Identity Theft in AI Conference Peer Review

TL;DR

This paper uncovers cases of identity theft in AI conference peer review, exposing how researchers exploit reviewer systems and proposing strategies to enhance security and integrity in academic evaluations.

Contribution

It reveals the mechanisms of identity theft in peer review and introduces new safeguards to prevent such fraudulent activities in academic publishing.

Findings

Identification of methods used for identity theft in peer review

Evidence of manipulation in AI conference paper evaluations

Proposed strategies to strengthen reviewer verification processes

Abstract

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.