Deep Learning Approaches For Security Threats In Iot Environments

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Deep Learning Approaches for Security Threats in IoT Environments

Author : Mohamed Abdel-Basset
Publisher : John Wiley & Sons
ISBN 13 : 1119884160
Total Pages : 388 pages
Book Rating : 4.1/5 (198 download)

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Book Synopsis Deep Learning Approaches for Security Threats in IoT Environments by : Mohamed Abdel-Basset

Download or read book Deep Learning Approaches for Security Threats in IoT Environments written by Mohamed Abdel-Basset and published by John Wiley & Sons. This book was released on 2022-11-22 with total page 388 pages. Available in PDF, EPUB and Kindle. Book excerpt: Deep Learning Approaches for Security Threats in IoT Environments An expert discussion of the application of deep learning methods in the IoT security environment In Deep Learning Approaches for Security Threats in IoT Environments, a team of distinguished cybersecurity educators deliver an insightful and robust exploration of how to approach and measure the security of Internet-of-Things (IoT) systems and networks. In this book, readers will examine critical concepts in artificial intelligence (AI) and IoT, and apply effective strategies to help secure and protect IoT networks. The authors discuss supervised, semi-supervised, and unsupervised deep learning techniques, as well as reinforcement and federated learning methods for privacy preservation. This book applies deep learning approaches to IoT networks and solves the security problems that professionals frequently encounter when working in the field of IoT, as well as providing ways in which smart devices can solve cybersecurity issues. Readers will also get access to a companion website with PowerPoint presentations, links to supporting videos, and additional resources. They’ll also find: A thorough introduction to artificial intelligence and the Internet of Things, including key concepts like deep learning, security, and privacy Comprehensive discussions of the architectures, protocols, and standards that form the foundation of deep learning for securing modern IoT systems and networks In-depth examinations of the architectural design of cloud, fog, and edge computing networks Fulsome presentations of the security requirements, threats, and countermeasures relevant to IoT networks Perfect for professionals working in the AI, cybersecurity, and IoT industries, Deep Learning Approaches for Security Threats in IoT Environments will also earn a place in the libraries of undergraduate and graduate students studying deep learning, cybersecurity, privacy preservation, and the security of IoT networks.

Research Anthology on Artificial Intelligence Applications in Security

Author : Management Association, Information Resources
Publisher : IGI Global
ISBN 13 : 1799877485
Total Pages : 2253 pages
Book Rating : 4.7/5 (998 download)

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Book Synopsis Research Anthology on Artificial Intelligence Applications in Security by : Management Association, Information Resources

Download or read book Research Anthology on Artificial Intelligence Applications in Security written by Management Association, Information Resources and published by IGI Global. This book was released on 2020-11-27 with total page 2253 pages. Available in PDF, EPUB and Kindle. Book excerpt: As industries are rapidly being digitalized and information is being more heavily stored and transmitted online, the security of information has become a top priority in securing the use of online networks as a safe and effective platform. With the vast and diverse potential of artificial intelligence (AI) applications, it has become easier than ever to identify cyber vulnerabilities, potential threats, and the identification of solutions to these unique problems. The latest tools and technologies for AI applications have untapped potential that conventional systems and human security systems cannot meet, leading AI to be a frontrunner in the fight against malware, cyber-attacks, and various security issues. However, even with the tremendous progress AI has made within the sphere of security, it’s important to understand the impacts, implications, and critical issues and challenges of AI applications along with the many benefits and emerging trends in this essential field of security-based research. Research Anthology on Artificial Intelligence Applications in Security seeks to address the fundamental advancements and technologies being used in AI applications for the security of digital data and information. The included chapters cover a wide range of topics related to AI in security stemming from the development and design of these applications, the latest tools and technologies, as well as the utilization of AI and what challenges and impacts have been discovered along the way. This resource work is a critical exploration of the latest research on security and an overview of how AI has impacted the field and will continue to advance as an essential tool for security, safety, and privacy online. This book is ideally intended for cyber security analysts, computer engineers, IT specialists, practitioners, stakeholders, researchers, academicians, and students interested in AI applications in the realm of security research.

Security and Quality in Cyber-Physical Systems Engineering

Author : Stefan Biffl
Publisher : Springer Nature
ISBN 13 : 3030253120
Total Pages : 518 pages
Book Rating : 4.0/5 (32 download)

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Book Synopsis Security and Quality in Cyber-Physical Systems Engineering by : Stefan Biffl

Download or read book Security and Quality in Cyber-Physical Systems Engineering written by Stefan Biffl and published by Springer Nature. This book was released on 2019-11-09 with total page 518 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book examines the requirements, risks, and solutions to improve the security and quality of complex cyber-physical systems (C-CPS), such as production systems, power plants, and airplanes, in order to ascertain whether it is possible to protect engineering organizations against cyber threats and to ensure engineering project quality. The book consists of three parts that logically build upon each other. Part I "Product Engineering of Complex Cyber-Physical Systems" discusses the structure and behavior of engineering organizations producing complex cyber-physical systems, providing insights into processes and engineering activities, and highlighting the requirements and border conditions for secure and high-quality engineering. Part II "Engineering Quality Improvement" addresses quality improvements with a focus on engineering data generation, exchange, aggregation, and use within an engineering organization, and the need for proper data modeling and engineering-result validation. Lastly, Part III "Engineering Security Improvement" considers security aspects concerning C-CPS engineering, including engineering organizations’ security assessments and engineering data management, security concepts and technologies that may be leveraged to mitigate the manipulation of engineering data, as well as design and run-time aspects of secure complex cyber-physical systems. The book is intended for several target groups: it enables computer scientists to identify research issues related to the development of new methods, architectures, and technologies for improving quality and security in multi-disciplinary engineering, pushing forward the current state of the art. It also allows researchers involved in the engineering of C-CPS to gain a better understanding of the challenges and requirements of multi-disciplinary engineering that will guide them in their future research and development activities. Lastly, it offers practicing engineers and managers with engineering backgrounds insights into the benefits and limitations of applicable methods, architectures, and technologies for selected use cases.

Deep Learning Applications for Cyber Security

Author : Mamoun Alazab
Publisher : Springer
ISBN 13 : 3030130576
Total Pages : 260 pages
Book Rating : 4.0/5 (31 download)

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Book Synopsis Deep Learning Applications for Cyber Security by : Mamoun Alazab

Download or read book Deep Learning Applications for Cyber Security written by Mamoun Alazab and published by Springer. This book was released on 2019-08-14 with total page 260 pages. Available in PDF, EPUB and Kindle. Book excerpt: Cybercrime remains a growing challenge in terms of security and privacy practices. Working together, deep learning and cyber security experts have recently made significant advances in the fields of intrusion detection, malicious code analysis and forensic identification. This book addresses questions of how deep learning methods can be used to advance cyber security objectives, including detection, modeling, monitoring and analysis of as well as defense against various threats to sensitive data and security systems. Filling an important gap between deep learning and cyber security communities, it discusses topics covering a wide range of modern and practical deep learning techniques, frameworks and development tools to enable readers to engage with the cutting-edge research across various aspects of cyber security. The book focuses on mature and proven techniques, and provides ample examples to help readers grasp the key points.

Handbook of Research on Machine and Deep Learning Applications for Cyber Security

Author : Ganapathi, Padmavathi
Publisher : IGI Global
ISBN 13 : 1522596135
Total Pages : 506 pages
Book Rating : 4.5/5 (225 download)

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Book Synopsis Handbook of Research on Machine and Deep Learning Applications for Cyber Security by : Ganapathi, Padmavathi

Download or read book Handbook of Research on Machine and Deep Learning Applications for Cyber Security written by Ganapathi, Padmavathi and published by IGI Global. This book was released on 2019-07-26 with total page 506 pages. Available in PDF, EPUB and Kindle. Book excerpt: As the advancement of technology continues, cyber security continues to play a significant role in todays 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.

Artificial Intelligence and Security Challenges in Emerging Networks

Author : Abassi, Ryma
Publisher : IGI Global
ISBN 13 : 1522573542
Total Pages : 309 pages
Book Rating : 4.5/5 (225 download)

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Book Synopsis Artificial Intelligence and Security Challenges in Emerging Networks by : Abassi, Ryma

Download or read book Artificial Intelligence and Security Challenges in Emerging Networks written by Abassi, Ryma and published by IGI Global. This book was released on 2019-01-25 with total page 309 pages. Available in PDF, EPUB and Kindle. Book excerpt: The recent rise of emerging networking technologies such as social networks, content centric networks, Internet of Things networks, etc, have attracted significant attention from academia as well as industry professionals looking to utilize these technologies for efficiency purposes. However, the allure of such networks and resultant storage of high volumes of data leads to increased security risks, including threats to information privacy. Artificial Intelligence and Security Challenges in Emerging Networks is an essential reference source that discusses applications of artificial intelligence, machine learning, and data mining, as well as other tools and strategies to protect networks against security threats and solve security and privacy problems. Featuring research on topics such as encryption, neural networks, and system verification, this book is ideally designed for ITC procurement managers, IT consultants, systems and network integrators, infrastructure service providers, computer and software engineers, startup companies, academicians, researchers, managers, and students.

2021 IEEE International Conference on Distributed Computing, VLSI, Electrical Circuits and Robotics (DISCOVER).

Author :
Publisher :
ISBN 13 : 9781665412445
Total Pages : pages
Book Rating : 4.4/5 (124 download)

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Book Synopsis 2021 IEEE International Conference on Distributed Computing, VLSI, Electrical Circuits and Robotics (DISCOVER). by :

Download or read book 2021 IEEE International Conference on Distributed Computing, VLSI, Electrical Circuits and Robotics (DISCOVER). written by and published by . This book was released on 2021 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Machine Learning Approach for Cloud Data Analytics in IoT

Author : Sachi Nandan Mohanty
Publisher : John Wiley & Sons
ISBN 13 : 1119785855
Total Pages : 528 pages
Book Rating : 4.1/5 (197 download)

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Book Synopsis Machine Learning Approach for Cloud Data Analytics in IoT by : Sachi Nandan Mohanty

Download or read book Machine Learning Approach for Cloud Data Analytics in IoT written by Sachi Nandan Mohanty and published by John Wiley & Sons. This book was released on 2021-07-14 with total page 528 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Deep Learning Techniques for Automation and Industrial Applications

Author : Pramod Singh Rathore
Publisher : John Wiley & Sons
ISBN 13 : 1394234244
Total Pages : 293 pages
Book Rating : 4.3/5 (942 download)

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Book Synopsis Deep Learning Techniques for Automation and Industrial Applications by : Pramod Singh Rathore

Download or read book Deep Learning Techniques for Automation and Industrial Applications written by Pramod Singh Rathore and published by John Wiley & Sons. This book was released on 2024-07-23 with total page 293 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides state-of-the-art approaches to deep learning in areas of detection and prediction, as well as future framework development, building service systems and analytical aspects in which artificial neural networks, fuzzy logic, genetic algorithms, and hybrid mechanisms are used. Deep learning algorithms and techniques are found to be useful in various areas, such as automatic machine translation, automatic handwriting generation, visual recognition, fraud detection, and detecting developmental delays in children. “Deep Learning Techniques for Automation and Industrial Applications” presents a concise introduction to the recent advances in this field of artificial intelligence (AI). The broad-ranging discussion covers the algorithms and applications in AI, reasoning, machine learning, neural networks, reinforcement learning, and their applications in various domains like agriculture, manufacturing, and healthcare. Applying deep learning techniques or algorithms successfully in these areas requires a concerted effort, fostering integrative research between experts from diverse disciplines from data science to visualization. This book provides state-of-the-art approaches to deep learning covering detection and prediction, as well as future framework development, building service systems, and analytical aspects. For all these topics, various approaches to deep learning, such as artificial neural networks, fuzzy logic, genetic algorithms, and hybrid mechanisms, are explained. Audience The book will be useful to researchers and industry engineers working in information technology, data analytics network security, and manufacturing. Graduate and upper-level undergraduate students in advanced modeling and simulation courses will find this book very useful.

Deep Learning

Author : Li Deng
Publisher :
ISBN 13 : 9781601988140
Total Pages : 212 pages
Book Rating : 4.9/5 (881 download)

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Book Synopsis Deep Learning by : Li Deng

Download or read book Deep Learning written by Li Deng and published by . This book was released on 2014 with total page 212 pages. Available in PDF, EPUB and Kindle. Book excerpt: Provides an overview of general deep learning methodology and its applications to a variety of signal and information processing tasks

Enhancing Steganography Through Deep Learning Approaches

Author : Kumar, Vijay
Publisher : IGI Global
ISBN 13 :
Total Pages : 436 pages
Book Rating : 4.3/5 (693 download)

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Book Synopsis Enhancing Steganography Through Deep Learning Approaches by : Kumar, Vijay

Download or read book Enhancing Steganography Through Deep Learning Approaches written by Kumar, Vijay and published by IGI Global. This book was released on 2024-11-04 with total page 436 pages. Available in PDF, EPUB and Kindle. Book excerpt: In an era defined by digital connectivity, securing sensitive information against cyber threats is a pressing concern. As digital transmission systems advance, so do the methods of intrusion and data theft. Traditional security measures often need to catch up in safeguarding against sophisticated cyber-attacks. This book presents a timely solution by integrating steganography, the ancient art of concealing information, with cutting-edge deep learning techniques. By blending these two technologies, the book offers a comprehensive approach to fortifying the security of digital communication channels. Enhancing Steganography Through Deep Learning Approaches addresses critical issues in national information security, business and personal privacy, property security, counterterrorism, and internet security. It thoroughly explores steganography's application in bolstering security across various domains. Readers will gain insights into the fusion of deep learning and steganography for advanced encryption and data protection, along with innovative steganographic techniques for securing physical and intellectual property. The book also delves into real-world examples of thwarting malicious activities using deep learning-enhanced steganography. This book is tailored for academics and researchers in Artificial Intelligence, postgraduate students seeking in-depth knowledge in AI and deep learning, smart computing practitioners, data analysis professionals, and security sector professionals.

Artificial Intelligence in IoT

Author : Fadi Al-Turjman
Publisher : Springer
ISBN 13 : 3030041107
Total Pages : 235 pages
Book Rating : 4.0/5 (3 download)

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Book Synopsis Artificial Intelligence in IoT by : Fadi Al-Turjman

Download or read book Artificial Intelligence in IoT written by Fadi Al-Turjman and published by Springer. This book was released on 2019-02-12 with total page 235 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides an insight into IoT intelligence in terms of applications and algorithmic challenges. The book is dedicated to addressing the major challenges in realizing the artificial intelligence in IoT-based applications including challenges that vary from cost and energy efficiency to availability to service quality in multidisciplinary fashion. The aim of this book is hence to focus on both the algorithmic and practical parts of the artificial intelligence approaches in IoT applications that are enabled and supported by wireless sensor networks and cellular networks. Targeted readers are from varying disciplines who are interested in implementing the smart planet/environments vision via intelligent wireless/wired enabling technologies. Includes the most up-to-date research and applications related to IoT artificial intelligence (AI); Provides new and innovative operational ideas regarding the IoT artificial intelligence that help advance the telecommunications industry; Presents AI challenges facing the IoT scientists and provides potential ways to solve them in critical daily life issues.

Big Data Analytics for Internet of Things

Author : Tausifa Jan Saleem
Publisher : John Wiley & Sons
ISBN 13 : 1119740754
Total Pages : 402 pages
Book Rating : 4.1/5 (197 download)

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Book Synopsis Big Data Analytics for Internet of Things by : Tausifa Jan Saleem

Download or read book Big Data Analytics for Internet of Things written by Tausifa Jan Saleem and published by John Wiley & Sons. This book was released on 2021-04-20 with total page 402 pages. Available in PDF, EPUB and Kindle. Book excerpt: BIG DATA ANALYTICS FOR INTERNET OF THINGS Discover the latest developments in IoT Big Data with a new resource from established and emerging leaders in the field Big Data Analytics for Internet of Things delivers a comprehensive overview of all aspects of big data analytics in Internet of Things (IoT) systems. The book includes discussions of the enabling technologies of IoT data analytics, types of IoT data analytics, challenges in IoT data analytics, demand for IoT data analytics, computing platforms, analytical tools, privacy, and security. The distinguished editors have included resources that address key techniques in the analysis of IoT data. The book demonstrates how to select the appropriate techniques to unearth valuable insights from IoT data and offers novel designs for IoT systems. With an abiding focus on practical strategies with concrete applications for data analysts and IoT professionals, Big Data Analytics for Internet of Things also offers readers: A thorough introduction to the Internet of Things, including IoT architectures, enabling technologies, and applications An exploration of the intersection between the Internet of Things and Big Data, including IoT as a source of Big Data, the unique characteristics of IoT data, etc. A discussion of the IoT data analytics, including the data analytical requirements of IoT data and the types of IoT analytics, including predictive, descriptive, and prescriptive analytics A treatment of machine learning techniques for IoT data analytics Perfect for professionals, industry practitioners, and researchers engaged in big data analytics related to IoT systems, Big Data Analytics for Internet of Things will also earn a place in the libraries of IoT designers and manufacturers interested in facilitating the efficient implementation of data analytics strategies.

Deep Learning Techniques for IoT Security and Privacy

Author : Mohamed Abdel-Basset
Publisher : Springer Nature
ISBN 13 : 3030890252
Total Pages : 273 pages
Book Rating : 4.0/5 (38 download)

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Book Synopsis Deep Learning Techniques for IoT Security and Privacy by : Mohamed Abdel-Basset

Download or read book Deep Learning Techniques for IoT Security and Privacy written by Mohamed Abdel-Basset and published by Springer Nature. This book was released on 2021-12-05 with total page 273 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book states that the major aim audience are people who have some familiarity with Internet of things (IoT) but interested to get a comprehensive interpretation of the role of deep Learning in maintaining the security and privacy of IoT. A reader should be friendly with Python and the basics of machine learning and deep learning. Interpretation of statistics and probability theory will be a plus but is not certainly vital for identifying most of the book's material.

Malware Detection

Author : Mihai Christodorescu
Publisher : Springer Science & Business Media
ISBN 13 : 0387445994
Total Pages : 307 pages
Book Rating : 4.3/5 (874 download)

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Book Synopsis Malware Detection by : Mihai Christodorescu

Download or read book Malware Detection written by Mihai Christodorescu and published by Springer Science & Business Media. This book was released on 2007-03-06 with total page 307 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book captures the state of the art research in the area of malicious code detection, prevention and mitigation. It contains cutting-edge behavior-based techniques to analyze and detect obfuscated malware. The book analyzes current trends in malware activity online, including botnets and malicious code for profit, and it proposes effective models for detection and prevention of attacks using. Furthermore, the book introduces novel techniques for creating services that protect their own integrity and safety, plus the data they manage.

Machine Learning for Smart Environments/Cities

Author : Gonçalo Marques
Publisher : Springer Nature
ISBN 13 : 3030975169
Total Pages : 254 pages
Book Rating : 4.0/5 (39 download)

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Book Synopsis Machine Learning for Smart Environments/Cities by : Gonçalo Marques

Download or read book Machine Learning for Smart Environments/Cities written by Gonçalo Marques and published by Springer Nature. This book was released on 2022-04-05 with total page 254 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book introduces machine learning and its applications in smart environments/cities. At this stage, a comprehensive understanding of smart environment/city applications is critical for supporting future research. This book includes chapters written by researchers from different countries across the globe and identifies critical threads in research and also gaps that open up new and challenging lines of research for the future. Recent advances are discussed, and thorough reviews introduce readers to critical domains. The discussion on key research topics presented in this book accelerates smart city and smart environment implementations based on IoT technologies. Consequently, this book supports future research activities aimed at developing future IoT architectures for smart environments/cities.

Big Data Analytics for Cyber-Physical Systems

Author : Guido Dartmann
Publisher : Elsevier
ISBN 13 : 0128166460
Total Pages : 398 pages
Book Rating : 4.1/5 (281 download)

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Book Synopsis Big Data Analytics for Cyber-Physical Systems by : Guido Dartmann

Download or read book Big Data Analytics for Cyber-Physical Systems written by Guido Dartmann and published by Elsevier. This book was released on 2019-07-15 with total page 398 pages. Available in PDF, EPUB and Kindle. Book excerpt: Big Data Analytics in Cyber-Physical Systems: Machine Learning for the Internet of Things examines sensor signal processing, IoT gateways, optimization and decision-making, intelligent mobility, and implementation of machine learning algorithms in embedded systems. This book focuses on the interaction between IoT technology and the mathematical tools used to evaluate the extracted data of those systems. Each chapter provides the reader with a broad list of data analytics and machine learning methods for multiple IoT applications. Additionally, this volume addresses the educational transfer needed to incorporate these technologies into our society by examining new platforms for IoT in schools, new courses and concepts for universities and adult education on IoT and data science. - Bridges the gap between IoT, CPS, and mathematical modelling - Features numerous use cases that discuss how concepts are applied in different domains and applications - Provides "best practices", "winning stories" and "real-world examples" to complement innovation - Includes highlights of mathematical foundations of signal processing and machine learning in CPS and IoT