Video-analytics-as-a-service is becoming an important offering for cloud providers. A key concern in such services is privacy of the videos being analyzed. While trusted execution environments (TEEs) are promising options for preventing the direct leakage of private video content, they remain vulnerable to side-channel attacks. We present Visor, a system that provides confidentiality for the user\u2019s video stream as well as the ML models in the presence of a compromised cloud platform and untrusted co-tenants. Visor executes video pipelines in a hybrid TEE that spans both the CPU and GPU. It protects the pipeline against side-channel attacks induced by data-dependent access patterns of video modules, and also addresses leakage in the CPU-GPU communication channel. Visor is up to 1000\u00d7 faster than na\u00efve oblivious solutions, and its overheads relative to a non-oblivious baseline are limited to 2\u00d7\u20136\u00d7.<\/p>\n","protected":false},"excerpt":{"rendered":"
Video-analytics-as-a-service is becoming an important offering for cloud providers. A key concern in such services is privacy of the videos being analyzed. While trusted execution environments (TEEs) are promising options for preventing the direct leakage of private video content, they remain vulnerable to side-channel attacks. We present Visor, a system that provides confidentiality for the […]<\/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":[246574],"research-area":[13562,13558,13547],"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-660741","msr-research-item","type-msr-research-item","status-publish","hentry","msr-research-highlight-award","msr-research-area-computer-vision","msr-research-area-security-privacy-cryptography","msr-research-area-systems-and-networking","msr-locale-en_us"],"msr_publishername":"","msr_edition":"","msr_affiliation":"","msr_published_date":"2020-8-12","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":"CSAW 2020 Applied Research Competition Award (Runner-up)","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":"","msr_publicationurl":"","msr_doi":"","msr_publication_uploader":[{"type":"file","viewUrl":"https:\/\/www.microsoft.com\/en-us\/research\/wp-content\/uploads\/2020\/05\/Visor-Privacy-Preserving-Video-Analytics-as-a-Cloud-Service.pdf","id":"668952","title":"visor-privacy-preserving-video-analytics-as-a-cloud-service-2","label_id":"243109","label":0}],"msr_related_uploader":[{"type":"url","viewUrl":"false","id":"false","title":"https:\/\/arxiv.org\/abs\/2006.09628","label_id":"243118","label":0}],"msr_attachments":[{"id":668952,"url":"https:\/\/www.microsoft.com\/en-us\/research\/wp-content\/uploads\/2020\/06\/Visor-Privacy-Preserving-Video-Analytics-as-a-Cloud-Service.pdf"}],"msr-author-ordering":[{"type":"text","value":"Rishabh Poddar","user_id":0,"rest_url":false},{"type":"user_nicename","value":"Ganesh Ananthanarayanan","user_id":31834,"rest_url":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/microsoft-research\/v1\/researchers?person=Ganesh Ananthanarayanan"},{"type":"user_nicename","value":"Srinath Setty","user_id":33709,"rest_url":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/microsoft-research\/v1\/researchers?person=Srinath Setty"},{"type":"user_nicename","value":"Stavros Volos","user_id":35437,"rest_url":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/microsoft-research\/v1\/researchers?person=Stavros Volos"},{"type":"text","value":"Raluca Ada Popa","user_id":0,"rest_url":false}],"msr_impact_theme":[],"msr_research_lab":[199561,199565],"msr_event":[],"msr_group":[144899,559983,761911],"msr_project":[923382,648207,382664],"publication":[],"video":[],"download":[],"msr_publication_type":"inproceedings","related_content":{"projects":[{"ID":923382,"post_title":"Project Venice","post_name":"venice","post_type":"msr-project","post_date":"2023-03-24 09:06:03","post_modified":"2025-02-19 05:23:43","post_status":"publish","permalink":"https:\/\/www.microsoft.com\/en-us\/research\/project\/venice\/","post_excerpt":"The goal of Project Venice is to provide strong end-to-end protection against software side-channel attacks, with confidential cloud computing as its main use case.","_links":{"self":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-project\/923382"}]}},{"ID":648207,"post_title":"Confidential AI","post_name":"confidential-ai","post_type":"msr-project","post_date":"2020-05-15 05:46:38","post_modified":"2023-02-15 01:10:13","post_status":"publish","permalink":"https:\/\/www.microsoft.com\/en-us\/research\/project\/confidential-ai\/","post_excerpt":"Our goal is to make Azure the most trustworthy cloud platform for AI. 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