[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-31371":3,"doc-seo-31371":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},31371,16904993612988,"Olivia Brown","https://ap-avatar.wpscdn.com/davatar_a8503ba1806abce46bf441b54a3ca4cd",8,"Research & Report","AIBFT: Artificial Intelligence Browser Forensic Toolkit","AIBFT (Artificial Intelligence Browser Forensic Toolkit) aims to increase both the accuracy and analysis speed of web browser forensics. The work unites digital forensics with artificial intelligence, providing a visually effective toolkit for forensic analysts and deploying a reliable AI model for classifying malicious code versus normal web pages with 99.8% accuracy. The paper reviews prior browser-forensic approaches, motivates limitations of manual and deobfuscation-based workflows, then presents its methodology, tool demonstration, and future directions.","cbCaipxOKjQXmvEt","https://ap.wps.com/l/cbCaipxOKjQXmvEt","pdf",680759,1,11,"English","en","# Introduction\n# Literature Review\n## Pattern-based malicious web page detection\n## Behavior-based malicious web page detection\n## Machine learning-based malicious webpage detection\n# Methodology\n# Toolkit Demonstration\n# Discussion and Future Work\n# Conclusion","[{\"question\":\"What problem does AIBFT address in browser forensics?\",\"answer\":\"AIBFT targets the difficulty and time cost of manually analyzing large numbers of visited pages, especially obfuscated malicious pages such as exploit-kit content that are hard to inspect directly.\"},{\"question\":\"How does AIBFT combine digital forensics and artificial intelligence?\",\"answer\":\"The approach merges digital forensics concepts with AI to build a visually effective toolkit and to implement an AI model that classifies malicious code and normal web pages.\"},{\"question\":\"What detection strategies are reviewed before presenting the proposed method?\",\"answer\":\"The paper reviews pattern-based detection, behavior-based detection using emulation, and machine learning/deep learning approaches for detecting malicious webpages, highlighting trade-offs in accuracy and speed.\"}]",1779397254,28,{"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":84,"head_meta":86,"extra_data":88,"updated_unix":25},105,"aibft-artificial-intelligence-browser-forensic-toolkit","",{"@graph":34,"@context":83},[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/aibft-artificial-intelligence-browser-forensic-toolkit/31371/",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","2026-05-21",true,{"@type":63,"interactionType":64,"userInteractionCount":4},"InteractionCounter",{"@type":65},"ViewAction",{"@type":67,"mainEntity":68},"FAQPage",[69,75,79],{"name":70,"@type":71,"acceptedAnswer":72},"What problem does AIBFT address in browser forensics?","Question",{"text":73,"@type":74},"AIBFT targets the difficulty and time cost of manually analyzing large numbers of visited pages, especially obfuscated malicious pages such as exploit-kit content that are hard to inspect directly.","Answer",{"name":76,"@type":71,"acceptedAnswer":77},"How does AIBFT combine digital forensics and artificial intelligence?",{"text":78,"@type":74},"The approach merges digital forensics concepts with AI to build a visually effective toolkit and to implement an AI model that classifies malicious code and normal web pages.",{"name":80,"@type":71,"acceptedAnswer":81},"What detection strategies are reviewed before presenting the proposed method?",{"text":82,"@type":74},"The paper reviews pattern-based detection, behavior-based detection using emulation, and machine learning/deep learning approaches for detecting malicious webpages, highlighting trade-offs in accuracy and speed.","https://schema.org",{"og:url":50,"og:type":85,"og:title":13,"og:site_name":57,"og:description":14},"article",{"robots":87,"canonical":50},"index,follow",{"doc_id":7,"site_id":30}]