A major threat to the peer-review systems of computer science conferences is the existence of "collusion rings" between reviewers. In such collusion rings, reviewers who have also submitted their own papers to the conference work together to manipulate the conference's paper assignment, with the aim of being assigned to review each other's papers. The most straightforward way that colluding reviewers can manipulate the paper assignment is by indicating their interest in each other's papers through strategic paper bidding. One potential approach to solve this important problem would be to detect the colluding reviewers from their manipulated bids, after which the conference can take appropriate action. While prior work has has developed effective techniques to detect other kinds of fraud, no research has yet established that detecting collusion rings is even possible. In this work, we tackle the question of whether it is feasible to detect collusion rings from the paper bidding. To answer this question, we conduct empirical analysis of two realistic conference bidding datasets, including evaluations of existing algorithms for fraud detection in other applications. We find that collusion rings can achieve considerable success at manipulating the paper assignment while remaining hidden from detection: for example, in one dataset, undetected colluders are able to achieve assignment to up to 30% of the papers authored by other colluders. In addition, when 10 colluders bid on all of each other's papers, no detection algorithm outputs a group of reviewers with more than 31% overlap with the true colluders. These results suggest that collusion cannot be effectively detected from the bidding, demonstrating the need to develop more complex detection algorithms that leverage additional metadata.

翻译：计算机科学会议同行评审系统面临的一大威胁是审稿人之间存在“共谋圈”。在此类共谋圈中，已向会议提交自身论文的审稿人通力合作操纵会议的论文分配，旨在被分配评审彼此的论文。共谋审稿人操纵论文分配最直接的方式是通过策略性投注表明对彼此论文的兴趣。解决这一重要问题的一种潜在方法是从被操纵的投注中检测共谋审稿人，随后会议可采取适当行动。尽管先前工作已开发出有效技术检测其他类型的欺诈行为，但尚无研究证明检测共谋圈的可能性。在本工作中，我们探讨从论文投注中检测共谋圈是否可行。为回答此问题，我们对两个真实的会议投注数据集进行实证分析，包括评估用于其他应用场景欺诈检测的现有算法。我们发现共谋圈能在成功操纵论文分配的同时隐藏自身不被察觉：例如，在一个数据集中，未被发现的共谋者最多可被分配评审其他共谋者所撰写的30%的论文。此外，当10名共谋者对所有彼此的论文进行投注时，没有任何检测算法输出的审稿人组与真实共谋者的重叠率超过31%。这些结果表明，从投注中无法有效检测共谋现象，凸显了开发利用额外元数据的更复杂检测算法的必要性。