Exploring Data Security and Compliance in SaaS Laboratory Management Systems

Authors

  • Vicrumnaug Vuppalapaty Technical Architect, CodeScience Inc. USA Author

Abstract

This study investigates records safety and compliance practices in SaaS laboratory control systems, focusing on encryption methods, get right of entry to controls, audit trails, and regulatory adherence. Through surveys and interviews with stakeholders, including laboratory managers and IT experts, the effectiveness of encryption methods along with AES, RSA, and TLS changed into assessed, yielding a mean score of eighty four %. Access controls, especially Role-Based Access Control (RBAC), were stated to be frequently reviewed and updated in eighty five% of companies. Confidence in audit trails was expressed with the aid of 72% of respondents, highlighting their importance in statistics security. While sixty five% of agencies reported compliance with HIPAA rules, adherence to GDPR requirements turned into lower, at forty two%. These findings underscore the important role of sturdy statistics security features and regulatory compliance in safeguarding touchy records within SaaS laboratory control structures. Recommendations include non-stop monitoring of security protocols, ordinary compliance audits, and workforce training on regulatory obligations to mitigate dangers and decorate records protection.

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References

A. Pena-Molina, M. L.-P. (2023). DATA PRIVACY AND SECURITY IN ONLINE LABORATORY MANAGEMENT SYSTEMS. INTED2023 Proceedings, 6459-6465.

Anandita Singh Thakur, P. K. (2015). Handling Data Integrity Issue in SaaS Cloud. Satapathy, S., Biswal, B., Udgata, S., Mandal, J. (eds) Proceedings of the 3rd International Conference on Frontiers of Intelligent Computing: Theory and Applications (FICTA) 2014. Advances in Intelligent Systems and Computing. Springer, Cham. https://doi.org/10.1007/978-3-319-12012-6_15.

Ansar Rafique, D. V. (2017). Leveraging NoSQL for Scalable and Dynamic Data Encryption in Multi-tenant SaaS. IEEE Trustcom/BigDataSE/ICESS, 885-892, doi: 10.1109/Trustcom/BigDataSE/ICESS.2017.327.

Cheng, S. (. (2024). Web 3.0 and SaaS Platform. In: Web 3.0: Concept, Content and Context. Springer, Singapore. , 147–163. https://doi.org/10.1007/978-981-99-6319-5_6.

Machireddy, Jeshwanth Reddy, Sareen Kumar Rachakatla, and Prabu Ravichandran. "Leveraging AI and Machine Learning for Data-Driven Business Strategy: A Comprehensive Framework for Analytics Integration." African Journal of Artificial Intelligence and Sustainable Development 1.2 (2021): 12-150.

Joel Bennett, R. S. (2024). Autonomic Computing in Total Achievement of Quality. Contribution to conference, https://www.iaria.org/conferences2024/ICAS24.html.

Krumm, N. (2023). Organizational and Technical Security Considerations for Laboratory Cloud Computing. The Journal of Applied Laboratory Medicine, 180–193, https://doi.org/10.1093/jalm/jfac118.

Muhammad Waseem, A. A. (2024). Containerization in Multi-Cloud Environment: Roles, Strategies, Challenges, and Solutions for Effective Implementation. 59, https://doi.org/10.48550/arXiv.2403.12980.

Machireddy, Jeshwanth Reddy, and Harini Devapatla. "Leveraging Robotic Process Automation (RPA) with AI and Machine Learning for Scalable Data Science Workflows in Cloud-Based Data Warehousing Environments." Australian Journal of Machine Learning Research & Applications 2.2 (2022): 234-261.

Phani Lanka, C. V. (2023). Strategies for a Startup Software-as-a-Service Organizations with Minimal Budget to Achieve Security and Compliance Goals. IEEE Xplore, 10.1109/ISDFS58141.2023.10131124.

Potla, Ravi Teja. "AI and Machine Learning for Enhancing Cybersecurity in Cloud-Based CRM Platforms." Australian Journal of Machine Learning Research & Applications 2.2 (2022): 287-302.

Regina Sousa, H. P. (2023). Implementing a Software-as-a-Service Strategy in Healthcare Workflows. Springer, Cham, https://doi.org/10.1007/978-3-031-38333-5_35.

Sara Aboukadri, A. O. (2024). Machine learning in identity and access management systems: Survey and deep dive. ELSEVIER, https://doi.org/10.1016/j.cose.2024.103729.

Sohr, K. (2008). Analyzing and Managing Role-Based Access Control Policies. IEEE Transactions on Knowledge and Data Engineering, 924-939.

Singh, Puneet. "Streamlining Telecom Customer Support with AI-Enhanced IVR and Chat." Journal of Artificial Intelligence Research and Applications 3.1 (2023): 443-479.

Wang, W. (2024). A Survey of Major Cybersecurity Compliance.

Y. S. Rajesh, V. G. (2024). A Unified Approach Toward Security Audit and Compliance in Cloud Computing. J. Inst. Eng. India Ser. B , https://doi.org/10.1007/s40031-024-01034-x.

Yunchuan Sun, J. Z. (2014). Data Security and Privacy in Cloud Computing. International Journal of Distributed Sensor Networks, https://doi.org/10.1155/2014/190903.

Zhang, R., Chen, D., Shang, X., Zhu, X., & Liu, K. (2018). "A Knowledge-Constrained Access Control Model for Protecting Patient Privacy in Hospital Information Systems,". IEEE Journal of Biomedical and Health Informatics, 904-911, doi: 10.1109/JBHI.2017.2696573.

Zheng, X. F. (2023). "Registered Data-Centered Lab Management System Based on Data Ownership Safety Architecture". Electronics, https://doi.org/10.3390/electronics12081817.

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Published

06-03-2024

How to Cite

[1]
V. Vuppalapaty, “Exploring Data Security and Compliance in SaaS Laboratory Management Systems”, Australian Journal of Machine Learning Research & Applications, vol. 4, no. 1, pp. 263–293, Mar. 2024, Accessed: Dec. 22, 2024. [Online]. Available: https://sydneyacademics.com/index.php/ajmlra/article/view/132