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. Methodology: 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. Findings: 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. Unique 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.
{"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}
Purpose: Cloud computing has revolutionized the way organizations deploy and manage their IT infrastructure. However, as cloud adoption increases, so does the complexity of managing cloud costs. Methodology: AWS Spot Fleet offers a compelling way to optimize cloud expenses by leveraging unused computing capacity at a fraction of the standard price. Findings: This paper explores strategies for cloud cost optimization through AWS Spot Fleet utilization and effective cloud resource management. Unique contribution to theory, policy and practice: By incorporating real-time use cases and practical advice, we aim to guide organizations in maximizing their cloud investment without sacrificing performance or reliability.
目的：云计算彻底改变了企业部署和管理 IT 基础设施的方式。然而，随着云计算应用的增加，管理云计算成本的复杂性也随之增加。方法：AWS Spot Fleet 以标准价格的一小部分利用未使用的计算能力，为优化云计算成本提供了一种极具吸引力的方法。研究结果：本文探讨了通过利用 AWS Spot Fleet 和有效的云资源管理来优化云成本的策略。对理论、政策和实践的独特贡献：通过结合实时使用案例和实用建议，我们旨在指导企业在不牺牲性能或可靠性的前提下最大化云投资。
{"title":"Cloud Cost Optimization: Achieving Cost Savings through AWS Spot Fleet Utilization and Optimizing Cloud Resource Usage","authors":"Gowtham Mulpuri","doi":"10.47941/ijce.1742","DOIUrl":"https://doi.org/10.47941/ijce.1742","url":null,"abstract":"Purpose: Cloud computing has revolutionized the way organizations deploy and manage their IT infrastructure. However, as cloud adoption increases, so does the complexity of managing cloud costs. \u0000Methodology: AWS Spot Fleet offers a compelling way to optimize cloud expenses by leveraging unused computing capacity at a fraction of the standard price. \u0000Findings: This paper explores strategies for cloud cost optimization through AWS Spot Fleet utilization and effective cloud resource management. \u0000Unique contribution to theory, policy and practice: By incorporating real-time use cases and practical advice, we aim to guide organizations in maximizing their cloud investment without sacrificing performance or reliability.","PeriodicalId":503134,"journal":{"name":"International Journal of Computing and Engineering","volume":" 19","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140216504","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}
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. Methodology: 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. Findings: 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. Unique 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.
目的：本文旨在阐明开放源码软件（OSS）在数字基础设施中的变革作用以及随之而来的安全挑战。文章强调了对自动代码扫描技术的迫切需求，以解决因编码错误、缺乏安全编码实践和快速开发速度而产生的漏洞。方法：通过对静态、动态和交互式代码扫描方法的全面分析，以及对人工智能和 ML 集成的探索，本研究探讨了可扩展的高效方法，以增强开发生命周期早期的检测能力。研究结果虽然自动代码扫描技术在检测和缓解漏洞方面取得了长足进步，但在研究和方法论方面仍存在明显差距，尤其是在技术可扩展性和这些方法的有效性方面。对理论、政策和实践的独特贡献：本文对自动代码扫描提出了前瞻性的观点，倡导在开放源码软件中采取智能、协作和集成的安全措施。文章强调了社区合作和开源贡献在推进这些技术中不可或缺的作用，这对于主动识别和缓解安全漏洞至关重要，从而保障了数字生态系统的完整性和可靠性。
{"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}
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. Methodology: The methodology covers local testing using the SAM CLI, allowing developers to validate the API's functionality before deployment. Findings: 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. Unique 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.
目的：本文为希望使用 AWS 无服务器应用程序模型（AWS SAM）创建 REST API 并使用无服务器计算功能的开发人员、架构师和云计算爱好者提供了详尽的路线图。为了有效处理 HTTP 请求，文章重点介绍了如何使用基于路径的路由在应用负载平衡器 (ALB) 后面部署 API。实践方法提供了有关规划、创建和实施无服务器 REST API 的详细说明和宝贵见解。重点是 AWS SAM 的细节，研究其优点和复杂性。本文通过提供详尽的代码摘录、解释和图片，使程序更易于理解。方法论：该方法包括使用 SAM CLI 进行本地测试，使开发人员能够在部署前验证 API 的功能。结果：该过程还包括使用 SAM CLI 进行本地测试，使开发人员能够在部署前确认 API 的功能。针对 Lambda 功能，本文将讨论在 ALB 后面使用基于路径的 ALB 监听器规则的 AWS Lambda。文章的结论涵盖了基于路径的路由、ALB 集成、AWS SAM 模板结构以及推荐的安全和性能优化实践等基本主题。对理论、政策和实践的独特贡献： 基于这些发现，建议提供有关优化模板、确保安全部署以及使用本地测试加快开发速度的信息。最后，文章指导读者通过 SAM CLI 将构建的 API 部署到 AWS，从而促进从本地开发环境到生产环境的无缝转移。最终，本文为读者提供了成功应对 AWS SAM 的复杂性并构建可靠的无服务器 REST API 的诀窍和能力。
{"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}
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.
{"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}
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.
{"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}
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