providing an overview of the historical context and the rise of big data, and then delve into the latest developments in artificial intelligence and machine learning. We examine the key drivers of datafication across industries and sectors, and explore the ethical, legal, and social implications of the data revolution. Finally, we consider the challenges and opportunities presented by datafication, including issues of data privacy and security, the need for new skills and competencies, and the potential for data to drive innovation and social change. Overall, this survey provides a comprehensive and up-to-date overview of the datafication landscape, helping readers to better understand and navigate the rapidly-evolving world of data.

Software-Defined Networking (SDN) is a unique approach to network administration with the potential to radically alter how companies approach network design, implementation, and management. By decoupling the control plane from the data plane, SDN makes it possible for businesses to centralise and automate network design, management, and optimization. Hence, the organisation gains in speed, adaptability, and scalability. This research looks into where networking is headed and how businesses may use software-defined networking to speed up digital transformation, cut costs, and boost efficiencies. The concepts and components of software-defined networking (SDN), such as the controller, southbound and northbound application programming interfaces (APIs), and network virtualization, are introduced in this article. The advantages of SDN in terms of network programmability, security, and application performance are also explored. It also draws attention to some of the challenges of putting SDN into practise, such as integrating it with existing systems, being tied to a single vendor, and a lack of adequate industry standards. Finally, this research presents case studies of businesses that have successfully used SDN and seen significant benefits as a result of this implementation. It concludes that software-defined networking (SDN) is the networking technology of the future and that companies that adopt this technology will have an advantage in the modern digital economy.

As the need for machine learning models continues to grow, concerns about data privacy and security become increasingly important. Federated learning, a decentralized machine learning approach, has emerged as a promising solution that allows multiple parties to collaborate and build models without sharing sensitive data. In this comprehensive survey, we explore the principles, techniques, and applications of federated learning, with a focus on its privacy-preserving aspects