CONFIDENTIAL COMPUTING ARCHITECTURES FOR SECURE BIOMEDICAL AND GOVERNMENT CLOUD ENVIRONMENTS
DOI:
https://doi.org/10.15680/d1csfq97Keywords:
Confidential Computing, Trusted Execution Environments (TEE), Secure Enclaves, Cloud Security, Biomedical Data Protection, Government Cloud, Data Privacy, Secure Data Processing, Memory Encryption, Remote Attestation, Confidential AI, Zero Trust Architecture, Hybrid Cloud Security, Regulatory Compliance, Privacy-Preserving ComputingAbstract
Confidential computing has emerged as a transformative paradigm for protecting sensitive data in use, addressing long-standing security gaps in traditional cloud computing models. As biomedical and government systems increasingly migrate to cloud environments, ensuring the confidentiality, integrity, and privacy of highly sensitive data—such as patient health records, genomic datasets, and classified public sector information—has become a critical concern. Conventional encryption techniques safeguard data at rest and in transit; however, data processed in memory remains vulnerable to sophisticated threats, including insider attacks and compromised system software.
This paper explores the architectural foundations and implementation strategies of confidential computing in secure cloud environments, with a focus on biomedical and government use cases. It examines hardware-based Trusted Execution Environments (TEEs), secure enclave technologies, memory encryption mechanisms, and attestation protocols that collectively enable secure data processing without exposing plaintext information. The study further analyzes integration patterns with modern cloud-native architectures, including containerized workloads, microservices, and hybrid cloud deployments.
Additionally, the paper highlights regulatory and compliance considerations, such as data sovereignty, privacy laws, and security standards, which are particularly critical in healthcare and public sector domains. Performance trade-offs, scalability challenges, and interoperability concerns are also discussed, along with emerging innovations such as confidential AI and privacy-preserving data analytics. organizations to unlock the full potential of cloud technologies while maintaining strict data protection guarantees.
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