Identity Theft in AI Conference Peer Review

Fuente: arXiv
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Auteurs principaux: Shah, Nihar B., Bok, Melisa, Liu, Xukun, McCallum, Andrew
Format: Preprint
Publié: 2025
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author Shah, Nihar B.
Bok, Melisa
Liu, Xukun
McCallum, Andrew
author_facet Shah, Nihar B.
Bok, Melisa
Liu, Xukun
McCallum, Andrew
contents We discuss newly uncovered cases of identity theft in the scientific peer-review process within artificial intelligence (AI) research, with broader implications for other academic procedures. We detail how dishonest researchers exploit the peer-review system by creating fraudulent reviewer profiles to manipulate paper evaluations, leveraging weaknesses in reviewer recruitment workflows and identity verification processes. The findings highlight the critical need for stronger safeguards against identity theft in peer review and academia at large, and to this end, we also propose mitigating strategies.
format Preprint
id arxiv_https___arxiv_org_abs_2508_04024
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Identity Theft in AI Conference Peer Review
Shah, Nihar B.
Bok, Melisa
Liu, Xukun
McCallum, Andrew
Digital Libraries
Artificial Intelligence
Cryptography and Security
We discuss newly uncovered cases of identity theft in the scientific peer-review process within artificial intelligence (AI) research, with broader implications for other academic procedures. We detail how dishonest researchers exploit the peer-review system by creating fraudulent reviewer profiles to manipulate paper evaluations, leveraging weaknesses in reviewer recruitment workflows and identity verification processes. The findings highlight the critical need for stronger safeguards against identity theft in peer review and academia at large, and to this end, we also propose mitigating strategies.
title Identity Theft in AI Conference Peer Review
topic Digital Libraries
Artificial Intelligence
Cryptography and Security
url https://arxiv.org/abs/2508.04024