Enhancing Security Mechanisms in Cloud Computing Optimisation for Modern Data Protection Strategies

With the ubiquity of digital media, managing personal data has become part of our daily lives. Teachers have to manage not only their own data, they also manage students’ sensitive data and furthermore have to teach data protection to students. In Switzerland, teacher education colleges have hence started to educate students about privacy and data protection. To do this effectively, it is important to understand pre-service teachers’ attitudes about online privacy and to assess their knowledge about protection strategies. Therefore, we tested whether existing scales for attitudes (perceived severity, perceived vulnerability, self-efficacy) about online privacy in social networks can be applied to pre-service teachers and be extended to e-mail and cloud storage. We then explored how these attitudes relate to protection strategies. Except for perceived vulnerability regarding social networks, we succeeded in reliably measuring the three different attitudes in the three domains. Priming did not change the attitudes. However, we did find that self-efficacy was related to the degree to which students report using data protection strategies. This suggests that to motivate pre-service teachers to engage in data protection, teaching them these strategies is more effective than making them more aware of their vulnerability and the severity of data breaches.

Disk drive failure related data lost remains a major threat to storage system reliability. Current counter-measurement all focused on reactive data protection, such as using RAID or erasure coding to reconstruct data after failure occurs. We argue that post-failure recovery will not scalable when the storage demand keep increase. In this paper, we present a proactive data protection (PDP) framework within the ZFS file system to rescue data from disks before actual failure onset. By reducing the risk of data loss and mitigating the prolonged disk rebuilds caused by disk failures, PDP is designed to enhance the overall storage reliability. We extensively evaluate the recovery performance of ZFS with diverse configurations, and further explore disk failure prediction techniques to develop a proactive data protection mechanism in ZFS. We further compare the performance of different data protection strategies, including post-failure disk recovery, proactive disk cloning, and proactive data recovery. We propose an analytic model that uses storage utilization and contextual system information to select the best data protection strategy that can save up to 70% of data rescue time.

Cloud computing and cloud services provide an alternative IT infrastructure and service models for users. The users use cloud to store their data, delegate the management of the data, and deploy their services cost-effectively. This usage model, however, raised a number of concerns relating to data control, data protection and data mobility: 1) users may lose control of their resource, 2) data protection schemes are not adequate when data is moved to a new cloud, 3) tracking and tracing changes of data location as well as accountability of data operations are not well supported. To address these issues, this paper proposes a novel cloud service for data mobility from two aspects: data mobility and data protection. A data mobility service is designed and implemented to manage data mobility and data traceability. A Location Register Database (LRD) is also developed to support the service. Furthermore, data is protected by a data security service CPRBAC (Cloud-based Privacy-aware Role Based Access Control) and an Auditing service that are capable of verifying data operations and triggering alarms on data violations in the Cloud environment.

With the increasing importance of data in modern business environments, effective data management and protection strategies are gaining increasing research attention. Data protection in a cloud environment is crucial for safeguarding information assets and maintaining sustainable services. This study introduces a system structure that integrates Kubernetes management platforms with backup and restoration tools. This system is designed to immediately detect disasters and automatically recover applications from another Kubernetes cluster. The experimental results show that this system executes the restoration process within 15 s without human intervention, enabling rapid recovery. This, in turn, significantly reduces the potential for delays and errors compared to manual recovery processes, thereby enhancing data management and recovery efficiency in cloud environments. Moreover, our research model predicts the CPU utilization of the cluster using Long Short-Term Memory (LSTM). The necessity of scheduling through this predict is made clearer through comparison with experiments without scheduling, demonstrating its ability to prevent performance degradation. This research highlights the efficiency and necessity of automatic recovery systems in cloud environments, setting a new direction for future research.

An optimal secure transmission scheme of space data is designed by optimizing the secure distribution of the space observation data in view of the change of source-channel condition. Various source-channel models are built based on the optimization objective of data quality, and then the data protection strategy and approach based on joint source-channel and secure coding are proposed. A quality evaluation and distribution model of space observation data is established, and the secure distribution of space observation data under separated source-channel coding and the encryption-authentication distribution of space observation data under joint source-channel coding are optimized and evaluated. The algorithms are analyzed and simulated. The data protection strategy and approach are validated in robustness, scalability and reliability. Keywords—information technology;information security; space data; information attribute; security mechanism

The data breach and regulatory scrutiny are spreading across the Organization; in such a phase, the Organization that is utilizing Customer Relationship Management (CRM), which is a selling force, faces the challenges of securing the data and compliance. Given the greater prevalence of sensitive customer data being processed, businesses must deploy stringent strategies that protect and keep information in line with strict regulations like the General Data Protection Regulation (GDPR) and the California Consumer Privacy Act (CCPA). This article will review how Salesforce, data protection, and compliance fit together when artificial intelligence (AI) is involved. Today, AI technologies are becoming powerful tools in data security, and their new directions are aimed at using these technologies to identify potential risks and automate compliance processes. Since AI analyzes vast amounts of data in real time, it can identify anomalies, predict breaches, and improve reporting processes. By enabling this, the efficacy of data protection measures and compliance with emerging regulations are improved. Using AI in conjunction with Salesforce is beneficial in managing customer data and, in this case, helps organizations respond faster to compliance requirements and maintain their clients' trust. As businesses continue using Salesforce as their CRM, they must understand its built-in data protection features and best practices, primarily once they rely on the platform to store large amounts of business-critical data. In this article, you will learn to use AI with Salesforce to strengthen your data protection strategy as safely as possible, getting practical guidance on dealing with the intricate world of data compliance. Accepting these technologies and practices, businesses protect sensitive information and breed a culture of compliance that aligns with their strategic goals.

As data center managers consider deployment of a Cloud Computing environment the most important issues they consider include critical application data availability, storage agility and data protection strategies. Early adopters of Cloud Computing have already deployed Virtualization as a key technology in their Infrastructure as a Service (IaaS) and Platform as a Service (PaaS) offerings. Cloud computing extends the benefits of virtualization by increasing the efficiency of server and storage utilization, reducing costs, improving operational efficiency and optimizing datacenter rack and floor space. It builds on first-generation system and storage virtualization with features such as application portability and storage agility to enable higher efficiencies and greater efficiencies across the enterprise. With recent innovation in storage, key features such as thin-provisioning, compression and de-duplication work in concert with virtualized infrastructure on the Storage Appliance to eliminate duplicate data blocks, compress data and allocate the amount of storage being consumed by users. Data services such as snapshots and clones provide instant and optionally, unattended backups that can be used in the short term for recovery of critical data. Disaster recovery is all the more important within the cloud computing environment and built in replication services enable a robust solution in case of a catastrophic event or simply for purposes of backup and recovery.

The exponential growth of big data and the increasing complexity of cloud infrastructures have heightened the demand for robust security frameworks. This study presents the implementation process and analyzes the effect of zero-trust architecture (ZTA) on system reliability and data protection in big-data cloud environments. The methodology involves a comprehensive research approach, encompassing a review of existing research papers and the execution of a narrative review and content analysis to identify critical issues related to ZTA, system reliability, and data protection. The findings indicate that ZTA, with its robust access control mechanisms, can enhance data protection in a practical and tangible manner, thereby contributing to the enhancement of operational efficiency. This implies that organizations that embrace ZTA can fortify their data protection strategies and experience substantial real-world improvements in system reliability. A continuous monitoring system aids in the detection of anomalies and maintenance records, leading to reduced downtimes and improved system reliability. This study underscores the crucial role of strategic planning, resource management, and awareness training in the seamless integration of ZTA into organizational functionality for superior outcomes.

The digital landscape has witnessed a significant transformation since the introduction of cookies in the mid-1990s, evolving from simple user tracking mechanisms to complex tools integral to online user experiences and targeted advertising. This evolution, however, has not come without consequences; the proliferation of cookies has raised substantial concerns regarding user privacy and data security, prompting the development of regulatory frameworks such as the General Data Protection Regulation (GDPR)1 and the ePrivacy Directive.2 This paper undertakes a critical analysis of the intricate intersection between cookies, the ePrivacy Directive and the GDPR, with a particular focus on the IAB Belgium ruling.3 This landmark case has catalysed significant changes in consent practices, reshaping the digital advertising ecosystem and compelling businesses to reassess their data protection strategies. Notably, the ruling reinforces the primacy of consent under GDPR for cookie deployment, particularly in the context of personalised advertising. The decision also brings into stark relief the unresolved tension between consent-based models and the use of legitimate interest as an alternative legal basis for data processing. While the IAB Belgium ruling firmly aligns with the GDPR’s stringent consent requirements, the European Court of Justice’s (ECJ) subsequent rulings on legitimate interest introduce a potential divergence. For example, in the Koninklijke Nederlandse Lawn Tennisbond (KNLTB) case,4 the court recognised commercial legitimate interest as a lawful basis for processing data, yet this recognition did not extend to cookies, which are central to behavioural advertising and commercial profiling. The recent European Data Protection Board (EDPB) guidelines5 further complicate this regulatory landscape, as they emphasise the need for legitimate interest assessments but offer limited insight into how this legal basis should apply to cookies. This confluence of judicial and regulatory decisions underscores the ongoing challenges in harmonising legitimate interest with cookie-related data processing, calling for a more cohesive regulatory framework. As organisations navigate this complex regulatory environment, the insights provided in this paper aim to serve as a valuable resource for understanding the evolving dynamics of cookie compliance and the broader implications for data protection in the digital age. The paper ultimately seeks to inform stakeholders of the pressing need for accountability and user-centric approaches in the realm of digital privacy.

Purpose: This research paper aims to enhance Big Data security by implementing comprehensive data protection measures, focusing on securing data at rest and in transit. In the era of Big Data, organizations handle vast quantities of data characterized by high velocity, volume, and variety, which complicates management and increases security risks. Methodology: The study examines various data protection strategies, including encryption, access control, data masking, immutable storage, tokenization, and physical security for data at rest. For data in transit, it explores encryption protocols, secure transfer methods like SSH and TLS, VPNs, Zero Trust architecture, and secure APIs. These methods are crucial for safeguarding sensitive information and preventing unauthorized access. Findings: The findings highlight common security challenges in Big Data, such as data breaches, unauthorized access, and integrity issues. The study emphasizes the need for robust protection measures and offers a comprehensive view of the data security landscape. Implementing these strategies helps organizations safeguard sensitive information and ensure compliance with international data protection regulations, enhancing their overall security posture. Unique contribution to theory policy and practice: This paper contributes to theory, policy, and practice by advocating comprehensive data protection strategies. It stresses the importance of continuous monitoring and regulatory compliance, providing practical insights into best practices and technologies that protect Big Data. The research supports developing robust data protection policies and practices, advancing knowledge in Big Data security.

Cloud computing has led to the development of IT to more sophisticated levels by improving the capacity and flexibility of data storage and by providing a scalable computation and processing power which matches the dynamic data requirements. Cloud computing has many benefits which has led to the transfer of many enterprise applications and data to public and hybrid clouds. However, many organizations refer to the protection of privacy and the security of data as the major issues which prevent them from adopting cloud computing. The only way successful implementation of clouds can be achieved is through effective enhancement and management of data security and privacy in clouds. This research paper analyzes the privacy and protection of data in cloud computing through all data lifecycle stages providing an overall perspective of cloud computing while highlighting key security issues and concerns which should be addressed. It also discusses several current solutions and further proposes more solutions which can enhance the privacy and security of data in clouds. Finally, the research paper describes future research work on the protection of data privacy and security in clouds.

Good backup and recovery strategies are key to the health of any organization. Medium- to very-large-scale systems administrators have to protect large amounts of critical data as well as design backup solutions that are scalable and optimized to meet changing conditions. Pro Data Backup and Recovery will cover some of the more common backup applications, such as Symantec NetBackup/BackupExec, EMC NetWorker, and CommVault, but the main discussion will focus on the implementation of 21st century architectures that allow the backup software to be a commodity item. The underlying architecture provides the framework for meeting the requirements of data protection for the organization. This book covers new developments in data protection as well as the impact of single-instance storage upon backup infrastructures. It discusses the impact of backup and data replication, the often misapplied B2D and D2D strategies, and tapeless backup environments. Continuous data protection and remote replication strategies are also addressed as they are integrated within backup strategiesa very important topic today. Learn backup solution design regardless of specific backup software Design realistic recovery solutions Take into account new data protection standards and the impact of data replication Whether you are using NetBackup, CommVault, or some other backup software, Pro Data Backup and Recovery will give you the information you need to keep your data safe and available. What youll learn Elements of a backup environment and applications of those elements New technologies within the backup technology area and their impact on design Configurations using both Symantec NetBackup and CommVault Simpana, with combinations of backup serves, media servers, and clients, and the impacts of each combination Combinations of both hardware and software configurations that are scalable from small to large environments Designs that address perennial problem areas such as remote offices, very short (less-than-15-minute) recovery point objectives (RPOs), and tape management Reporting requirements that will assist in maintaining and growing an implementation once executed Who this book is for The general audience for this book includes systems engineers, systems administrators, and specialist backup administrators Table of Contents Introduction to Backup and Recovery Backup Software Physical Backup Media Virtual Backup Media New Media Technologies Software Architectures: CommVault Software Architectures: NetBackup Application Backup Strategies Putting It All Together: Sample Backup Environments Monitoring and Reporting Summary

A Study on the Extraterritorial Application of the General Data Protection Regulation with a Focus on Computing

Today, the use of cloud computing for better data protection has been increased to a great extent. One of the essential reasons for using cloud computing as a means of data protection is that users can easily access relevant data with the proper security protocols. However, various sectors such as healthcare, finance, automotive, education, manufacturing, etc. have experienced a lot of challenges regarding large and confidential data protection in the past few decades. With the advent of Cloud-computing in recent times, all the issues related to data security and information protection have been easier than before. Researchers have conducted an effective quantitative data collection approach by performing primary analysis through surveys. With a probability sampling technique, researchers have asked around 60 participants from different industrial fields about their opinions regarding the research topic. As per research findings around 60% of people have supported that cloud computing is essential for maximizing data protection. Around 30% people agreed with the <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$24 \times 7$</tex> information monitoring and data encryption challenges can be solved with cloud computing. On the other hand, around 10% of participants have placed their positive opinion over the error reduction in data protection by using cloud computing. Researchers in this particular research paper are going to explain the importance of using cloud computing as a data security tool. In order to create better data protection systems across various industrial departments, cloud computing can be used in the future research as well.

IntroductionData security is a critical issue in today's digital age, exacerbated by the rampant online buying and selling of consumers’ personal data. This study focuses on the strategies employed by microfinance institutions, specifically Baitul Maal wa Tamwil (BMT), to protect member data and manage the associated risks.ObjectivesThe objective of this study is to describe mitigation strategies for data protection and risk management implemented by BMTs in Lampung. MethodThis field research employs qualitative methods, including observation and interviews, which are analyzed using the inductive thinking paradigm. Data collection focuses on BMTs' risk management practices and their cooperation with commercial banks to transfer risk.ResultsThe findings reveal that BMTs in Lampung have implemented effective risk-management strategies for data protection. Some BMTs transfer risk to commercial banks, a strategy known as risk transfer. Others adopt risk reduction and acceptance strategies by enhancing data security, training employees on system use, and managing existing risks to minimize business impact. ImplicationsThis study highlights the importance of robust data protection and risk management strategies to maintain customer trust in microfinance institutions. Effective risk mitigation ensures customer data security, thereby enhancing the credibility and sustainability of BMTs.Originality/NoveltyThis study contributes to the understanding of data security practices in microfinance institutions, particularly in the context of Islamic microfinance, by exploring practical mitigation strategies and their implementation.