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Inf. Syst."],"published-print":{"date-parts":[[2026,2,28]]},"abstract":"<jats:p>Graph Contrastive Learning (GCL) has demonstrated substantial promise in enhancing the robustness and generalization of recommender systems, particularly by enabling models to leverage large-scale unlabeled data for improved representation learning. However, in this article, we reveal an unexpected vulnerability: the integration of GCL inadvertently increases the susceptibility of a recommender to targeted promotion attacks. Through both theoretical investigation and empirical validation, we identify the root cause as the spectral smoothing effect induced by contrastive optimization, which disperses item embeddings across the representation space and unintentionally enhances the exposure of target items. Building on this insight, we introduce a bi-level optimization attack method, named graph Contrastive Learning Recommendation Attack (CLeaR), which deliberately amplifies spectral smoothness and enables a systematic investigation of the susceptibility of GCL-based recommendation models to targeted promotion attacks. Our findings highlight the urgent need for robust countermeasures; in response, we further propose a Spectral-Irregularity Mitigation framework, named SIM, which accurately detects and suppresses targeted items without compromising model performance. Extensive experiments on multiple benchmark datasets demonstrate that, compared to existing targeted promotion attacks, GCL-based recommendation models exhibit greater susceptibility when evaluated with CLeaR, while SIM effectively mitigates these vulnerabilities.<\/jats:p>","DOI":"10.1145\/3779448","type":"journal-article","created":{"date-parts":[[2025,12,9]],"date-time":"2025-12-09T16:17:25Z","timestamp":1765297045000},"page":"1-30","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":5,"title":["When Graph Contrastive Learning Backfires: Spectral Vulnerability and Defense in Recommendation"],"prefix":"10.1145","volume":"44","author":[{"ORCID":"https:\/\/orcid.org\/0009-0003-2606-9508","authenticated-orcid":false,"given":"Zongwei","family":"Wang","sequence":"first","affiliation":[{"name":"Chongqing University, Chongqing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0127-7477","authenticated-orcid":false,"given":"Min","family":"Gao","sequence":"additional","affiliation":[{"name":"Key Laboratory of Dependable Service Computing in Cyber Physical Society, Ministry of Education, Chongqing University, Chongqing, China and School of Big Data &amp; Software Engineering, Chongqing University, Chongqing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3401-9829","authenticated-orcid":false,"given":"Junliang","family":"Yu","sequence":"additional","affiliation":[{"name":"The University of Queensland\u2014St Lucia Campus, Brisbane, Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6739-4145","authenticated-orcid":false,"given":"Shazia","family":"Sadiq","sequence":"additional","affiliation":[{"name":"The University of Queensland\u2014St Lucia Campus, Brisbane, Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1395-261X","authenticated-orcid":false,"given":"Hongzhi","family":"Yin","sequence":"additional","affiliation":[{"name":"The University of Queensland\u2014St Lucia Campus, Brisbane, Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4138-3082","authenticated-orcid":false,"given":"Ling","family":"Liu","sequence":"additional","affiliation":[{"name":"College of Computing, Georgia Institute of Technology, Atlanta, Georgia, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"320","published-online":{"date-parts":[[2026,1,9]]},"reference":[{"key":"e_1_3_2_2_2","doi-asserted-by":"crossref","first-page":"529","DOI":"10.1145\/3306618.3314309","volume-title":"Proceedings of the 2019 AAAI\/ACM Conference on AI, Ethics, and Society","author":"Abdollahpouri Himan","year":"2019","unstructured":"Himan Abdollahpouri. 2019. 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