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The uneven distribution of tasks and workers has led to recent research on Cross-Platform Spatial Crowdsourcing (CPSC), aiming for a multi-win situation for platforms, workers, and task requesters. Previous studies on CPSC problems focused on task assignment and worker selection performance, overlooking the importance of privacy preservation. This article addresses the existing challenges of privacy preservation and service quality by formulating a Privacy-Preserving Cross-Platform Spatial Crowdsourcing (PP-CPSC) problem and proves it to be NP-hard. We propose an Evolutionary Differential Privacy (Evo-DP) approach to optimize PP-CPSC. Evo-DP\u2019s evolutionary framework enables efficient and flexible optimization of privacy budget allocation. Within Evo-DP, each solution to the privacy budget allocation is represented as an individual in the population. To approximate the optimal solution, three evolutionary operations\u2014mutation, crossover, and scaling\u2014are employed for population updates, along with a selection process. A hybrid population model is introduced to balance exploration and exploitation abilities. Experimental results demonstrate Evo-DP\u2019s superiority over previous strategies in terms of solution quality, convergence speed, and scalability.<\/jats:p>","DOI":"10.1145\/3803794","type":"journal-article","created":{"date-parts":[[2026,3,25]],"date-time":"2026-03-25T14:24:09Z","timestamp":1774448649000},"page":"1-24","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["Towards Evolutionary Differential Privacy in Cross-Platform Spatial Crowdsourcing"],"prefix":"10.1145","volume":"17","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-5955-6295","authenticated-orcid":false,"given":"Yong-Feng","family":"Ge","sequence":"first","affiliation":[{"name":"Victoria University, Melbourne, Australia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8465-0996","authenticated-orcid":false,"given":"Hua","family":"Wang","sequence":"additional","affiliation":[{"name":"Victoria University, Melbourne, Australia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4029-7051","authenticated-orcid":false,"given":"Elisa","family":"Bertino","sequence":"additional","affiliation":[{"name":"Purdue University, West Lafayette, Indiana, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0221-6361","authenticated-orcid":false,"given":"Jinli","family":"Cao","sequence":"additional","affiliation":[{"name":"La Trobe University, Melbourne, Australia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5094-5980","authenticated-orcid":false,"given":"Yanchun","family":"Zhang","sequence":"additional","affiliation":[{"name":"Victoria University, Melbourne, Australia, Zhejiang Normal University, Jinhua, China, and Peng Cheng Laboratory, Shenzhen, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5271-9215","authenticated-orcid":false,"given":"Zhonglong","family":"Zheng","sequence":"additional","affiliation":[{"name":"Zhejiang Normal University, Jinhua, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2026,5,18]]},"reference":[{"key":"e_1_3_2_2_2","first-page":"222","volume-title":"Lecture Notes in Computer Science","volume":"11391","author":"Bkakria Anis","year":"2019","unstructured":"Anis Bkakria, Aimilia Tasidou, Nora Cuppens-Boulahia, Fr\u00e9d\u00e9ric Cuppens, Fatma Bouattour, and Feten Ben Fredj. 2019. 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