We present a new protocol for maliciously secure two-partycomputation based on cut-and-choose of garbled circuits using the recent idea of "forge-and-loose" which eliminates around a factor 3 of garbled circuits that needs to be constructed and evaluated. Our protocol introduces a new way to realize the "forge-and-loose" approach which avoids an auxiliary secure two-party computation protocol, does not rely on any number theoretic assumptions and parallelizes well in a same instruction, multiple data (SIMD) framework. With this approach we prove our protocol universally composable-secure against a malicious adversary assuming access to oblivious transfer, commitment and coin-tossing functionalities in the random oracle model. Finally, we construct, and benchmark, a SIMD implementation of this protocol using a GPU as a massive SIMD device. The findings compare favorably with all previous implementations of maliciously secure, two-party computation.<\/p>\n","protected":false},"excerpt":{"rendered":"
We present a new protocol for maliciously secure two-partycomputation based on cut-and-choose of garbled circuits using the recent idea of "forge-and-loose" which eliminates around a factor 3 of garbled circuits that needs to be constructed and evaluated. Our protocol introduces a new way to realize the "forge-and-loose" approach which avoids an auxiliary secure two-party computation […]<\/p>\n","protected":false},"author":351,"featured_media":0,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_jetpack_memberships_contains_paid_content":false,"footnotes":"","jetpack_publicize_message":"","jetpack_publicize_feature_enabled":true,"jetpack_social_post_already_shared":true,"jetpack_social_options":{"image_generator_settings":{"template":"highway","default_image_id":0,"font":"","enabled":false},"version":2}},"categories":[11,89,3,287],"tags":[1782,14,20,1394,1800],"class_list":["post-11933","post","type-post","status-publish","format-standard","hentry","category-computer-science","category-nvidia-cuda","category-paper","category-security","tag-computer-science","tag-cuda","tag-nvidia","tag-nvidia-geforce-gtx-670","tag-security"],"views":1937,"jetpack_publicize_connections":[],"jetpack_featured_media_url":"","jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/11933","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/users\/351"}],"replies":[{"embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=11933"}],"version-history":[{"count":0,"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/11933\/revisions"}],"wp:attachment":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=11933"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=11933"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=11933"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}