Modern Approaches In Iot And Machine Learning For Cyber Security
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Modern Approaches In Iot And Machine Learning For Cyber Security
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Author : Vinit Kumar Gunjan
language : en
Publisher: Springer Nature
Release Date : 2023-12-07
Modern Approaches In Iot And Machine Learning For Cyber Security written by Vinit Kumar Gunjan and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-12-07 with Technology & Engineering categories.
This book examines the cyber risks associated with Internet of Things (IoT) and highlights the cyber security capabilities that IoT platforms must have in order to address those cyber risks effectively. The chapters fuse together deep cyber security expertise with artificial intelligence (AI), machine learning, and advanced analytics tools, which allows readers to evaluate, emulate, outpace, and eliminate threats in real time. The book’s chapters are written by experts of IoT and machine learning to help examine the computer-based crimes of the next decade. They highlight on automated processes for analyzing cyber frauds in the current systems and predict what is on the horizon. This book is applicable for researchers and professionals in cyber security, AI, and IoT.
Machine Learning Approach For Cloud Data Analytics In Iot
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Author : Sachi Nandan Mohanty
language : en
Publisher: John Wiley & Sons
Release Date : 2021-07-14
Machine Learning Approach For Cloud Data Analytics In Iot written by Sachi Nandan Mohanty and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-07-14 with Computers categories.
Machine Learning Approach for Cloud Data Analytics in IoT The book covers the multidimensional perspective of machine learning through the perspective of cloud computing and Internet of Things ranging from fundamentals to advanced applications Sustainable computing paradigms like cloud and fog are capable of handling issues related to performance, storage and processing, maintenance, security, efficiency, integration, cost, energy and latency in an expeditious manner. In order to expedite decision-making involved in the complex computation and processing of collected data, IoT devices are connected to the cloud or fog environment. Since machine learning as a service provides the best support in business intelligence, organizations have been making significant investments in this technology. Machine Learning Approach for Cloud Data Analytics in IoT elucidates some of the best practices and their respective outcomes in cloud and fog computing environments. It focuses on all the various research issues related to big data storage and analysis, large-scale data processing, knowledge discovery and knowledge management, computational intelligence, data security and privacy, data representation and visualization, and data analytics. The featured technologies presented in the book optimizes various industry processes using business intelligence in engineering and technology. Light is also shed on cloud-based embedded software development practices to integrate complex machines so as to increase productivity and reduce operational costs. The various practices of data science and analytics which are used in all sectors to understand big data and analyze massive data patterns are also detailed in the book.
Proceedings Of 5th International Conference On Recent Trends In Machine Learning Iot Smart Cities And Applications
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Author : Vinit Kumar Gunjan
language : en
Publisher: Springer Nature
Release Date : 2025-02-25
Proceedings Of 5th International Conference On Recent Trends In Machine Learning Iot Smart Cities And Applications written by Vinit Kumar Gunjan and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-02-25 with Technology & Engineering categories.
This book contains original, peer-reviewed research articles from the 5th International Conference on Recent Trends in Machine Learning, IoT, Smart Cities, and Applications, held in Hyderabad, India on 28–29 March 2024. It includes the most recent research trends and advancements in machine learning, smart cities, IoT, AI, cyber-physical systems, cybernetics, data science, neural networks, and cognition. This book addresses the comprehensive nature of AI, ML, and DL to highlight its role in the modelling, identification, optimisation, prediction, forecasting, and control of future intelligent systems.
Modern Approaches In Machine Learning And Cognitive Science A Walkthrough
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Author : Vinit Kumar Gunjan
language : en
Publisher: Springer Nature
Release Date : 2024-01-13
Modern Approaches In Machine Learning And Cognitive Science A Walkthrough written by Vinit Kumar Gunjan and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-01-13 with Computers categories.
This book provides a systematic and comprehensive overview of cognitive intelligence and AI-enabled IoT ecosystem and machine learning, capable of recognizing the object pattern in complex and large data sets. A remarkable success has been experienced in the last decade by emulating the brain–computer interface. It presents the applied cognitive science methods and AI-enabled technologies that have played a vital role at the core of practical solutions for a wide scope of tasks between handheld apps and industrial process control, autonomous vehicles, IoT, intelligent learning environment, game theory, human computer interaction, environmental policies, life sciences, playing computer games, computational theory, and engineering development. The book contains contents highlighting artificial neural networks that are analogous to the networks of neurons that comprise the brain and have given computers the ability to distinguish an image of a cat from one of a coconut, to spot pedestrians with enough accuracy to direct a self-driving car, and to recognize and respond to the spoken word. The chapters in this book focus on audiences interested in artificial intelligence, machine learning, fuzzy, cognitive and neurofuzzy-inspired computational systems, their theories, mechanisms, and architecture, which underline human and animal behavior, and their application to conscious and intelligent systems. In the current version, it focuses on the successful implementation and step-by-step execution and explanation of practical applications of the domain. It also offers a wide range of inspiring and interesting cutting-edge contributions on applications of machine learning, artificial intelligence, and cognitive science such as healthcare products, AI-enabled IoT, gaming, medical, and engineering. Overall, this book provides valuable information on effective, cutting-edge techniques, and approaches for students, researchers, practitioners, and academics in the field of machine learning and cognitive science. Furthermore, the purpose of this book is to address the interests of a broad spectrum of practitioners, students, and researchers, who are interested in applying machine learning and cognitive science methods in their respective domains.
Security Risk Management For The Internet Of Things
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Author : John Soldatos
language : en
Publisher:
Release Date : 2020-06-15
Security Risk Management For The Internet Of Things written by John Soldatos and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-06-15 with categories.
In recent years, the rising complexity of Internet of Things (IoT) systems has increased their potential vulnerabilities and introduced new cybersecurity challenges. In this context, state of the art methods and technologies for security risk assessment have prominent limitations when it comes to large scale, cyber-physical and interconnected IoT systems. Risk assessments for modern IoT systems must be frequent, dynamic and driven by knowledge about both cyber and physical assets. Furthermore, they should be more proactive, more automated, and able to leverage information shared across IoT value chains. This book introduces a set of novel risk assessment techniques and their role in the IoT Security risk management process. Specifically, it presents architectures and platforms for end-to-end security, including their implementation based on the edge/fog computing paradigm. It also highlights machine learning techniques that boost the automation and proactiveness of IoT security risk assessments. Furthermore, blockchain solutions for open and transparent sharing of IoT security information across the supply chain are introduced. Frameworks for privacy awareness, along with technical measures that enable privacy risk assessment and boost GDPR compliance are also presented. Likewise, the book illustrates novel solutions for security certification of IoT systems, along with techniques for IoT security interoperability. In the coming years, IoT security will be a challenging, yet very exciting journey for IoT stakeholders, including security experts, consultants, security research organizations and IoT solution providers. The book provides knowledge and insights about where we stand on this journey. It also attempts to develop a vision for the future and to help readers start their IoT Security efforts on the right foot.
Handbook Of Research On Machine And Deep Learning Applications For Cyber Security
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Author : Ganapathi, Padmavathi
language : en
Publisher: IGI Global
Release Date : 2019-07-26
Handbook Of Research On Machine And Deep Learning Applications For Cyber Security written by Ganapathi, Padmavathi and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-07-26 with Computers categories.
As the advancement of technology continues, cyber security continues to play a significant role in today’s world. With society becoming more dependent on the internet, new opportunities for virtual attacks can lead to the exposure of critical information. Machine and deep learning techniques to prevent this exposure of information are being applied to address mounting concerns in computer security. The Handbook of Research on Machine and Deep Learning Applications for Cyber Security is a pivotal reference source that provides vital research on the application of machine learning techniques for network security research. While highlighting topics such as web security, malware detection, and secure information sharing, this publication explores recent research findings in the area of electronic security as well as challenges and countermeasures in cyber security research. It is ideally designed for software engineers, IT specialists, cybersecurity analysts, industrial experts, academicians, researchers, and post-graduate students.
Machine Intelligence And Big Data Analytics For Cybersecurity Applications
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Author : Yassine Maleh
language : en
Publisher: Springer Nature
Release Date : 2020-12-14
Machine Intelligence And Big Data Analytics For Cybersecurity Applications written by Yassine Maleh and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-12-14 with Computers categories.
This book presents the latest advances in machine intelligence and big data analytics to improve early warning of cyber-attacks, for cybersecurity intrusion detection and monitoring, and malware analysis. Cyber-attacks have posed real and wide-ranging threats for the information society. Detecting cyber-attacks becomes a challenge, not only because of the sophistication of attacks but also because of the large scale and complex nature of today’s IT infrastructures. It discusses novel trends and achievements in machine intelligence and their role in the development of secure systems and identifies open and future research issues related to the application of machine intelligence in the cybersecurity field. Bridging an important gap between machine intelligence, big data, and cybersecurity communities, 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 on machine intelligence and big data analytics for cybersecurity applications.
Machine Learning Approaches In Cyber Security Analytics
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Author : Tony Thomas
language : en
Publisher: Springer Nature
Release Date : 2019-12-16
Machine Learning Approaches In Cyber Security Analytics written by Tony Thomas and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-12-16 with Computers categories.
This book introduces various machine learning methods for cyber security analytics. With an overwhelming amount of data being generated and transferred over various networks, monitoring everything that is exchanged and identifying potential cyber threats and attacks poses a serious challenge for cyber experts. Further, as cyber attacks become more frequent and sophisticated, there is a requirement for machines to predict, detect, and identify them more rapidly. Machine learning offers various tools and techniques to automate and quickly predict, detect, and identify cyber attacks.
Critical Phishing Defense Strategies And Digital Asset Protection
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Author : Gupta, Brij B.
language : en
Publisher: IGI Global
Release Date : 2025-02-14
Critical Phishing Defense Strategies And Digital Asset Protection written by Gupta, Brij B. and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-02-14 with Computers categories.
As phishing attacks become more sophisticated, organizations must use a multi-layered approach to detect and prevent these threats, combining advanced technologies like AI-powered threat detection, user training, and authentication systems. Protecting digital assets requires strong encryption, secure access controls, and continuous monitoring to minimize vulnerabilities. With the growing reliance on digital platforms, strengthening defenses against phishing and ensuring the security of digital assets are integral to preventing financial loss, reputational damage, and unauthorized access. Further research into effective strategies may help prevent cybercrime while building trust and resilience in an organization's digital infrastructure. Critical Phishing Defense Strategies and Digital Asset Protection explores the intricacies of phishing attacks, including common tactics and techniques used by attackers. It examines advanced detection and prevention methods, offering practical solutions and best practices for defending against these malicious activities. This book covers topics such as network security, smart devices, and threat detection, and is a useful resource for computer engineers, security professionals, data scientists, academicians, and researchers.
Leveraging Ai For Innovative Sustainable Energy Solar Wind And Green Hydrogen
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Author : Hammouch, Hind
language : en
Publisher: IGI Global
Release Date : 2025-05-15
Leveraging Ai For Innovative Sustainable Energy Solar Wind And Green Hydrogen written by Hammouch, Hind and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-05-15 with Technology & Engineering categories.
Artificial intelligence (AI) and intelligent technologies play a vital role in transforming the energy sector, which is key to delivering lower carbon footprints combined with increased levels of security. AI-driven innovations in solar, wind energy, green hydrogen generation increase efficiency to achieve further sustainability. Furthermore, the disruptive impact of AI-based solutions in the energy sector is informative for initiating more sustainable industrial and commercial purposes and practices worldwide. Thus, AI-enabled systems and their capabilities in generation, distribution of energy and consumption can contribute to helping build more robust and greener infrastructures for our resources. Leveraging AI for Innovative Sustainable Energy: Solar, Wind and Green Hydrogen offers practical steps for incorporating green hydrogen into established energy systems that can help to realize net-zero emissions targets. It inspires innovation by detailing the experiences of real-life case studies and presenting forward-looking viewpoints that make collaboration between various sectors possible, all towards embracing renewable energy solutions on a global scale. Covering topics such as hydrogen power, marketing strategies, and public education campaigns, this book is an excellent resource for environmental advocates, sustainability practitioners, policymakers, manufacturers, industry leaders, professionals, researchers, scholars, academicians, and more.