International Journal of Computing and Engineering

Federated Learning for Cybersecurity in Edge and Cloud Computing

Phani Sekhar Emmanni — Tue, 12 Mar 2024 00:00:00 +0300

Purpose: The article explores the integration of federated learning within edge and cloud computing frameworks to address complex cybersecurity challenges. It aims to illustrate how federated learning, by enabling collaborative model training across decentralized devices without data exchange, can serve as an effective mechanism for enhancing cybersecurity defenses. This study investigates the potential of federated learning to improve privacy-preserving data analysis and augment real-time threat detection capabilities in the context of the growing Internet of Things (IoT) ecosystem.

Methodology: The research delves into the conceptual framework of federated learning, examining its application in cybersecurity contexts through a detailed literature review and theoretical analysis. It evaluates the benefits and limitations of federated learning in enhancing data privacy and reducing latency in threat detection. Furthermore, the article assesses the technical and security challenges of implementing federated learning, including communication overhead, model aggregation complexities, and vulnerability to model poisoning, through qualitative analysis.

Findings: The study finds that federated learning significantly improves privacy-preserving data analysis and enhances real-time threat detection capabilities by keeping data localized while enabling collaborative learning. However, it also identifies key challenges in deploying federated learning strategies, such as the risk of model poisoning and the complexities involved in model aggregation and communication overhead. The research highlights the need for robust mechanisms to address these challenges to fully leverage federated learning in cybersecurity.

Unique Contribution to Theory, Policy, and Practice: This article contributes uniquely to the theoretical understanding of federated learning as a cybersecurity measure, offering a comprehensive analysis of its applications, benefits, and limitations within edge and cloud computing environments. Practically, it provides insights for cybersecurity professionals and researchers on integrating federated learning into existing cybersecurity frameworks to enhance data privacy and threat detection. The article recommends further exploration into combining federated learning with other cutting-edge technologies to develop resilient cybersecurity measures. Additionally, it suggests that policymakers should consider the implications of federated learning on data privacy regulations and cybersecurity standards. Through its thorough examination of federated learning's potential and challenges, the article offers valuable recommendations for fortifying cybersecurity frameworks in an increasingly interconnected world.

Revolutionizing Frontend Development: Embracing Micro UI Architecture with Cloud Integration

Phani Sekhar Emmanni — Thu, 14 Mar 2024 00:00:00 +0300

Purpose: The primary aim of this study is to dissect and highlight the ongoing transformative shift in frontend development practices, predominantly spurred by the adoption of Micro UI architecture and its synergistic integration with cloud services. This transformation is poised to address critical challenges in scalability, modularity, and development efficiency that currently beset web application development. By investigating the theoretical underpinnings and practical applications of Micro UI architecture in tandem with cloud technologies, the study elucidates its potential to revolutionize frontend development, enhance team dynamics, and elevate application performance.

Methodology: This article adopts a comprehensive approach to explore the theoretical foundations and practical implications of Micro UI architecture and cloud integration in frontend development. The methodology encompasses a comparative analysis with the microservices approach in backend development, detailed case studies on the implementation of Micro UI with cloud services, and an empirical examination of its effects on development processes and application performance. Through this multifaceted methodology, the article aims to provide a holistic understanding of Micro UI architecture’s role in modern web development.

Findings: The findings reveal that Micro UI architecture, characterized by its decoupled, component-based strategy, significantly contributes to simplifying the complexities inherent in modern web development. This architectural approach, when combined with the expansive capabilities of cloud computing, facilitates the development of more resilient, scalable, and performant frontend applications. Additionally, the study finds that this convergence enhances development efficiency, fosters better team collaboration, and promotes a more agile development environment. The integration with cloud services further ensures a seamless and robust user experience globally, underscoring the transformative potential of embracing Micro UI architecture in frontend development.

Unique Contribution to Theory, Policy, and Practice: The article makes a unique contribution to the theoretical framework of frontend development by systematically articulating the concept of Micro UI architecture and delineating its integration with cloud technologies. On a practical level, it offers actionable insights and guidelines for development teams and organizations looking to adopt this innovative approach. Policy-wise, it suggests frameworks for standardizing practices and protocols in deploying Micro UI components and integrating cloud services. Recommendations include the adoption of Micro UI architecture as a standard practice in frontend development, the development of best practices for its integration with cloud services, and the encouragement of collaborative efforts across teams to leverage the full potential of this transformative approach. By doing so, the study paves the way for a new era of frontend development that is more scalable, efficient, and conducive to innovation.

Ethical Considerations in the Collection and Handling of Financial Data in ETC

Pankaj Lembhe — Wed, 24 Apr 2024 00:00:00 +0300

Purpose: This research note provides some practical advice on accessing financial reports on the internet and the collection of associated data for subsequent analysis.

Methodology: Potential methodological problems, such as biases or conflicts of interest, should be acknowledged and strategies for addressing them should be outlined.

Findings: Additionally, the confidentiality and privacy of individuals or companies whose financial data is being collected must be protected.

Unique contribution to theory, practice, and policy: The guidance on accessing and collecting financial data online contributes to both the theoretical framework of financial analysis and practical applications for researchers and practitioners, ensuring ethical standards are maintained.