[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-31223":3,"doc-seo-31223":27},{"code":4,"msg":5,"data":6},0,"success",{"doc_id":7,"user_id":8,"nickname":9,"user_avatar":10,"doc_module":4,"category_id":11,"category_name":12,"doc_title":13,"doc_description":14,"file_id":15,"file_url":16,"file_type":17,"file_size":18,"view_count":4,"is_deleted":4,"is_public":19,"is_downloadable":19,"audit_status":19,"page_count":20,"language":21,"language_code":22,"table_of_contents":23,"faqs":24,"seo_title":13,"seo_description":14,"update_tm":25,"read_time":26},31223,16904993612988,"Olivia Brown","https://ap-avatar.wpscdn.com/davatar_a8503ba1806abce46bf441b54a3ca4cd",8,"Research & Report","PILLAR: LINDDUN Privacy Threat Modeling using LLMs","The evolution of Large Language Models (LLMs) increases both opportunities and the need for rigorous privacy engineering. Privacy threat modeling frameworks such as LINDDUN help uncover risks, but they often demand substantial manual effort, expert knowledge, and detailed system information, slowing adoption and increasing oversight. PILLAR (Privacy risk Identification with LINDDUN and LLM Analysis Report) automates LINDDUN via LLM integration: it generates data flow diagrams from unstructured text, elicits threats, and prioritizes them based on risk. It also simulates multi-agent collaboration to improve coverage and relevance.","cbCaiimwW4MJ4aRA","https://ap.wps.com/l/cbCaiimwW4MJ4aRA","pdf",198119,1,9,"English","en","# Introduction\n## Motivation and challenges\n## PILLAR approach and innovations","[{\"question\":\"How does PILLAR handle multi-stakeholder perspectives during threat modeling?\",\"answer\":\"PILLAR simulates multi-agent collaboration by running multiple LLM instances as virtual experts with different contributor roles. Agents communicate and debate risks across multiple rounds to improve coverage of critical issues.\"}]",1779224450,23,{"code":4,"msg":28,"data":29},"ok",{"site_id":30,"language":22,"slug":31,"title":13,"keywords":32,"description":14,"schema_data":33,"social_meta":76,"head_meta":78,"extra_data":80,"updated_unix":25},105,"pillar-linddun-privacy-threat-modeling-using-llms","",{"@graph":34,"@context":75},[35,52,66],{"@type":36,"itemListElement":37},"BreadcrumbList",[38,42,46,49],{"item":39,"name":40,"@type":41,"position":19},"https://docshare.wps.com","Home","ListItem",{"item":43,"name":44,"@type":41,"position":45},"https://docshare.wps.com/document/","Document",2,{"item":47,"name":12,"@type":41,"position":48},"https://docshare.wps.com/document/research-report/",3,{"item":50,"name":13,"@type":41,"position":51},"https://docshare.wps.com/document/pillar-linddun-privacy-threat-modeling-using-llms/31223/",4,{"url":50,"name":13,"@type":53,"author":54,"headline":13,"publisher":56,"fileFormat":59,"description":14,"dateModified":60,"datePublished":60,"encodingFormat":59,"isAccessibleForFree":61,"interactionStatistic":62},"DigitalDocument",{"name":9,"@type":55},"Person",{"url":39,"name":57,"@type":58},"DocShare","Organization","application/pdf","2026-05-19",true,{"@type":63,"interactionType":64,"userInteractionCount":4},"InteractionCounter",{"@type":65},"ViewAction",{"@type":67,"mainEntity":68},"FAQPage",[69],{"name":70,"@type":71,"acceptedAnswer":72},"How does PILLAR handle multi-stakeholder perspectives during threat modeling?","Question",{"text":73,"@type":74},"PILLAR simulates multi-agent collaboration by running multiple LLM instances as virtual experts with different contributor roles. Agents communicate and debate risks across multiple rounds to improve coverage of critical issues.","Answer","https://schema.org",{"og:url":50,"og:type":77,"og:title":13,"og:site_name":57,"og:description":14},"article",{"robots":79,"canonical":50},"index,follow",{"doc_id":7,"site_id":30}]