This work provides guidelines for the practical implementation of security architecture in a particular corporate cloud. The authors are mathematicians and specialists in data modeling and security. Experience of scientific collaboration with industry inspired the authors to attempt to conceptualize the common processes and strategies in cloud security, in order to make security system deployment as simple and transparent as possible. The deployment is broken into several essential steps that allow the functionality of security architecture for any cloud to be split into a set of modules. The continuous verification of security support on all levels (data, processes and communication channels) helps to avoid common security breaches and protect against the most dangerous attacks. Additionally, performing the proposed optimization of the selected set of mechanisms will enhance the efficiency of the security system.

Cloud Storage Security: A Practical Guide introduces and discusses the risks associated with cloud-based data storage from a security and privacy perspective. Gain an in-depth understanding of the risks and benefits of cloud storage illustrated using a Use-Case methodology. The authors also provide a checklist that enables the user, as well as the enterprise practitioner to evaluate what security and privacy issues need to be considered when using the cloud to store personal and sensitive information. - Describes the history and the evolving nature of cloud storage and security - Explores the threats to privacy and security when using free social media applications that use cloud storage - Covers legal issues and laws that govern privacy, compliance, and legal responsibility for enterprise users - Provides guidelines and a security checklist for selecting a cloud-storage service provider - Includes case studies and best practices for securing data in the cloud - Discusses the future of cloud computing

This book provides a comprehensive overview of data security in cloud storage, ranging from basic paradigms and principles, to typical security issues and practical security solutions. It also illustrates how malicious attackers benefit from the compromised security of outsourced data in cloud storage and how attacks work in real situations, together with the countermeasures used to ensure the security of outsourced data. Furthermore, the book introduces a number of emerging technologies that hold considerable potential – for example, blockchain, trusted execution environment, and indistinguishability obfuscation – and outlines open issues and future research directions in cloud storage security. The topics addressed are important for the academic community, but are also crucial for industry, since cloud storage has become a fundamental component in many applications. The book offers a general introduction for interested readers with a basic modern cryptography background, and a reference guide for researchers and practitioners in the fields of data security and cloud storage. It will also help developers and engineers understand why some current systems are insecure and inefficient, and move them to design and develop improved systems.

Cloud storage is an important service of cloud computing, which offers service for data owners to host their data in the cloud. This new paradigm of data hosting and data access services introduces two major security concerns. The first is the protection of data integrity. Data owners may not fully trust the cloud server and worry that data stored in the cloud could be corrupted or even removed. The second is data access control. Data owners may worry that some dishonest servers provide data access to users that are not permitted for profit gain and thus they can no longer rely on the servers for access control. To protect the data integrity in the cloud, an efficient and secure dynamic auditing protocol is introduced, which can support dynamic auditing and batch auditing. To ensure the data security in the cloud, two efficient and secure data access control schemes are introduced in this brief: ABAC for Single-authority Systems and DAC-MACS for Multi-authority Systems. While Ciphertext-Policy Attribute-based Encryption (CP-ABE) is a promising technique for access control of encrypted data, the existing schemes cannot be directly applied to data access control for cloud storage systems because of the attribute revocation problem. To solve the attribute revocation problem, new Revocable CP-ABE methods are proposed in both ABAC and DAC-MACS.

The three-volume proceedings set LNCS 13655,13656 and 13657 constitutes the refereedproceedings of the 4th International Conference on Machine Learning for Cyber Security, ML4CS 2022, which taking place during December 2–4, 2022, held in Guangzhou, China. The 100 full papers and 46 short papers were included in these proceedings were carefully reviewed and selected from 367 submissions.

The 3-volume set CCIS 1252 until CCIS 1254 constitutes the refereed proceedings of the 6th International Conference on Artificial Intelligence and Security, ICAIS 2020, which was held in Hohhot, China, in July 2020. The conference was formerly called “International Conference on Cloud Computing and Security” with the acronym ICCCS. The total of 178 full papers and 8 short papers presented in this 3-volume proceedings was carefully reviewed and selected from 1064 submissions. The papers were organized in topical sections as follows: Part I: artificial intelligence; Part II: artificial intelligence; Internet of things; information security; Part III: information security; big data and cloud computing; information processing.

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Enterprise security is an important area since all types of organizations require secure and robust environments, platforms and services to work with people, data and computing applications. The book provides selected papers of the Second International Workshop on Enterprise Security held in Vancouver, Canada, November 30-December 3, 2016 in conjunction with CloudCom 2015. The 11 papers were selected from 24 submissions and provide a comprehensive research into various areas of enterprise security such as protection of data, privacy and rights, data ownership, trust, unauthorized access and big data ownership, studies and analysis to reduce risks imposed by data leakage, hacking and challenges of Cloud forensics.

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.