[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"detail-sidebar-cat-1-en-105":3,"doc-seo-243848-105":53,"doc-detail-243848-en":126},{"code":4,"msg":5,"data":6},0,"success",[7,14,19,24,29,34,39,44,49],{"id":8,"doc_module":9,"doc_module_name":10,"category_name":11,"show_sort_weight":12,"slug":13},11,1,"Template","Presentations",90,"presentations",{"id":15,"doc_module":9,"doc_module_name":10,"category_name":16,"show_sort_weight":17,"slug":18},12,"Resumes",80,"resumes",{"id":20,"doc_module":9,"doc_module_name":10,"category_name":21,"show_sort_weight":22,"slug":23},14,"Invoices",70,"invoices",{"id":25,"doc_module":9,"doc_module_name":10,"category_name":26,"show_sort_weight":27,"slug":28},15,"Posters",60,"posters",{"id":30,"doc_module":9,"doc_module_name":10,"category_name":31,"show_sort_weight":32,"slug":33},16,"Social Media",50,"social-media",{"id":35,"doc_module":9,"doc_module_name":10,"category_name":36,"show_sort_weight":37,"slug":38},17,"Forms",40,"forms",{"id":40,"doc_module":9,"doc_module_name":10,"category_name":41,"show_sort_weight":42,"slug":43},18,"Letters",30,"letters",{"id":45,"doc_module":9,"doc_module_name":10,"category_name":46,"show_sort_weight":47,"slug":48},21,"Paper Templates",5,"papers-templates",{"id":50,"doc_module":9,"doc_module_name":10,"category_name":51,"show_sort_weight":4,"slug":52},158,"General","general-158",{"code":4,"msg":54,"data":55},"ok",{"site_id":56,"language":57,"slug":58,"title":59,"keywords":60,"description":61,"schema_data":62,"social_meta":119,"head_meta":121,"extra_data":123,"updated_unix":125},105,"en","laconic-function-evaluation-functional-encryption-and-obfuscation-for-rams-with-sublinear-computation","Laconic Function Evaluation, Functional Encryption and Obfuscation for RAMs with Sublinear Computation","","This document details research on Laconic Function Evaluation (LFE), focusing on its application in Functional Encryption and Obfuscation for Random Access Machines (RAMs) with sublinear computation. The work analyzes LFE within the Common Reference String (CRS) model, where the CRS is hidden. A key aspect highlighted is that the digest of a computation C is significantly shorter than the computation itself, |C|. The evaluation process involves a process where C(x) is computed and the result is stored in a variable x, with the equation y ← Eval(pk, x) or y ← Enc(pk, x) being central. The security property ensures that the server learns nothing more than C(x). This system is compared to Fully Homomorphic Encryption (FHE), noting similarities in that the server performs computational work in a two-round two-party computation (2PC) scenario. The authors, Fangqi Dong from Tsinghua University, Zihan Hao from Tsinghua University, Ethan Mook from Northeastern University, and Daniel Wichs from Northeastern University & NTT Research, presented this work at Eurocrypt 2024.",{"@graph":63,"@context":118},[64,80,101],{"@type":65,"itemListElement":66},"BreadcrumbList",[67,71,74,77],{"item":68,"name":69,"@type":70,"position":9},"https://docshare.wps.com","Home","ListItem",{"item":72,"name":10,"@type":70,"position":73},"https://docshare.wps.com/template/",2,{"item":75,"name":51,"@type":70,"position":76},"https://docshare.wps.com/template/general/",3,{"item":78,"name":59,"@type":70,"position":79},"https://docshare.wps.com/template/laconic-function-evaluation-functional-encryption-and-obfuscation-for-rams-with-sublinear-computation/243848/",4,{"url":78,"name":59,"@type":81,"image":82,"author":87,"headline":59,"publisher":90,"fileFormat":93,"inLanguage":57,"description":61,"dateModified":94,"datePublished":95,"encodingFormat":93,"isAccessibleForFree":96,"interactionStatistic":97},"DigitalDocument",{"url":83,"@type":84,"width":85,"height":86},"https://docshare.wps.com/thumbnails/laconic-function-evaluation-functional-encryption-and-obfuscation-for-rams-with-sublinear-computation/243848.png","ImageObject",442,249,{"name":88,"@type":89},"Pentious","Person",{"url":68,"name":91,"@type":92},"DocShare","Organization","application/pdf","2026-09-22","2026-09-12",true,{"@type":98,"interactionType":99,"userInteractionCount":9},"InteractionCounter",{"@type":100},"ViewAction",{"@type":102,"mainEntity":103},"FAQPage",[104,110,114],{"name":105,"@type":106,"acceptedAnswer":107},"What is Laconic Function Evaluation (LFE)?","Question",{"text":108,"@type":109},"Laconic Function Evaluation (LFE) is a cryptographic technique that allows for computations where the digest of the computation is significantly shorter than the computation itself. It is studied within the Common Reference String (CRS) model.","Answer",{"name":111,"@type":106,"acceptedAnswer":112},"What is the security property of LFE in this context?",{"text":113,"@type":109},"The security property ensures that the server involved in the evaluation process learns nothing more than the result of the computation C(x).",{"name":115,"@type":106,"acceptedAnswer":116},"How does LFE compare to Fully Homomorphic Encryption (FHE)?",{"text":117,"@type":109},"LFE shares similarities with FHE, particularly in that the server performs computational work in a two-round two-party computation (2PC) scenario. In both, the server is responsible for the brunt of the computation.","https://schema.org",{"og:url":78,"og:type":120,"og:title":59,"og:site_name":91,"og:description":61},"article",{"robots":122,"canonical":78},"index,follow",{"doc_id":124,"site_id":56},243848,1790050790,{"code":4,"msg":5,"data":127},{"doc_id":124,"user_id":128,"nickname":88,"user_avatar":129,"doc_module":9,"category_id":50,"category_name":51,"doc_title":59,"doc_description":61,"doc_content":130,"file_id":131,"file_url":132,"file_type":133,"file_size":134,"view_count":76,"is_deleted":4,"is_public":9,"is_downloadable":9,"audit_status":9,"page_count":135,"language":136,"language_code":57,"site_id":56,"html_lang":57,"table_of_contents":137,"faqs":138,"seo_title":139,"seo_description":61,"update_tm":140,"read_time":141},1374404730887,"https://ap-avatar.wpscdn.com/davatar_6f874abed73319feea01a86fa6f0fab8","Laconic Function Evaluation, Functional Encryption and Obfuscation  for RAMs with Sublinear Computation   \nFangqi Dong  \nIIIS, Tsinghua University  \nZihan Hao  \nIIIS, Tsinghua University  \nEthan Mook  \nNortheastern University  \nDaniel Wichs  \nNortheastern University & NTT Research  \nEurocrypt 2024   \nLaconic Function Evaluation (LFE)  \nLaconic Function Evaluation (LFE)  \nC x  \nLaconic Function Evaluation (LFE)  \nC  \nx  \nLaconic Function Evaluation (LFE)  \n* in CRS model, CRS hidden  \nC x  \n􀀡􀀢􀀣 = 􀀤􀀥􀀦􀀧 (C)  \nLaconic Function Evaluation (LFE)  \n* in CRS model, CRS hidden  \nC  \ndigest very short compared to | C |  \nx  \n􀀡􀀢􀀣 = 􀀤􀀥􀀦􀀧 (C)  \nLaconic Function Evaluation (LFE)  \n* in CRS model, CRS hidden  \ndigest very short compared to | C |  \nC  x  \n􀀡􀀢􀀣 = 􀀤􀀥􀀦􀀧 (C)  \n􀀨􀀩 ← 􀀫􀀬􀀨(􀀡􀀢􀀣 , x)  \nLaconic Function Evaluation (LFE)  \n* in CRS model, CRS hidden  \ndigest very short compared to | C |  \nC  x  \n􀀭􀀮􀀨(C, 􀀨􀀩) = C (x)  \n􀀡􀀢􀀣 = 􀀤􀀥􀀦􀀧 (C)  \n􀀨􀀩  \n􀀨􀀩 ← 􀀫􀀬􀀨(􀀡􀀢􀀣 , x)  \nLaconic Function Evaluation (LFE)  \n* in CRS model, CRS hidden  \ndigest very short compared to | C |  \nC  x  \n􀀡􀀢􀀣 = 􀀤􀀥􀀦􀀧 (C)  \n􀀨􀀩  \n􀀨􀀩 ← 􀀫􀀬􀀨(􀀡􀀢􀀣 , x)  \n􀀭􀀮􀀨(C, 􀀨􀀩) = C (x)  \nSecurity: Server learns nothing more than C (x)   \nLaconic Function Evaluation (LFE)  \n* in CRS model, CRS hidden  \ndigest very short compared to | C |  \nC  x  \n􀀡􀀢􀀣 = 􀀤􀀥􀀦􀀧 (C)  \n􀀨􀀩  \n􀀨􀀩 ← 􀀫􀀬􀀨(􀀡􀀢􀀣 , x)  \n| 􀀭􀀮􀀨(C, 􀀨􀀩) = C (x)\u003Cbr>| \u003Cbr>\u003Cbr>\u003Cbr>Security: Server learns nothing more than C (x)\u003Cbr>|\n| --- | --- |\n|  Like FHE: 2-round 2PC where Server does the computational work \u003Cbr>|  |","cbCaibKNLOSbhbMY","https://ap.wps.com/l/cbCaibKNLOSbhbMY","pdf",1425519,89,"English","# Laconic Function Evaluation (LFE)\n## Security: Server learns nothing more than C (x)\n## Comparison to FHE: 2-round 2PC where Server does the computational work","[{\"question\":\"What is Laconic Function Evaluation (LFE)?\",\"answer\":\"Laconic Function Evaluation (LFE) is a cryptographic technique that allows for computations where the digest of the computation is significantly shorter than the computation itself. It is studied within the Common Reference String (CRS) model.\"},{\"question\":\"What is the security property of LFE in this context?\",\"answer\":\"The security property ensures that the server involved in the evaluation process learns nothing more than the result of the computation C(x).\"},{\"question\":\"How does LFE compare to Fully Homomorphic Encryption (FHE)?\",\"answer\":\"LFE shares similarities with FHE, particularly in that the server performs computational work in a two-round two-party computation (2PC) scenario. In both, the server is responsible for the brunt of the computation.\"}]","Laconic Function Evaluation, Functional Encryption and Obfuscation for RAMs with Sublinear Computation | PDF",1789209338,31]