Student assessment in online learning is submitted remotely without any face-to-face interaction, and therefore, student authentication is widely seen as one of the major challenges in online examination. Authentication is the process of determining whether someone or something is, in fact, who or what it is declared to be. As the dependence upon computers and computer networks grows, especially within education, the need for authentication has increased. Biometric Authentication in Online Learning Environments provides innovative insights into biometrics as a strategy to mitigate risk and provide authentication, while introducing a framework that provides security to improve e-learning and on-line examination by utilizing biometric-based authentication techniques. This book examines e-learning, security, threats in online exams, security considerations, and biometric technologies, and is designed for IT professionals, higher education administrators, professors, researchers, business professionals, academicians, and libraries seeking topics centered on biometrics as an authentication strategy within educational environments.

This two-volume set LNAI 13355 and 13356 constitutes the refereed proceedings of the 23rd International Conference on Artificial Intelligence in Education, AIED 2022, held in Durham, UK, in July 2022. The 40 full papers and 40 short papers presented together with 2 keynotes, 6 industry papers, 12 DC papers, 6 Workshop papers, 10 Practitioner papers, 97 Posters and Late-Breaking Results were carefully reviewed and selected from 243 submissions. The conference presents topics such as intelligent systems and the cognitive sciences for the improvement and advancement of education, the science and engineering of intelligent interactive learning systems. The theme for the AIED 2022 conference was „AI in Education: Bridging the gap between academia, business, and non-pro t in preparing future-proof generations towards ubiquitous AI."

In the current educational environment, there has been a shift towards online learning as a replacement for the traditional in-person classroom experience. With this new environment comes new technologies, benefits, and challenges for providing courses to students through an entirely digital environment. With this shift comes the necessary research on how to utilize these online courses and how to develop effective online educational materials that fit student needs and encourage student learning, motivation, and success. The optimization of these online tools requires a deeper look into curriculum, instructional design, teaching techniques, and new models for student assessment and evaluation. Information on how to create valuable online course content, engaging lesson plans for the digital space, and meaningful student activities online are only a few of many current topics of interest for promoting student achievement through online learning. The Research Anthology on Developing Effective Online Learning Courses provides multiple perspectives on how to develop engaging and effective online learning courses in the wake of the rapid digitalization of education. This book includes topics focused on online learners, online course content, effective online instruction strategies, and instructional design for the online environment. This reference work is ideal for curriculum developers, instructional designers, IT consultants, deans, chairs, teachers, administrators, academicians, researchers, and students interested in the latest research on how to create online learning courses that promote student success.

With the increasing use of e-learning, technology has not only revolutionized the way businesses operate but has also impacted learning processes in the education sector. E-learning is slowly replacing traditional methods of teaching and security in e-learning is an important issue in this educational context. With this book, you will be familiarized with the theoretical frameworks, technical methodologies, information security, and empirical research findings in the field to protect your computers and information from threats. Secure Data Management for Online Learning Applications will keep you interested and involved throughout.

In order to be successful, online learning should be planned systematically. It can be said that offering distance education courses without preparation and knowledge about the theoretical background can cause drawbacks. While distance education has become widespread and popular, it is observed that there could be problems in its application. Such problems can include technical problems, inability to meet the learning needs at the learners’ own speeds, lack of communication among learners and between learners and teachers, and lack of quality materials appropriate for online learning or the inclusion of materials used in traditional methods directly into online learning. For successful online courses, these critical aspects of distance education are important, and they should be taken into account by the institutions and the instructors offering online courses. The Handbook of Research on Managing and Designing Online Courses in Synchronous and Asynchronous Environments provides up-to-date knowledge and experiences regarding technologies, processes, and environments for online course design in distance education systems and covers topics related to the aspects of successful distance education systems with a focus on teaching and learning in online environments. Focusing on topics such as instructional design and integrated systems, it is an ideal guide for online course designers, instructional designers, curricula developers, administrators, educators, researchers, trainers, and students.

DEEP LEARNING APPROACHES TO CLOUD SECURITY Covering one of the most important subjects to our society today, cloud security, this editorial team delves into solutions taken from evolving deep learning approaches, solutions allowing computers to learn from experience and understand the world in terms of a hierarchy of concepts, with each concept defined through its relation to simpler concepts. Deep learning is the fastest growing field in computer science. Deep learning algorithms and techniques are found to be useful in different areas like automatic machine translation, automatic handwriting generation, visual recognition, fraud detection, and detecting developmental delay in children. However, applying deep learning techniques or algorithms successfully in these areas needs a concerted effort, fostering integrative research between experts ranging from diverse disciplines from data science to visualization. This book provides state of the art approaches of deep learning in these areas, including areas of detection and prediction, as well as future framework development, building service systems and analytical aspects. In all these topics, deep learning approaches, such as artificial neural networks, fuzzy logic, genetic algorithms, and hybrid mechanisms are used. This book is intended for dealing with modeling and performance prediction of the efficient cloud security systems, thereby bringing a newer dimension to this rapidly evolving field. This groundbreaking new volume presents these topics and trends of deep learning, bridging the research gap, and presenting solutions to the challenges facing the engineer or scientist every day in this area. Whether for the veteran engineer or the student, this is a must-have for any library. Deep Learning Approaches to Cloud Security: Is the first volume of its kind to go in-depth on the newest trends and innovations in cloud security through the use of deep learning approaches Covers these important new innovations, such as AI, data mining, and other evolving computing technologies in relation to cloud security Is a useful reference for the veteran computer scientist or engineer working in this area or an engineer new to the area, or a student in this area Discusses not just the practical applications of these technologies, but also the broader concepts and theory behind how these deep learning tools are vital not just to cloud security, but society as a whole Audience: Computer scientists, scientists and engineers working with information technology, design, network security, and manufacturing, researchers in computers, electronics, and electrical and network security, integrated domain, and data analytics, and students in these areas

Digital transformation, also known as Industry 4.0, Smart Industry, and Smart Manufacturing, is at the top of leaders’ agendas. Such a transformation stimulates innovation in new products and services, the digital transformation of processes, and the creation of new business models and ecosystems. In the world of manufacturing, Industry 4.0 is based on various technological advances, among which we can mainly cite CPS (cyber-physical systems), IoT (Internet of Things), and IoS (internet of services). While engaging, this fourth wave also brings significant challenges for manufacturers. Business operations and the supply chain are becoming more vulnerable to cyber threats. Security Engineering for Embedded and Cyber-Physical Systems is an invaluable resource to discover cybersecurity and privacy techniques for embedded and cyber-physical systems. This book presents the latest studies and research results on all aspects of security engineering for embedded and cyber-physical systems. It also provides a premier interdisciplinary reference for researchers, practitioners, and educators to discover the most recent innovations, trends, concerns, and practical challenges encountered and solutions adopted in security engineering for embedded and cyber-physical systems. The book offers comprehensive coverage of the essential topics, including the following: Embedded and cyber-physical systems threats and vulnerabilities Security engineering techniques for embedded and cyber-physical systems Security engineering for embedded and cyber-physical systems and potential future-use cases Artificial intelligence techniques for cybersecurity and privacy Security engineering for Internet of Things Blockchain for cybersecurity in embedded and cyber-physical systems This book comprises a number of state-of-the-art contributions from both scientists and practitioners working in security engineering for embedded and cyber-physical systems. It aspires to provide a relevant reference for students, researchers, engineers, and professionals working in this area or those interested in grasping its diverse facets and exploring the latest advances and future trends related to security engineering for embedded and cyber-physical systems.