International Journal of Computing and Engineering最新文献

Enhancing Cyber Resilience: Convergence of SIEM, SOAR, and AI in 2024 增强网络复原力：2024 年 SIEM、SOAR 和 AI 的融合

International Journal of Computing and Engineering Pub Date : 2024-03-28 DOI: 10.47941/ijce.1754

Shanmugavelan Ramakrishnan, Dinesh Reddy Chittibala

{"title":"Enhancing Cyber Resilience: Convergence of SIEM, SOAR, and AI in 2024","authors":"Shanmugavelan Ramakrishnan, Dinesh Reddy Chittibala","doi":"10.47941/ijce.1754","DOIUrl":"https://doi.org/10.47941/ijce.1754","url":null,"abstract":"Purpose: The study aims to examine the synergistic effects of integrating Security Information and Event Management (SIEM), Security Orchestration, Automation, and Response (SOAR), and Artificial Intelligence (AI) technologies in enhancing cybersecurity frameworks. It explores how this combination can lead to a transformative era in cybersecurity, focusing on the improved efficacy of threat management and incident response. \u0000Methodology: An analytical approach was used to investigate the integration trends between SIEM and SOAR technologies, underpinned by advancements in AI. This method emphasizes accelerated incident detection and response, enriched threat intelligence collaboration, and fortified security strategies. \u0000Findings: The fusion of SIEM, SOAR, and AI technologies has led to a paradigm shift in cybersecurity, offering unparalleled efficiency in threat management and a significant reduction in the impacts of cyber incidents on entities. It highlights the accelerated detection and response to incidents and the enhancement of threat intelligence collaboration and security strategies. \u0000Unique Contribution to Theory, Practice, and Policy: This study contributes to the field by presenting invaluable insights for cybersecurity practitioners and entities aiming to strengthen their defenses against an evolving digital threat landscape. It advocates for a proactive orchestration of security measures, underlining the strategic implications of the SIEM-SOAR-AI triad for future cybersecurity endeavors. Recommendations are provided for entities to adopt this integrated approach to enhance their cybersecurity frameworks effectively.","PeriodicalId":503134,"journal":{"name":"International Journal of Computing and Engineering","volume":"93 12","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140371247","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Cloud Cost Optimization: Achieving Cost Savings through AWS Spot Fleet Utilization and Optimizing Cloud Resource Usage 云成本优化：通过 AWS Spot Fleet 利用率和优化云资源使用实现成本节约

International Journal of Computing and Engineering Pub Date : 2024-03-22 DOI: 10.47941/ijce.1742

Gowtham Mulpuri

引用次数: 0

Advancements in Automated Code Scanning Techniques for Detecting Security Vulnerabilities in Open Source Software 自动代码扫描技术在检测开源软件安全漏洞方面的进展

International Journal of Computing and Engineering Pub Date : 2024-03-21 DOI: 10.47941/ijce.1737

Dinesh Reddy Chittibala

{"title":"Advancements in Automated Code Scanning Techniques for Detecting Security Vulnerabilities in Open Source Software","authors":"Dinesh Reddy Chittibala","doi":"10.47941/ijce.1737","DOIUrl":"https://doi.org/10.47941/ijce.1737","url":null,"abstract":"Purpose: This article aims to shed light on the transformative role of Open Source Software (OSS) in digital infrastructure and the accompanying security challenges. It highlights the critical need for automated code scanning technologies to address vulnerabilities stemming from coding errors, lack of secure coding practices, and the rapid development pace. \u0000Methodology: Through a comprehensive analysis of static, dynamic, and interactive code scanning methods, along with the exploration of AI and ML integration, this study examines scalable and efficient approaches to enhance detection capabilities early in the development lifecycle. \u0000Findings: While automated code scanning technologies have made significant strides in detecting and mitigating vulnerabilities, there remain notable research and methodology gaps, especially in technology scalability and the effectiveness of these methods. \u0000Unique Contribution to Theory, Policy, and Practice: This article posits a forward-looking perspective on automated code scanning, advocating for intelligent, collaborative, and integrated security measures in OSS. It emphasizes the indispensable role of community collaboration and open-source contributions in advancing these technologies, crucial for the proactive identification and mitigation of security vulnerabilities, thereby safeguarding the digital ecosystem's integrity and reliability.","PeriodicalId":503134,"journal":{"name":"International Journal of Computing and Engineering","volume":"131 2","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140223564","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Unveiling the AWS SAM Magic for Serverless Restful APIs: Architecting with ALB Path-Based Routing in AWS 揭开 AWS SAM 在无服务器有源 API 方面的神奇面纱：在 AWS 中使用基于 ALB 路径的路由进行架构设计

International Journal of Computing and Engineering Pub Date : 2024-03-20 DOI: 10.47941/ijce.1734

Balasubrahmanya Balakrishna

{"title":"Unveiling the AWS SAM Magic for Serverless Restful APIs: Architecting with ALB Path-Based Routing in AWS","authors":"Balasubrahmanya Balakrishna","doi":"10.47941/ijce.1734","DOIUrl":"https://doi.org/10.47941/ijce.1734","url":null,"abstract":"Purpose: This paper provides a thorough roadmap for developers, architects, and cloud enthusiasts who want to use the AWS Serverless Application Model (AWS SAM) to create a REST API and use the power of serverless computing. To handle HTTP requests effectively, the article focuses on deploying the API behind an Application Load Balancer (ALB) using path-based routing. The hands-on approach offers detailed instructions and valuable insights on planning, creating, and implementing serverless REST APIs. The focus is on the details of AWS SAM, examining its benefits and complexities. The paper makes the procedure easier to understand by providing thorough code excerpts, explanations, and pictures. \u0000Methodology: The methodology covers local testing using the SAM CLI, allowing developers to validate the API's functionality before deployment. \u0000Findings: The process also includes local testing with the SAM CLI, which enables developers to confirm the functioning of the API before deployment. To target the Lambda function, this paper will discuss AWS Lambda behind an ALB using a path-based listener rule on the ALB. The article’s conclusions cover essential topics like path-based routing, ALB integration, AWS SAM template structure, and recommended security and performance optimization practices. \u0000Unique Contributor to Theory, Policy and Practice: Based on these findings, recommendations offer information on optimizing templates, ensuring secure deployment, and using local testing to speed up development. Finally, the article walks readers through deploying the built API to AWS via the SAM CLI, facilitating a seamless transfer from a local development environment to an environment in production. Ultimately, this paper provides readers with the know-how and abilities to successfully negotiate AWS SAM's complexities and build reliable serverless REST APIs.","PeriodicalId":503134,"journal":{"name":"International Journal of Computing and Engineering","volume":"8 18","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140227479","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Decoding Lambda API Architectures: Analyzing Monolithic Lambda Functions Versus Fine-Grained Single-Purpose Functions 解码 Lambda API 架构：分析单片式 Lambda 函数与细粒度的单用途函数

International Journal of Computing and Engineering Pub Date : 2023-12-31 DOI: 10.47941/ijce.1596

Balasubrahmanya Balakrishna

{"title":"Decoding Lambda API Architectures: Analyzing Monolithic Lambda Functions Versus Fine-Grained Single-Purpose Functions","authors":"Balasubrahmanya Balakrishna","doi":"10.47941/ijce.1596","DOIUrl":"https://doi.org/10.47941/ijce.1596","url":null,"abstract":"Purpose: With an emphasis on AWS Lambda specifically, this technical paper explores the trade-offs and architectural considerations between monolithic and single-purpose functions in server less computing systems. Methodology: By examining the effects of using either a monolithic approach or a precisely calibrated, single-purpose function design, we hope to empower developers and architects. We investigate in-depth aspects, including resource usage, application monitoring, scalability, and performance. The approach strongly emphasizes a thorough examination of AWS Lambda's architectural issues, including the methods and resources utilized to produce insightful results. Findings: The results emphasize carefully investigating server less computing's scalability, performance, and resource use, especially regarding single- and monolithic-purpose function architectures. These observations provide concise factors to take into account when developing server less applications. Unique contributor to theory, policy and practice: The last section provides actionable insights to help developers of server less applications make well-informed decisions by condensing knowledge into useful suggestions for maximizing system responsiveness and resource management. The author, coming from an AWS background, is committed to using these technologies to express the concept throughout.","PeriodicalId":503134,"journal":{"name":"International Journal of Computing and Engineering","volume":" 1135","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139136289","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Artificial Intelligence and Energy Efficiency of 5G Radio Access Network 人工智能与 5G 无线接入网的能效

International Journal of Computing and Engineering Pub Date : 2023-12-31 DOI: 10.47941/ijce.1595

Omkar Ghag

{"title":"Artificial Intelligence and Energy Efficiency of 5G Radio Access Network","authors":"Omkar Ghag","doi":"10.47941/ijce.1595","DOIUrl":"https://doi.org/10.47941/ijce.1595","url":null,"abstract":"Purpose: This paper is a pioneering study that investigates the integration of Artificial Intelligence (AI) to enhance energy efficiency in 5G Radio Access Networks (RANs). This paper aims to identify AI-driven strategies that can significantly optimize energy consumption in the rapidly evolving 5G network infrastructure, which is essential for meeting the increasing demand for high-speed connectivity. Methodology: The methodology used for this research is a detailed review and analysis of the 5G RAN architecture and its energy dynamics, alongside the exploration of AI applications in optimizing network operations. The study focuses on AI techniques such as resource allocation, traffic prediction, adaptive sleep modes, and fault detection, proposing a holistic approach to energy management in 5G networks. A key contribution of this research is its in-depth examination of AI's role in 5G energy efficiency, highlighting its practical implications and potential for future applications. The paper offers novel insights into the implementation of AI in real-world 5G scenarios and addresses the challenges in transitioning from theoretical models to practical solutions. Findings: The findings reveal that AI integration is a vital step towards reducing the environmental footprint of 5G networks, with AI-based solutions showing promise in enhancing efficiency beyond the inherent capabilities of current 5G technologies. Despite many AI applications being in nascent stages, their potential impact on energy efficiency is significant. Unique contributor to theory, policy and practice: This paper is a valuable guide for researchers, industry professionals, and policymakers in telecommunications and environmental sustainability. It provides a clear roadmap for leveraging AI in 5G networks, emphasizing the synergy between technological innovation and ecological responsibility.","PeriodicalId":503134,"journal":{"name":"International Journal of Computing and Engineering","volume":"57 4","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139132313","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0