[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"detail-sidebar-cat-0-en-105":3,"doc-seo-140968-105":59,"doc-detail-140968-en":125},{"code":4,"msg":5,"data":6},0,"success",[7,13,18,23,28,33,38,43,48,51,55],{"id":8,"doc_module":4,"doc_module_name":9,"category_name":10,"show_sort_weight":11,"slug":12},1,"Document","Story & Novel",90,"story-novel",{"id":14,"doc_module":4,"doc_module_name":9,"category_name":15,"show_sort_weight":16,"slug":17},2,"Literature",80,"literature",{"id":19,"doc_module":4,"doc_module_name":9,"category_name":20,"show_sort_weight":21,"slug":22},4,"Exam",70,"exam",{"id":24,"doc_module":4,"doc_module_name":9,"category_name":25,"show_sort_weight":26,"slug":27},5,"Comic",60,"comic",{"id":29,"doc_module":4,"doc_module_name":9,"category_name":30,"show_sort_weight":31,"slug":32},6,"Technology",50,"technology",{"id":34,"doc_module":4,"doc_module_name":9,"category_name":35,"show_sort_weight":36,"slug":37},7,"Healthcare",40,"healthcare",{"id":39,"doc_module":4,"doc_module_name":9,"category_name":40,"show_sort_weight":41,"slug":42},8,"Research & Report",30,"research-report",{"id":44,"doc_module":4,"doc_module_name":9,"category_name":45,"show_sort_weight":46,"slug":47},9,"Religion & Spirituality",20,"religion-spirituality",{"id":46,"doc_module":4,"doc_module_name":9,"category_name":49,"show_sort_weight":46,"slug":50},"World Cup","world-cup",{"id":52,"doc_module":4,"doc_module_name":9,"category_name":53,"show_sort_weight":52,"slug":54},10,"Lifestyle","lifestyle",{"id":56,"doc_module":4,"doc_module_name":9,"category_name":57,"show_sort_weight":24,"slug":58},19,"General","general",{"code":4,"msg":60,"data":61},"ok",{"site_id":62,"language":63,"slug":64,"title":65,"keywords":66,"description":67,"schema_data":68,"social_meta":118,"head_meta":120,"extra_data":122,"updated_unix":124},105,"en","author-obfuscation-attacking-the-state-of-the-art-in-authorship-verification","Author Obfuscation - Attacking the State of the Art in Authorship Verification","","We report the first large-scale evaluation of author obfuscation methods designed to attack authorship verification systems. Three obfuscators were tested against a total of 44 authorship verification approaches across multiple evaluation settings. The best obfuscator shifts verifier decisions in about 47% of cases, leading systems to misjudge document pairs as written by different authors. Submitted to a PAN 2016 shared task, the work also surveys the literature, organizes evaluation methodology, and introduces targeted performance measures for obfuscation impact.",{"@graph":69,"@context":117},[70,84,100],{"@type":71,"itemListElement":72},"BreadcrumbList",[73,77,79,82],{"item":74,"name":75,"@type":76,"position":8},"https://docshare.wps.com","Home","ListItem",{"item":78,"name":9,"@type":76,"position":14},"https://docshare.wps.com/document/",{"item":80,"name":40,"@type":76,"position":81},"https://docshare.wps.com/document/research-report/",3,{"item":83,"name":65,"@type":76,"position":19},"https://docshare.wps.com/document/author-obfuscation-attacking-the-state-of-the-art-in-authorship-verification/140968/",{"url":83,"name":65,"@type":85,"author":86,"headline":65,"publisher":89,"fileFormat":92,"inLanguage":63,"description":67,"dateModified":93,"datePublished":94,"encodingFormat":92,"isAccessibleForFree":95,"interactionStatistic":96},"DigitalDocument",{"name":87,"@type":88},"Finn","Person",{"url":74,"name":90,"@type":91},"DocShare","Organization","application/pdf","2026-09-09","2026-08-25",true,{"@type":97,"interactionType":98,"userInteractionCount":14},"InteractionCounter",{"@type":99},"ViewAction",{"@type":101,"mainEntity":102},"FAQPage",[103,109,113],{"name":104,"@type":105,"acceptedAnswer":106},"What does the paper evaluate about author obfuscation?","Question",{"text":107,"@type":108},"It presents the first large-scale evaluation of author obfuscation approaches that are built to attack authorship verification systems, measuring how different obfuscators affect verifier performance.","Answer",{"name":110,"@type":105,"acceptedAnswer":111},"How effective was the best-performing obfuscator?",{"text":112,"@type":108},"The best obfuscator impacts the decision-making process on average in about 47% of cases, causing authorship verifiers to misjudge document pairs.",{"name":114,"@type":105,"acceptedAnswer":115},"What tasks does the paper contrast and how are they related?",{"text":116,"@type":108},"It contrasts authorship verification (decide whether two documents share an author) with author masking (paraphrase so the author cannot be verified). The tasks are opposed in effectiveness requirements yet entangled in that advances in one can build on the other.","https://schema.org",{"og:url":83,"og:type":119,"og:title":65,"og:site_name":90,"og:description":67},"article",{"robots":121,"canonical":83},"index,follow",{"doc_id":123,"site_id":62},140968,1787646993,{"code":4,"msg":5,"data":126},{"doc_id":123,"user_id":127,"nickname":87,"user_avatar":128,"doc_module":4,"category_id":39,"category_name":40,"doc_title":65,"doc_description":67,"doc_content":129,"file_id":130,"file_url":131,"file_type":132,"file_size":133,"view_count":14,"is_deleted":4,"is_public":8,"is_downloadable":8,"audit_status":8,"page_count":134,"language":135,"language_code":63,"site_id":62,"html_lang":63,"table_of_contents":136,"faqs":137,"seo_title":138,"seo_description":67,"update_tm":124,"read_time":139},34359740700684,"https://ap-avatar.wpscdn.com/avatar/1f400023980c374ae676?_k=1777273430885731487","Author Obfuscation: Attacking the State of the Art  \nin Authorship Verification?  \nMartin Potthast, Matthias Hagen, and Benno Stein  \nBauhaus-Universität Weimar  \n\u003Cfirst name> . \u003Clast name>@[uni-weimar.de](uni-weimar.de)  \nAbstract We report on the first large-scale evaluation of author obfuscation approaches built to attack authorship verification approaches: the impact of 3 obfuscators on the performance of a total of 44 authorship verification approaches has been measured and analyzed. The best-performing obfuscator successfully impacts the decision-making process of the authorship verifiers on average in about 47% of the cases, causing them to misjudge a given pair of documents as having been written by “different authors” when in fact they would have decided otherwise if one of them had not been automatically obfuscated. The evaluated obfuscators have been submitted to a shared task on author obfuscation that we organized at the PAN 2016 lab on digital text forensics. We contribute further by surveying the literature on author obfuscation, by collecting and organizing evaluation methodology for this domain, and by introducing performance measures tailored to measuring the impact of author obfuscation on authorship verification.  \n1 Introduction  \nThe development of author identification technology has reached a point at which it can be carefully employed in the wild to resolve cases of unknown or disputed authorship. For a recent example, a state-of-the-art forensic software played a role in breaking the anonymity of J. K. Rowling, who published her book “The Cuckoo's Calling” under the pseudonym Robert Gailbraith in order to “liberate” herself from the pressure of stardom, caused by her success with the Harry Potter series.1 Moreover, forensic author identification software is part of the toolbox of forensic linguists, who employ the technology on a regular basis to support their testimony in court as expert witnesses in cases where the authenticity of a piece of writing is important. Despite their successful application, none of the existing approaches has been shown to work flawless—a fact that is rooted in the complexity and the ill-posedness of the problem. All approaches have a likelihood of returning false decisions under certain circumstances, but the circumstances under which they do are barely understood. It is hence particularly interesting to analyze whether and how these circumstances can be controlled, since any form of control over the outcome of an author identification software bears the risk of misuse.  \nIn fiction, a number of examples can be found where authors tried to remain anonymous, and where they, overtly or covertly, tried to imitate the writing style of others. In? A summary of this report has been published as part of [92]  \n1 [http://languagelog.ldc.upenn.edu/nll/?p=5315](http://languagelog.ldc.upenn.edu/nll/?p=5315)  \npublishes automatically obfuscated text   \nAlice    \nis known to have written  \ncircumvents  \nobstructs  \nautomatically verifies authorship  \nis received by  \nEve  \nFigure 1. Schematic view of the opposed tasks of author masking and authorship verification.  \nfact, style imitation is a well-known learning technique in writing courses. But the question of whether humans are ultimately capable of controlling their own writing style soas to fool experts into believing they have not written a given piece of text, or even that someone else has, is difficult to answer based on observation alone: are the known cases more or less all there is, or are they just the tip of the iceberg (i.e., examples of unskilled attempts)? And, if the “expert” to be fooled is not a human but an author identification software, the rules are changed entirely. The fact that software is used to assist author identification increases the attack surface of investigations to spoil the decision-making process of the software. This is troublesome since the human operator of such a software may be ignorant of its flaws, and biase","cbCaimlVhO5PludQ","https://ap.wps.com/l/cbCaimlVhO5PludQ","pdf",594513,34,"English","# Introduction\n## Authorship identification and real-world usage\n## Author masking vs. authorship verification\n## Research contributions and evaluation scope","[{\"question\":\"What does the paper evaluate about author obfuscation?\",\"answer\":\"It presents the first large-scale evaluation of author obfuscation approaches that are built to attack authorship verification systems, measuring how different obfuscators affect verifier performance.\"},{\"question\":\"How effective was the best-performing obfuscator?\",\"answer\":\"The best obfuscator impacts the decision-making process on average in about 47% of cases, causing authorship verifiers to misjudge document pairs.\"},{\"question\":\"What tasks does the paper contrast and how are they related?\",\"answer\":\"It contrasts authorship verification (decide whether two documents share an author) with author masking (paraphrase so the author cannot be verified). The tasks are opposed in effectiveness requirements yet entangled in that advances in one can build on the other.\"}]","Author Obfuscation - Attacking the State of the Art in Authorship Verification | PDF",86]