{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/hastee-confidential-cloud-computing-and","title":"HasTEE+ : Confidential Cloud Computing and Analytics with Haskell","arxiv_id":"2401.08901","date":"2024-01-17","proceeding":null,"authors":["Abhiroop Sarkar","Alejandro Russo"],"abstract":"Confidential computing is a security paradigm that enables the protection of confidential code and data in a co-tenanted cloud deployment using specialized hardware isolation units called Trusted Execution Environments (TEEs). By integrating TEEs with a Remote Attestation protocol, confidential computing allows a third party to establish the integrity of an \\textit{enclave} hosted within an untrusted cloud. However, TEE solutions, such as Intel SGX and ARM TrustZone, offer low-level C/C++-based toolchains that are susceptible to inherent memory safety vulnerabilities and lack language constructs to monitor explicit and implicit information-flow leaks. Moreover, the toolchains involve complex multi-project hierarchies and the deployment of hand-written attestation protocols for verifying \\textit{enclave} integrity. We address the above with HasTEE+, a domain-specific language (DSL) embedded in Haskell that enables programming TEEs in a high-level language with strong type-safety. HasTEE+ assists in multi-tier cloud application development by (1) introducing a \\textit{tierless} programming model for expressing distributed client-server interactions as a single program, (2) integrating a general remote-attestation architecture that removes the necessity to write application-specific cross-cutting attestation code, and (3) employing a dynamic information flow control mechanism to prevent explicit as well as implicit data leaks. We demonstrate the practicality of HasTEE+ through a case study on confidential data analytics, presenting a data-sharing pattern applicable to mutually distrustful participants and providing overall performance metrics.","url_abs":"https://arxiv.org/abs/2401.08901v1","url_pdf":"https://arxiv.org/pdf/2401.08901v1.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"links_only","authors_date_abstract":"arXiv metadata, CC0 1.0 (https://info.arxiv.org/help/license), from the Kaggle arXiv metadata snapshot of 2026-09-12"},"code_links":[{"paper_slug":"hastee-confidential-cloud-computing-and","repo_url":"https://github.com/abhiroop/hastee","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"none","reach":{"status":"unanswered"}},{"paper_slug":"hastee-confidential-cloud-computing-and","repo_url":"https://github.com/abhiroop/enclaveifc","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":{"status":"unanswered"}}],"tasks":[],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}