Enhancing Data Security in Logistics Applications: A Scalable Microservices Approach |
||
 |
 |
|
| © 2025 by IJCTT Journal | ||
| Volume-73 Issue-4 |
||
| Year of Publication : 2025 | ||
| Authors : Rakesh Kumar Mali | ||
| DOI : 10.14445/22312803/IJCTT-V73I4P118 | ||
How to Cite?
Rakesh Kumar Mali, "Enhancing Data Security in Logistics Applications: A Scalable Microservices Approach," International Journal of Computer Trends and Technology, vol. 73, no. 4, pp. 126-134, 2025. Crossref, https://doi.org/10.14445/22312803/IJCTT-V73I4P118
Abstract
As logistics applications are increasingly crucial to the movement of goods and services, the importance of protecting that data cannot be overstated. Scalable microservices-based data security for logistics applications: in their decentralized nature, Microservices provide a perfect architecture for developing more secure, flexible, and resilient applications. This paper exposes the delivery applications’ typical delivery practices threats (e.g., unauthorized use, breach of data, and integrity of real-time transactional data). We suggest an architecture that enhances security by utilizing robust encryption methods, a token-based authentication process, and the distributed property of microservice-based applications to defend against potential dangers. The answer involves a layered approach to security that works at both the application and the network layers to enable granular access control, real-time protection for data in flight, and better auditability. Furthermore, we have also implemented an intelligent anomaly detection mechanism using machine learning models to detect security threats in a running environment. The results demonstrate a drastic improvement in the security posture of logistics applications, such as reduced susceptibility to common attack vectors, quicker detection of unauthorized activities, and improved user confidence. With scalability, the proposed solution grows together with changing needs, safeguarding logistics companies in the long run.
Keywords
Microservices, Data Security, Logistics Applications, Anomaly Detection, Scalable Architecture.
Reference
[1] Nicola Dragoni et al., Microservices: Yesterday, Today, and Tomorrow, Present and Ulterior Software Engineering, Springer, Cham, pp. 195-216, 2017.
[CrossRef] [Google Scholar] [Publisher Link]
[2] M. Šipek et al., “Enhancing Performance of Cloud-Based Software Applications with GraalVM and Quarkus,” 2020 43rd International Convention on Information, Communication and Electronic Technology, Opatija, Croatia, pp. 1746-1751, 2020.
[CrossRef] [Google Scholar] [Publisher Link]
[3] Fikri Aydemir, and Fatih Başçiftçi, "Building a Performance Efficient Core Banking System Based on the Microservices Architecture," Journal of Grid Computing, vol. 20, no. 4, 2022.
[CrossRef] [Google Scholar] [Publisher Link]
[4] Xiang Li et al., "Research on Real-Time Log Data Processing And Monitoring Scheme of Printing Equipment Based on Flink Framework," Proceedings of the 2022 6th International Conference on Electronic Information Technology and Computer Engineering, Xiamen China, pp. 1096-1100, 2023.
[CrossRef] [Google Scholar] [Publisher Link]
[5] Panagiotis Sotiropoulos, and Costas Vassilakis, "The Additional Testsuite Framework: Facilitating Software Testing and Test Management," International Journal of Web Engineering and Technology, vol. 17, no. 3, pp. 296-334, 2022.
[CrossRef] [Google Scholar] [Publisher Link]
[6] Noor Mohammed Noorani et al., "Factor Prioritization for Effectively Implementing DevOps in Software Development Organizations: A SWOT-AHP Approach," Axioms, vol. 11, no. 10, pp. 1-29, 2022.
[CrossRef] [Google Scholar] [Publisher Link]
[7] Eman Daraghmi, Cheng-Pu Zhang, and Shyan-Ming Yuan, "Enhancing Saga Pattern for Distributed Transactions within a Microservices Architecture," Applied Sciences, vol. 12, no. 12, pp. 1-24, 2022.
[CrossRef] [Google Scholar] [Publisher Link]
[8] Pethuru Raj, Skylab Vanga, and Akshita Chaudhary, Cloud-Native Computing: How to Design, Develop, and Secure Microservices and Event-Driven Applications, 1st ed., Wiley-IEEE Press, pp. 1-352, 2022.
[Google Scholar] [Publisher Link]
[9] Nathan Cruz Coulson, Stelios Sotiriadis, and Nik Bessis, “Adaptive Microservice Scaling for Elastic Applications,” IEEE Internet of Things Journal, vol. 7, no. 5, pp. 4195-4202, 2020.
[CrossRef] [Google Scholar] [Publisher Link]
[10] Yusuf Adedayo Lawal et al., “Enhancing Sustainability in Project Management through Smart Technology Integration: A Case Study Approach to Green Building Projects,” Dutch Journal of Finance and Management, vol. 7, no. 2, 2024.
[CrossRef] [Google Scholar] [Publisher Link]
[11] Adebayo Omowunmi Temitope, “Software Adoption in Project Management and Their Impact on Project Efficiency and Collaboration,” IRE Journals, vol. 3, no. 12, pp. 277-282, 2020.
[Google Scholar] [Publisher Link]
[12] Daniel Ajiga et al., “Methodologies for Developing Scalable Software Frameworks that Support Growing Business Needs,” vol. 6, no. 8, pp. 2661-2683, 2024.
[CrossRef] [Google Scholar] [Publisher Link]
[13] Grzegorz Blinowski, Anna Ojdowska, and Adam Przybyłek, “Monolithic vs. Microservice Architecture: A Performance and Scalability Evaluation,” IEEE Access, vol. 10, pp. 20357-20374, 2022.
[CrossRef] [Google Scholar] [Publisher Link]
[14] Arvind Chandaka, and Ovais Mehboob Ahmed Khan, Developing Microservices Architecture on Microsoft Azure with Open Source Technologies, Microsoft Press, 1st ed., pp. 1-304, 2021.
[Google Scholar] [Publisher Link]
[15] Shanshan Li et al., “Understanding and Addressing Quality Attributes of Microservices Architecture: A Systematic Literature Review,” Information and Software Technology, vol. 131, 2021.
[CrossRef] [Google Scholar] [Publisher Link]
[16] Cleber Santana et al., “Increasing the Availability of IoT Applications with Reactive Microservices,” Service Oriented Computing and Applications, vol. 15, pp. 109-126, 2021.
[CrossRef] [Google Scholar] [Publisher Link]
[17] Chouhan Kumar Rath, Amit Kr. Mandal, and Anirban Sarkar, “Microservice Based Scalable IoT Architecture for Device Interoperability,” Computer Standards & Interfaces, vol. 84, 2023.
[CrossRef] [Google Scholar] [Publisher Link]
[18] Atonu Ghosh, Anandarup Mukherjee, and Sudip Misra, “SEGA: Secured Edge Gateway Microservices Architecture for IIoT-Based Machine Monitoring,” IEEE Transactions on Industrial Informatics, vol. 18, no. 3, pp. 1949-1956, 2022.
[CrossRef] [Google Scholar] [Publisher Link]
[19] Safa Ben Atitallah, Maha Driss, and Henda Ben Ghézala, “Revolutionizing Disease Diagnosis: A Microservices-Based Architecture for Privacy-Preserving and Efficient IoT Data Analytics Using Federated Learning,” Procedia Computer Science, vol. 225, pp. 3322 3331, 2023.
[CrossRef] [Google Scholar] [Publisher Link]
[20] Kai Petersen, Sairam Vakkalanka, and Ludwik Kuzniarz, “Guidelines for Conducting Systematic Mapping Studies in Software Engineering: An Update,” Information and Software Technology, vol. 64, pp. 1-8, 2015.
[CrossRef] [Google Scholar] [Publisher Link]
[21] Claes Wohlin et al., Experimentation in Software Engineering, 2nd ed., Springer Berlin, Heidelberg, 2024.
[CrossRef] [Google Scholar] [Publisher Link]
[22] Badr El Khalyly et al., “A Comparative Study of Microservices-based IoT Platforms,” International Journal of Advanced Computer Science and Applications, vol. 11, no. 8, pp. 389-398, 2020.
[CrossRef] [Google Scholar] [Publisher Link]
[23] Claes Wohlin, “Guidelines for Snowballing in Systematic Literature Studies and a Replication in Software Engineering,” Proceedings of the 18th International Conference on Evaluation and Assessment in Software Engineering, London England United Kingdom, pp. 1-10, 2014.
[CrossRef] [Google Scholar] [Publisher Link]