BEGIN:VCALENDAR
PRODID:-//AddEvent Inc//AddEvent.com v1.7//EN
VERSION:2.0
BEGIN:VTIMEZONE
TZID:America/Los_Angeles
BEGIN:STANDARD
DTSTART:20261101T010000
RRULE:FREQ=YEARLY;BYDAY=1SU;BYMONTH=11
TZOFFSETFROM:-0700
TZOFFSETTO:-0800
TZNAME:PST
END:STANDARD
BEGIN:DAYLIGHT
DTSTART:20260308T030000
RRULE:FREQ=YEARLY;BYDAY=2SU;BYMONTH=3
TZOFFSETFROM:-0800
TZOFFSETTO:-0700
TZNAME:PDT
END:DAYLIGHT
END:VTIMEZONE
BEGIN:VEVENT
DESCRIPTION:In recent years\, text generation techniques have greatly advanced\, especially in therealm of Large Language Models (LLMs)\, such as ChatGPT. These LLMs are able to generatetexts that are easily misconstrued as human-written. This\, therefore\, poses a security risk\, asthese LLMs can be used to generate disinformation at scale with little cost. Thus\, to combat thisnovel challenge\, two new computational problems emerge - (1) “Deepfake” AuthorshipAttribution (AA) and (2) “Deepfake” Authorship Obfuscation (AO) problems\, where the AAproblem is concerned with attributing the authorship of a given text to the true author\, whilethe AO problem is aims to circumvent accurate attribution of a given text by modifying parts ofthe text. Therefore\, in this talk\, the focus is to call attention to the serious security risk of LLMs\,and how these 2 computational problems propose solutions to mitigate this risk.\n\nPlace of work: MIT Lincoln LabBio: Dr. Adaku Uchendu is an AI Researcher at MIT Lincoln Lab. She earned her Ph.D.in Information Sciences and Technology at The Pennsylvania State University under theguidance of Dr. Dongwon Lee at the PIKE Lab in August 2023. While at Penn State\, she was aButton-Waller Fellow\, an NSF Scholarship for Service Scholar\, and an Alfred P. Sloan Scholar.Her dissertation\, titled “Reverse Turing Test in the Age of Deepfake Texts\,” focused onunderstanding and detecting AI-generated texts. She earned a B.S. in Mathematics\, with aminor in Statistics at University of Maryland Baltimore County (UMBC) in May 2018. While atUMBC\, she was a McNair scholar and a member of Pi Mu Epsilon (the Mathematical HonorarySociety). Uchendu’s research interests are in Artificial Intelligence\, Adversarial Robustness\, andTopological Data Analysis in the application domain of Cybersecurity.\n\n------\n\nPowered by addevent.com \nShare your next event with us!\n
X-ALT-DESC;FMTTYPE=text/html:In recent years, text generation techniques have greatly advanced, especially in therealm of Large Language Models (LLMs), such as ChatGPT. These LLMs are able to generatetexts that are easily misconstrued as human-written. This, therefore, poses a security risk, asthese LLMs can be used to generate disinformation at scale with little cost. Thus, to combat thisnovel challenge, two new computational problems emerge - (1) “Deepfake” AuthorshipAttribution (AA) and (2) “Deepfake” Authorship Obfuscation (AO) problems, where the AAproblem is concerned with attributing the authorship of a given text to the true author, whilethe AO problem is aims to circumvent accurate attribution of a given text by modifying parts ofthe text. Therefore, in this talk, the focus is to call attention to the serious security risk of LLMs,and how these 2 computational problems propose solutions to mitigate this risk.<br><br><strong>Place of work</strong>: MIT Lincoln Lab<strong>Bio</strong>: Dr. Adaku Uchendu is an AI Researcher at MIT Lincoln Lab. She earned her Ph.D.in Information Sciences and Technology at The Pennsylvania State University under theguidance of Dr. Dongwon Lee at the PIKE Lab in August 2023. While at Penn State, she was aButton-Waller Fellow, an NSF Scholarship for Service Scholar, and an Alfred P. Sloan Scholar.Her dissertation, titled “Reverse Turing Test in the Age of Deepfake Texts,” focused onunderstanding and detecting AI-generated texts. She earned a B.S. in Mathematics, with aminor in Statistics at University of Maryland Baltimore County (UMBC) in May 2018. While atUMBC, she was a McNair scholar and a member of Pi Mu Epsilon (the Mathematical HonorarySociety). Uchendu’s research interests are in Artificial Intelligence, Adversarial Robustness, andTopological Data Analysis in the application domain of Cybersecurity.<br /><br />------<br /><br />Powered by addevent.com <br>Share your next event with us!<br>
UID:19d539f4f80f4f58806bfdf3de501ce1addeventcom
SUMMARY:[C4AI] Dr. Adaku Uchendu - Attribution and Obfuscation of Deepfake Text Authorship
DTSTART;TZID=America/Los_Angeles:20240514T070000
DTEND;TZID=America/Los_Angeles:20240514T080000
DTSTAMP:20260808T060443Z
TRANSP:OPAQUE
STATUS:CONFIRMED
SEQUENCE:0
LOCATION:https://meet.google.com/rrj-sotc-yjt?authuser=0&hs=122
X-MICROSOFT-CDO-BUSYSTATUS:BUSY
BEGIN:VALARM
TRIGGER:-PT30M
ACTION:DISPLAY
DESCRIPTION:Reminder
END:VALARM
END:VEVENT
END:VCALENDAR