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Trust, Security and Privacy for Big Data
Data has revolutionized the digital ecosystem. Readily available large datasets foster AI and machine learning automated solutions. The data generated from diverse and varied sources including IoT, social platforms, healthcare, system logs, bio-informatics, etc. contribute to and define the ethos of Big Data which is volume, velocity and variety. Data lakes formed by the amalgamation of data from these sources requires powerful, scalable and resilient storage and processing platforms to reveal the true value hidden inside this data mine. Data formats and its collection from various sources not only introduce unprecedented challenges to different domains including IoT, manufacturing, smart ca...
Malware Analysis Using Artificial Intelligence and Deep Learning
This book is focused on the use of deep learning (DL) and artificial intelligence (AI) as tools to advance the fields of malware detection and analysis. The individual chapters of the book deal with a wide variety of state-of-the-art AI and DL techniques, which are applied to a number of challenging malware-related problems. DL and AI based approaches to malware detection and analysis are largely data driven and hence minimal expert domain knowledge of malware is needed. This book fills a gap between the emerging fields of DL/AI and malware analysis. It covers a broad range of modern and practical DL and AI techniques, including frameworks and development tools enabling the audience to innovate with cutting-edge research advancements in a multitude of malware (and closely related) use cases.
Introduction to Cybersecurity in the Internet of Things
This book addresses the security challenges facing the rapidly growing Internet of Things (IoT) industry, including the potential threats and risks arising from its complex architecture. The authors discuss the overall IoT architecture, covering networking, computing, and security threats and risks to hardware such as sensors, actuators, and portable devices, as well as infrastructure layers. They cover a range of technical concepts such as cryptography, distributed storage, and data transmission, and offer practical advice on implementing security solutions such as authentication and access control. By exploring the future of cybersecurity in the IoT industry, with insights into the importance of big data and the threats posed by data mining techniques, this book is an essential resource for anyone interested in, or working in, the rapidly evolving field of IoT security.
Deep Learning for Security and Privacy Preservation in IoT
This book addresses the issues with privacy and security in Internet of things (IoT) networks which are susceptible to cyber-attacks and proposes deep learning-based approaches using artificial neural networks models to achieve a safer and more secured IoT environment. Due to the inadequacy of existing solutions to cover the entire IoT network security spectrum, the book utilizes artificial neural network models, which are used to classify, recognize, and model complex data including images, voice, and text, to enhance the level of security and privacy of IoT. This is applied to several IoT applications which include wireless sensor networks (WSN), meter reading transmission in smart grid, vehicular ad hoc networks (VANET), industrial IoT and connected networks. The book serves as a reference for researchers, academics, and network engineers who want to develop enhanced security and privacy features in the design of IoT systems.
The Future of Artificial Intelligence and Robotics
Zusammenfassung: This book includes the results from the 5th International Conference on Deep Learning, Artificial Intelligence and Robotics (ICDLAIR), held in National Institute of Technology, Kurukshetra, on December 07-09, 2023, which brought together visionaries, researchers, and industry leaders at the forefront of technological innovation. In the rapidly evolving landscape of technology, deep learning, artificial intelligence, and robotics stand as a beacon of innovation and intellectual exchange. Among the myriad of groundbreaking contributions, a notable gem emerges--a forthcoming book that promises to encapsulate the essence of the 5th International Conference on Deep Learning, Arti...
Computational Intelligence Aided Systems for Healthcare Domain
This book covers recent advances in artificial intelligence, smart computing, and their applications in augmenting medical and health care systems. It will serve as an ideal reference text for graduate students and academic researchers in diverse engineering fields including electrical, electronics and communication, computer, and biomedical. This book: Presents architecture, characteristics, and applications of artificial intelligence and smart computing in health care systems Highlights privacy issues faced in health care and health informatics using artificial intelligence and smart computing technologies Discusses nature-inspired computing algorithms for the brain-computer interface Cove...
Cyber Security for Next-Generation Computing Technologies
This book sheds light on the cyber security challenges associated with nextgeneration computing technologies, emphasizing the serious threats posed to individuals, businesses, and nations. With everything becoming increasingly interconnected via the Internet, data security becomes paramount. As technology advances, people need to secure their data communication processes. Personal data security, including data integrity and confidentiality, is particularly vulnerable. Therefore, the concept of cyber security forensics emerges to ensure data security for everyone, addressing issues such as data control, hijacking, and threats to personal devices such as mobile phones, laptops, and other smart...
Cyber Security Cryptography and Machine Learning
This book constitutes the refereed proceedings of the 5th International Symposium on Cyber Security Cryptography and Machine Learning, CSCML 2021, held in Be'er Sheva, Israel, in July 2021. The 22 full and 13 short papers presented together with a keynote paper in this volume were carefully reviewed and selected from 48 submissions. They deal with the theory, design, analysis, implementation, or application of cyber security, cryptography and machine learning systems and networks, and conceptually innovative topics in these research areas.
Data and Applications Security and Privacy XXXI
This book constitutes the refereed proceedings of the 31st Annual IFIP WG 11.3 International Working Conference on Data and Applications Security and Privacy, DBSec 2017, held in Philadelphia, PA, USA, in July 2017. The 21 full papers and 9 short papers presented were carefully reviewed and selected from 59 submissions. The papers are organized in topical sections on access control, privacy, cloud security, secure storage in the cloud, secure systems, and security in networks and Web.
Data and Applications Security and Privacy XXXVI
This book constitutes the refereed proceedings of the 36th Annual IFIP WG 11.3 Conference on Data and Applications Security and Privacy, DBSec 2022, held in Newark, NJ, USA, in July 2022. The 12 full papers and 6 short papers presented were carefully reviewed and selected from 33 submissions. The conference covers research in data and applications security and privacy.
