{"id":168117,"date":"2013-11-01T00:00:00","date_gmt":"2013-11-01T00:00:00","guid":{"rendered":"https:\/\/www.microsoft.com\/en-us\/research\/msr-research-item\/verifying-computations-with-state\/"},"modified":"2018-10-16T20:08:30","modified_gmt":"2018-10-17T03:08:30","slug":"verifying-computations-with-state","status":"publish","type":"msr-research-item","link":"https:\/\/www.microsoft.com\/en-us\/research\/publication\/verifying-computations-with-state\/","title":{"rendered":"Verifying computations with state"},"content":{"rendered":"

When a client outsources a job to a third party (e.g., the
\ncloud), how can the client check the result, without reexecuting
\nthe computation? Recent work in proof-based
\nverifiable computation has made significant progress on
\nthis problem by incorporating deep results from complexity
\ntheory and cryptography into built systems. However,
\nthese systems work within a stateless model: they exclude
\ncomputations that interact with RAM or a disk, or for
\nwhich the client does not have the full input.
\nThis paper describes Pantry, a built system that overcomes
\nthese limitations. Pantry composes proof-based
\nverifiable computation with untrusted storage: the client
\nexpresses its computation in terms of digests that attest to
\nstate, and verifiably outsources that computation. Using
\nPantry, we extend verifiability to MapReduce jobs, simple
\ndatabase queries, and interactions with private state.
\nThus, Pantry takes another step toward practical proofbased
\nverifiable computation for realistic applications.<\/p>\n","protected":false},"excerpt":{"rendered":"

When a client outsources a job to a third party (e.g., the cloud), how can the client check the result, without reexecuting the computation? Recent work in proof-based verifiable computation has made significant progress on this problem by incorporating deep results from complexity theory and cryptography into built systems. However, these systems work within a […]<\/p>\n","protected":false},"featured_media":0,"template":"","meta":{"msr-url-field":"","msr-podcast-episode":"","msrModifiedDate":"","msrModifiedDateEnabled":false,"ep_exclude_from_search":false,"_classifai_error":"","footnotes":""},"msr-content-type":[3],"msr-research-highlight":[],"research-area":[13558,13547],"msr-publication-type":[193716],"msr-product-type":[],"msr-focus-area":[],"msr-platform":[],"msr-download-source":[],"msr-locale":[268875],"msr-post-option":[],"msr-field-of-study":[],"msr-conference":[],"msr-journal":[],"msr-impact-theme":[],"msr-pillar":[],"class_list":["post-168117","msr-research-item","type-msr-research-item","status-publish","hentry","msr-research-area-security-privacy-cryptography","msr-research-area-systems-and-networking","msr-locale-en_us"],"msr_publishername":"ACM - Association for Computing Machinery","msr_edition":"Symposium on Operating Systems Principles (SOSP)","msr_affiliation":"","msr_published_date":"2013-11-01","msr_host":"","msr_duration":"","msr_version":"","msr_speaker":"","msr_other_contributors":"","msr_booktitle":"","msr_pages_string":"","msr_chapter":"","msr_isbn":"","msr_journal":"","msr_volume":"","msr_number":"","msr_editors":"","msr_series":"","msr_issue":"","msr_organization":"","msr_how_published":"","msr_notes":"","msr_highlight_text":"","msr_release_tracker_id":"","msr_original_fields_of_study":"","msr_download_urls":"","msr_external_url":"","msr_secondary_video_url":"","msr_longbiography":"","msr_microsoftintellectualproperty":1,"msr_main_download":"205183","msr_publicationurl":"","msr_doi":"","msr_publication_uploader":[{"type":"file","title":"pantry-sosp13.pdf","viewUrl":"https:\/\/www.microsoft.com\/en-us\/research\/wp-content\/uploads\/2016\/02\/pantry-sosp13.pdf","id":205183,"label_id":0}],"msr_related_uploader":"","msr_attachments":[{"id":205183,"url":"https:\/\/www.microsoft.com\/en-us\/research\/wp-content\/uploads\/2016\/02\/pantry-sosp13.pdf"}],"msr-author-ordering":[{"type":"text","value":"Benjamin Braun","user_id":0,"rest_url":false},{"type":"text","value":"Ariel J. 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