Privacy Preserving Ai Models In Cloud Based Cybersecurity
DOWNLOAD
Download Privacy Preserving Ai Models In Cloud Based Cybersecurity PDF/ePub or read online books in Mobi eBooks. Click Download or Read Online button to get Privacy Preserving Ai Models In Cloud Based Cybersecurity book now. This website allows unlimited access to, at the time of writing, more than 1.5 million titles, including hundreds of thousands of titles in various foreign languages. If the content not found or just blank you must refresh this page
Privacy Preserving Ai Models In Cloud Based Cybersecurity
DOWNLOAD
Author : Amit Goswami
language : en
Publisher: SGSH Publications
Release Date : 2025-02-27
Privacy Preserving Ai Models In Cloud Based Cybersecurity written by Amit Goswami and has been published by SGSH Publications this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-02-27 with Antiques & Collectibles categories.
The book Privacy-Preserving AI Models in Cloud-Based Cybersecurity explores the intersection of artificial intelligence (AI), cybersecurity, and privacy protection in cloud computing. It highlights how AI can enhance cybersecurity by identifying and mitigating threats in real-time while addressing the privacy concerns that arise from data processing in cloud environments. The book is structured into multiple chapters, covering key topics such as homomorphic encryption, differential privacy, federated learning, and their applications in AI-driven cybersecurity frameworks. It begins by discussing the challenges of integrating AI into cybersecurity, particularly the risks associated with cloud storage, data breaches, and regulatory compliance (e.g., GDPR and HIPAA). It then explores various privacy-preserving techniques, including encryption and decentralized learning models, that enable AI systems to function without directly accessing sensitive data. Homomorphic encryption is highlighted as a transformative cryptographic method that allows computations on encrypted data, making it highly relevant for secure cloud-based AI applications. Similarly, differential privacy is discussed as a method to introduce noise into datasets, ensuring anonymity while maintaining data utility. Federated learning is presented as a decentralized AI training approach that enables multiple entities to collaborate without sharing raw data, enhancing security in sectors like healthcare and finance. The book also examines real-world applications, such as AI-driven fraud detection, automated cybersecurity incident response, and privacy-preserving AI for medical data analysis. It concludes with a discussion on future trends, emphasizing the need for scalable encryption solutions, improved AI model robustness against adversarial attacks, and evolving regulatory frameworks. Overall, Privacy-Preserving AI Models in Cloud-Based Cybersecurity provides a comprehensive guide for researchers, cybersecurity professionals, and policymakers seeking to balance AI innovation with data privacy in an increasingly cloud-driven world.
Security And Privacy In Cloud Based Ai
DOWNLOAD
Author : Samarth Shah Dr. Vikhyat Singhal
language : en
Publisher: DeepMisti Publication
Release Date : 2025-01-01
Security And Privacy In Cloud Based Ai written by Samarth Shah Dr. Vikhyat Singhal and has been published by DeepMisti Publication this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-01-01 with Computers categories.
In an era where cloud computing and artificial intelligence (AI) are driving digital transformation across industries, security and privacy have become critical concerns for businesses, governments, and consumers alike. The convergence of AI with cloud-based infrastructures brings about unprecedented opportunities, yet it also introduces a unique set of challenges. As organizations continue to rely on cloud-based AI systems for their operations, the importance of securing sensitive data and safeguarding privacy has never been more paramount. Security and Privacy in Cloud-Based AI explores the complex intersection of cloud computing, artificial intelligence, and cybersecurity, providing a comprehensive framework for understanding the evolving risks and mitigation strategies in this space. The book is designed for professionals, researchers, and policymakers seeking to navigate the intricacies of AI technologies deployed in cloud environments, while ensuring that security and privacy concerns are addressed from the ground up. This book begins by laying a foundation of essential concepts, including the architecture of cloud-based AI systems, the nature of security threats in these environments, and the fundamental principles of data privacy. From there, it delves into the most pressing security and privacy issues—ranging from data breaches and AI model vulnerabilities to regulatory compliance and ethical considerations. It also highlights emerging solutions such as advanced encryption techniques, federated learning, and privacy-preserving AI models, which are reshaping the landscape of secure cloud-based AI deployments. In each chapter, we explore real-world case studies and practical applications, providing insights into how organizations can adopt best practices to safeguard their AI models and data while maintaining trust and transparency with end-users. Additionally, this book examines the regulatory frameworks and policies that govern AI security and privacy, offering a roadmap for navigating complex legal landscapes. As cloud-based AI continues to evolve, so too must our understanding of how to protect the valuable data and technologies driving this revolution. This book aims to equip readers with the knowledge and tools necessary to build secure, privacy-conscious AI systems in the cloud, and to proactively address the challenges that lie ahead. I hope that Security and Privacy in Cloud-Based AI serves as an invaluable resource for those looking to stay ahead of the curve in the rapidly advancing world of AI and cloud security. Authors
Understanding Ai In Cybersecurity And Secure Ai
DOWNLOAD
Author : Dilli Prasad Sharma
language : en
Publisher: Springer Nature
Release Date : 2025-05-26
Understanding Ai In Cybersecurity And Secure Ai written by Dilli Prasad Sharma and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-05-26 with Business & Economics categories.
This book presents an overview of the emerging topics in Artificial Intelligence (AI) and cybersecurity and addresses the latest AI models that could be potentially applied to a range of cybersecurity areas. Furthermore, it provides different techniques of how to make the AI algorithms secure from adversarial attacks. The book presents the cyber threat landscape and explains the various spectrums of AI and the applications and limitations of AI in cybersecurity. Moreover, it explores the applications and limitations of secure AI. The authors discuss the three categories of machine learning (ML) models and reviews cutting-edge recent Deep Learning (DL) models. Furthermore, the book provides a general AI framework in security as well as different modules of the framework; similarly, chapter four proposes a general framework for secure AI. It explains different aspects of network security including malware and attacks. The book also includes a comprehensive study of various scopes of application security; categorised into three groups of smartphone, web application, and desktop application and delves into the concepts of cloud security. The authors discuss state-of-the-art Internet of Things (IoT) security and describe various challenges of AI for cybersecurity, such as data diversity, model customising, explainability, and time complexity and includes some future work. They provide a comprehensive understanding of adversarial machine learning including the up-to-date adversarial attacks and defences. The book finishes off with a discussion of the challenges and future work in secure AI. Overall, this book covers applications of AI models to various fields of cybersecurity and appeals not only to an scholarly audience but also to professionals wanting to learn more about the new developments in these areas.
Privacy Preservation And Secured Data Storage In Cloud Computing
DOWNLOAD
Author : D., Lakshmi
language : en
Publisher: IGI Global
Release Date : 2023-10-25
Privacy Preservation And Secured Data Storage In Cloud Computing written by D., Lakshmi and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-10-25 with Computers categories.
As cloud services become increasingly popular, safeguarding sensitive data has become paramount. Privacy Preservation and Secured Data Storage in Cloud Computing is a comprehensive book that addresses the critical concerns surrounding privacy and security in the realm of cloud computing. Beginning with an introduction to cloud computing and its underlying technologies, the book explores various models of cloud service delivery. It then delves into the challenges and risks associated with storing and processing data in the cloud, including data breaches, insider threats, and third-party access. The book thoroughly examines techniques and tools to enhance privacy and security in the cloud, covering encryption, access control, data anonymization, and other measures to mitigate risks. Additionally, it explores emerging trends and opportunities in cloud security, such as blockchain-based solutions, homomorphic encryption, and other cutting-edge technologies poised to transform data privacy and security. This invaluable resource offers practical advice and in-depth analysis for cloud service providers, IT professionals, researchers, and students seeking to understand best practices for securing data in the cloud.
Convergence Of Cybersecurity And Cloud Computing
DOWNLOAD
Author : Avanija, J.
language : en
Publisher: IGI Global
Release Date : 2024-12-27
Convergence Of Cybersecurity And Cloud Computing written by Avanija, J. and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-12-27 with Computers categories.
The convergence of cybersecurity and cloud computing is crucial for protecting data and ensuring the integrity of digital systems in an increasingly interconnected world. As cloud computing continues to grow, so does the need for robust security measures to address vulnerabilities in these environments. Understanding how to secure cloud deployments is essential for businesses, organizations, and individuals to safeguard sensitive information and maintain trust in digital services. By addressing the unique security challenges posed by cloud computing, society can better adapt to the evolving landscape of digital threats and ensure the safety of critical infrastructure. Convergence of Cybersecurity and Cloud Computing is a comprehensive resource to navigate the link between cybersecurity and cloud computing. It discusses the unique security challenges that arise from cloud environments. Covering topics such as artificial intelligence, data protection, and threat detection, this book is an excellent resource for academicians, research scholars, IT professionals, security experts, faculty, and more.
Smart Cities Cybersecurity And Privacy
DOWNLOAD
Author : Danda B. Rawat
language : en
Publisher: Elsevier
Release Date : 2018-12-04
Smart Cities Cybersecurity And Privacy written by Danda B. Rawat and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-12-04 with Computers categories.
Smart Cities Cybersecurity and Privacy examines the latest research developments and their outcomes for safe, secure, and trusting smart cities residents. Smart cities improve the quality of life of citizens in their energy and water usage, healthcare, environmental impact, transportation needs, and many other critical city services. Recent advances in hardware and software, have fueled the rapid growth and deployment of ubiquitous connectivity between a city's physical and cyber components. This connectivity however also opens up many security vulnerabilities that must be mitigated. Smart Cities Cybersecurity and Privacy helps researchers, engineers, and city planners develop adaptive, robust, scalable, and reliable security and privacy smart city applications that can mitigate the negative implications associated with cyber-attacks and potential privacy invasion. It provides insights into networking and security architectures, designs, and models for the secure operation of smart city applications. - Consolidates in one place state-of-the-art academic and industry research - Provides a holistic and systematic framework for design, evaluating, and deploying the latest security solutions for smart cities - Improves understanding and collaboration among all smart city stakeholders to develop more secure smart city architectures
Revolutionizing Cybersecurity With Deep Learning And Large Language Models
DOWNLOAD
Author : Zangana, Hewa Majeed
language : en
Publisher: IGI Global
Release Date : 2025-04-08
Revolutionizing Cybersecurity With Deep Learning And Large Language Models written by Zangana, Hewa Majeed and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-04-08 with Computers categories.
As cyber threats grow, national security measures struggle to keep pace with sophisticated attacks. Deep learning and large language models (LLMs) revolutionize cybersecurity by enabling advanced threat detection automated response mechanisms and analytics. AI technologies can analyze vast amounts of data, recognize patterns, and identify threats to security systems. Using deep learning and LLMs to transform cybersecurity is essential for addressing both their potential and the challenges that come with their adoption. Revolutionizing Cybersecurity With Deep Learning and Large Language Models explores the intersection of AI, cybersecurity, deep learning, and LLMs, and the potential of these technologies in safeguarding the digital world. It examines real-world applications, ethical challenges, and new technological advancements. This book covers topics such as artificial intelligence, cybersecurity, and threat detection, and is a useful resource for academicians, researchers, security professionals, computer engineers, and data scientists.
Proceedings Of The International Conference On Sustainability Innovation In Computing And Engineering Icsice 24
DOWNLOAD
Author : S. Kannadhasan
language : en
Publisher: Springer Nature
Release Date : 2025-06-24
Proceedings Of The International Conference On Sustainability Innovation In Computing And Engineering Icsice 24 written by S. Kannadhasan and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-06-24 with Computers categories.
This is an open access book. The International Conference on Sustainability Innovation in Computing and Engineering is a distinguished event that brings together leading experts, researchers, practitioners, and innovators to explore the transformative role of computing and engineering in advancing sustainable solutions. In today’s world, where environmental challenges are intensifying, the need for technological innovation in addressing sustainability issues has never been more urgent. This conference serves as a dynamic platform for sharing groundbreaking research, showcasing innovative technologies, and fostering cross-disciplinary collaborations to accelerate sustainable development. With a focus on integrating sustainability into the core of computing and engineering practices, this conference will delve into a wide array of topics such as sustainable computing technologies, energy-efficient systems, green engineering practices, and the role of data science in promoting sustainability. It will also highlight the latest advancements in areas like artificial intelligence, smart systems, and digital solutions that contribute to environmental stewardship and social equity. The conference aims to bridge the gap between theoretical research and practical application, empowering participants to develop actionable strategies and innovative solutions that can be deployed in real-world scenarios. By facilitating robust discussions and knowledge exchange, the conference seeks to inspire new ideas, foster collaboration, and catalyze the development of technologies that not only enhance efficiency and performance but also contribute to a more sustainable future. It is an honor to host a gathering of visionary leaders in computing and engineering, whose expertise and insights will guide the global movement toward a greener, more sustainable world.
Model Optimization Methods For Efficient And Edge Ai
DOWNLOAD
Author : Pethuru Raj Chelliah
language : en
Publisher: John Wiley & Sons
Release Date : 2024-11-13
Model Optimization Methods For Efficient And Edge Ai written by Pethuru Raj Chelliah 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 2024-11-13 with Computers categories.
Comprehensive overview of the fledgling domain of federated learning (FL), explaining emerging FL methods, architectural approaches, enabling frameworks, and applications Model Optimization Methods for Efficient and Edge AI explores AI model engineering, evaluation, refinement, optimization, and deployment across multiple cloud environments (public, private, edge, and hybrid). It presents key applications of the AI paradigm, including computer vision (CV) and Natural Language Processing (NLP), explaining the nitty-gritty of federated learning (FL) and how the FL method is helping to fulfill AI model optimization needs. The book also describes tools that vendors have created, including FL frameworks and platforms such as PySyft, Tensor Flow Federated (TFF), FATE (Federated AI Technology Enabler), Tensor/IO, and more. The first part of the text covers popular AI and ML methods, platforms, and applications, describing leading AI frameworks and libraries in order to clearly articulate how these tools can help with visualizing and implementing highly flexible AI models quickly. The second part focuses on federated learning, discussing its basic concepts, applications, platforms, and its potential in edge systems (such as IoT). Other topics covered include: Building AI models that are destined to solve several problems, with a focus on widely articulated classification, regression, association, clustering, and other prediction problems Generating actionable insights through a variety of AI algorithms, platforms, parallel processing, and other enablers Compressing AI models so that computational, memory, storage, and network requirements can be substantially reduced Addressing crucial issues such as data confidentiality, data access rights, data protection, and access to heterogeneous data Overcoming cyberattacks on mission-critical software systems by leveraging federated learning Written in an accessible manner and containing a helpful mix of both theoretical concepts and practical applications, Model Optimization Methods for Efficient and Edge AI is an essential reference on the subject for graduate and postgraduate students, researchers, IT professionals, and business leaders.
Strategies For E Commerce Data Security Cloud Blockchain Ai And Machine Learning
DOWNLOAD
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.