Deep Learning For Security And Privacy Preservation In Iot
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Deep Learning For Security And Privacy Preservation In Iot
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Author : Aaisha Makkar
language : en
Publisher: Springer Nature
Release Date : 2022-04-03
Deep Learning For Security And Privacy Preservation In Iot written by Aaisha Makkar and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-04-03 with Computers categories.
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.
Federated Learning Systems
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Author : Muhammad Habib ur Rehman
language : en
Publisher: Springer Nature
Release Date : 2021-06-11
Federated Learning Systems written by Muhammad Habib ur Rehman and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-06-11 with Technology & Engineering categories.
This book covers the research area from multiple viewpoints including bibliometric analysis, reviews, empirical analysis, platforms, and future applications. The centralized training of deep learning and machine learning models not only incurs a high communication cost of data transfer into the cloud systems but also raises the privacy protection concerns of data providers. This book aims at targeting researchers and practitioners to delve deep into core issues in federated learning research to transform next-generation artificial intelligence applications. Federated learning enables the distribution of the learning models across the devices and systems which perform initial training and report the updated model attributes to the centralized cloud servers for secure and privacy-preserving attribute aggregation and global model development. Federated learning benefits in terms of privacy, communication efficiency, data security, and contributors’ control of their critical data.
Security And Privacy Preserving Techniques In Wireless Robotics
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Author : Amit Kumar Tyagi
language : en
Publisher: CRC Press
Release Date : 2022-08-17
Security And Privacy Preserving Techniques In Wireless Robotics written by Amit Kumar Tyagi and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-08-17 with Technology & Engineering categories.
The wide gap between the existing security solutions and the actual practical deployment in smart manufacturing, smart home, and remote environments (with respect to wireless robotics) is one of the major reasons why we require novel strategies, mechanisms, architectures, and frameworks. Furthermore, it is also important to access and understand the different level of vulnerabilities and attack vectors in Wireless Sensor Network (WSN) and Wireless Robotics. This book includes an in-depth explanation of a secure and dependable Wireless Robotics (WR) architecture, to ensure confidentiality, authenticity, and availability. Features Blockchain technology for securing data at end/server side Emerging technologies/networking, like Cloud, Edge, Fog, etc., for communicating and storing data (securely). Various open issues, challenges faced in this era towards wireless robotics, including several future research directions for the future. Several real world’s case studies are included Chapters on ethical concerns and privacy laws, i.e., laws for service providers Security and privacy challenges in wireless sensor networks and wireless robotics The book is especially useful for academic researchers, undergraduate students, postgraduate students, and industry researchers and professionals.
Research Anthology On Privatizing And Securing Data
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Author : Management Association, Information Resources
language : en
Publisher: IGI Global
Release Date : 2021-04-23
Research Anthology On Privatizing And Securing Data written by Management Association, Information Resources and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-04-23 with Computers categories.
With the immense amount of data that is now available online, security concerns have been an issue from the start, and have grown as new technologies are increasingly integrated in data collection, storage, and transmission. Online cyber threats, cyber terrorism, hacking, and other cybercrimes have begun to take advantage of this information that can be easily accessed if not properly handled. New privacy and security measures have been developed to address this cause for concern and have become an essential area of research within the past few years and into the foreseeable future. The ways in which data is secured and privatized should be discussed in terms of the technologies being used, the methods and models for security that have been developed, and the ways in which risks can be detected, analyzed, and mitigated. The Research Anthology on Privatizing and Securing Data reveals the latest tools and technologies for privatizing and securing data across different technologies and industries. It takes a deeper dive into both risk detection and mitigation, including an analysis of cybercrimes and cyber threats, along with a sharper focus on the technologies and methods being actively implemented and utilized to secure data online. Highlighted topics include information governance and privacy, cybersecurity, data protection, challenges in big data, security threats, and more. This book is essential for data analysts, cybersecurity professionals, data scientists, security analysts, IT specialists, practitioners, researchers, academicians, and students interested in the latest trends and technologies for privatizing and securing data.
Privacy Preserving Data Publishing
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Author : Bee-Chung Chen
language : en
Publisher: Now Publishers Inc
Release Date : 2009
Privacy Preserving Data Publishing written by Bee-Chung Chen and has been published by Now Publishers Inc this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009 with Business & Economics categories.
This book is dedicated to those who have something to hide. It is a book about "privacy preserving data publishing" -- the art of publishing sensitive personal data, collected from a group of individuals, in a form that does not violate their privacy. This problem has numerous and diverse areas of application, including releasing Census data, search logs, medical records, and interactions on a social network. The purpose of this book is to provide a detailed overview of the current state of the art as well as open challenges, focusing particular attention on four key themes: RIGOROUS PRIVACY POLICIES Repeated and highly-publicized attacks on published data have demonstrated that simplistic approaches to data publishing do not work. Significant recent advances have exposed the shortcomings of naive (and not-so-naive) techniques. They have also led to the development of mathematically rigorous definitions of privacy that publishing techniques must satisfy; METRICS FOR DATA UTILITY While it is necessary to enforce stringent privacy policies, it is equally important to ensure that the published version of the data is useful for its intended purpose. The authors provide an overview of diverse approaches to measuring data utility; ENFORCEMENT MECHANISMS This book describes in detail various key data publishing mechanisms that guarantee privacy and utility; EMERGING APPLICATIONS The problem of privacy-preserving data publishing arises in diverse application domains with unique privacy and utility requirements. The authors elaborate on the merits and limitations of existing solutions, based on which we expect to see many advances in years to come.
Machine Learning And Cryptographic Solutions For Data Protection And Network Security
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Author : Ruth, J. Anitha
language : en
Publisher: IGI Global
Release Date : 2024-05-31
Machine Learning And Cryptographic Solutions For Data Protection And Network Security written by Ruth, J. Anitha and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-05-31 with Computers categories.
In the relentless battle against escalating cyber threats, data security faces a critical challenge – the need for innovative solutions to fortify encryption and decryption processes. The increasing frequency and complexity of cyber-attacks demand a dynamic approach, and this is where the intersection of cryptography and machine learning emerges as a powerful ally. As hackers become more adept at exploiting vulnerabilities, the book stands as a beacon of insight, addressing the urgent need to leverage machine learning techniques in cryptography. Machine Learning and Cryptographic Solutions for Data Protection and Network Security unveil the intricate relationship between data security and machine learning and provide a roadmap for implementing these cutting-edge techniques in the field. The book equips specialists, academics, and students in cryptography, machine learning, and network security with the tools to enhance encryption and decryption procedures by offering theoretical frameworks and the latest empirical research findings. Its pages unfold a narrative of collaboration and cross-pollination of ideas, showcasing how machine learning can be harnessed to sift through vast datasets, identify network weak points, and predict future cyber threats.
Security And Privacy For Big Data Cloud Computing And Applications
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Author : Wei Ren
language : en
Publisher: Institution of Engineering and Technology
Release Date : 2019-08-14
Security And Privacy For Big Data Cloud Computing And Applications written by Wei Ren and has been published by Institution of Engineering and Technology this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-08-14 with Computers categories.
As big data becomes increasingly pervasive and cloud computing utilization becomes the norm, the security and privacy of our systems and data becomes more critical with emerging security and privacy threats and challenges. This book presents a comprehensive view on how to advance security and privacy in big data, cloud computing, and their applications. Topics include cryptographic tools, SDN security, big data security in IoT, privacy preserving in big data, security architecture based on cyber kill chain, privacy-aware digital forensics, trustworthy computing, privacy verification based on machine learning, and chaos-based communication systems. This book is an essential reading for networking, computing, and communications professionals, researchers, students and engineers, working with big data and cloud computing.
Deep Learning For Internet Of Things Infrastructure
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Author : Uttam Ghosh
language : en
Publisher: CRC Press
Release Date : 2021-09-30
Deep Learning For Internet Of Things Infrastructure written by Uttam Ghosh and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-09-30 with Computers categories.
This book promotes and facilitates exchanges of research knowledge and findings across different disciplines on the design and investigation of deep learning (DL)–based data analytics of IoT (Internet of Things) infrastructures. Deep Learning for Internet of Things Infrastructure addresses emerging trends and issues on IoT systems and services across various application domains. The book investigates the challenges posed by the implementation of deep learning on IoT networking models and services. It provides fundamental theory, model, and methodology in interpreting, aggregating, processing, and analyzing data for intelligent DL-enabled IoT. The book also explores new functions and technologies to provide adaptive services and intelligent applications for different end users. FEATURES Promotes and facilitates exchanges of research knowledge and findings across different disciplines on the design and investigation of DL-based data analytics of IoT infrastructures Addresses emerging trends and issues on IoT systems and services across various application domains Investigates the challenges posed by the implementation of deep learning on IoT networking models and services Provides fundamental theory, model, and methodology in interpreting, aggregating, processing, and analyzing data for intelligent DL-enabled IoT Explores new functions and technologies to provide adaptive services and intelligent applications for different end users Uttam Ghosh is an Assistant Professor in the Department of Electrical Engineering and Computer Science, Vanderbilt University, Nashville, Tennessee, USA. Mamoun Alazab is an Associate Professor in the College of Engineering, IT and Environment at Charles Darwin University, Australia. Ali Kashif Bashir is a Senior Lecturer/Associate Professor and Program Leader of BSc (H) Computer Forensics and Security at the Department of Computing and Mathematics, Manchester Metropolitan University, United Kingdom. Al-Sakib Khan Pathan is an Adjunct Professor of Computer Science and Engineering at the Independent University, Bangladesh.
Proceedings Of The 22nd Acm Sigsac Conference On Computer And Communications Security
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Author : Indrajit Ray
language : en
Publisher:
Release Date : 2015-10-12
Proceedings Of The 22nd Acm Sigsac Conference On Computer And Communications Security written by Indrajit Ray and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-10-12 with Computer science categories.
CCS'15: The 22nd ACM Conference on Computer and Communications Security Oct 12, 2015-Oct 16, 2015 Denver, USA. You can view more information about this proceeding and all of ACM�s other published conference proceedings from the ACM Digital Library: http://www.acm.org/dl.
Strategies For E Commerce Data Security Cloud Blockchain Ai And Machine Learning
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Author : Goel, Pawan Kumar
language : en
Publisher: IGI Global
Release Date : 2024-08-22
Strategies For E Commerce Data Security Cloud Blockchain Ai And Machine Learning written by Goel, Pawan Kumar and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-08-22 with Business & Economics categories.
In the landscape of e-commerce, data security has become a concern as businesses navigate the complexities of sensitive customer information protection and cyber threat mitigation. Strategies involving cloud computing, blockchain technology, artificial intelligence, and machine learning offer solutions to strengthen data security and ensure transactional integrity. Implementing these technologies requires a balance of innovation and efficient security protocols. The development and adoption of security strategies is necessary to positively integrate cutting-edge technologies for effective security in online business. Strategies for E-Commerce Data Security: Cloud, Blockchain, AI, and Machine Learning addresses the need for advanced security measures, while examining the current state of e-commerce data security. It explores strategies such as cloud computing, blockchain, artificial intelligence, and machine learning. This book covers topics such as cybersecurity, cloud technology, and forensics, and is a useful resource for computer engineers, business owners, security professionals, government officials, academicians, scientists, and researchers.