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Appl."],"published-print":{"date-parts":[[2025,2,28]]},"abstract":"<jats:p>In pursuit of an immersive virtual experience within the Cyber-Physical Metaverse Systems (CPMS), the construction of Avatars often requires a significant amount of real-world data. Mobile Crowd Sensing (MCS) has emerged as an efficient method for collecting data for CPMS. While progress has been made in protecting the privacy of workers, little attention has been given to safeguarding task privacy, potentially exposing the intentions of applications and posing risks to the development of the Metaverse. Additionally, existing privacy protection schemes hinder the exchange of information among entities, inadvertently compromising the quality of the collected data. To this end, we propose a Quality-aware and Obfuscation-based Task Privacy-Preserving (QOTPP) scheme, which protects task privacy and enhances data quality without third-party involvement. The QOTPP scheme initially employs the insight of \u201cshowing the fake, and hiding the real\u201d by employing differential privacy techniques to create fake tasks and conceal genuine ones. Additionally, we introduce a two-tier truth discovery mechanism using Deep Matrix Factorization (DMF) to efficiently identify high-quality workers. Furthermore, we propose a Combinatorial Multi-Armed Bandit (CMAB)-based worker incentive and selection mechanism to improve the quality of data collection. Theoretical analysis confirms that our QOTPP scheme satisfies essential properties such as truthfulness, individual rationality, and \u03b5-differential privacy. Extensive simulation experiments validate the state-of-the-art performance achieved by QOTPP.<\/jats:p>","DOI":"10.1145\/3659582","type":"journal-article","created":{"date-parts":[[2024,4,16]],"date-time":"2024-04-16T15:51:30Z","timestamp":1713282690000},"page":"1-23","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":10,"title":["A Quality-Aware and Obfuscation-Based Data Collection Scheme for Cyber-Physical Metaverse Systems"],"prefix":"10.1145","volume":"21","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-4762-5943","authenticated-orcid":false,"given":"Jianheng","family":"Tang","sequence":"first","affiliation":[{"name":"Central South University, Changsha, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0236-759X","authenticated-orcid":false,"given":"Kejia","family":"Fan","sequence":"additional","affiliation":[{"name":"Central South University, Changsha, China"}]},{"ORCID":"https:\/\/orcid.org\/0009-0003-9831-1981","authenticated-orcid":false,"given":"Wenjie","family":"Yin","sequence":"additional","affiliation":[{"name":"Central South University, Changsha, China"}]},{"ORCID":"https:\/\/orcid.org\/0009-0000-1042-0269","authenticated-orcid":false,"given":"Shihao","family":"Yang","sequence":"additional","affiliation":[{"name":"Central South University, Changsha, China"}]},{"ORCID":"https:\/\/orcid.org\/0009-0006-5023-0738","authenticated-orcid":false,"given":"Yajiang","family":"Huang","sequence":"additional","affiliation":[{"name":"Central South University, Changsha, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5190-4761","authenticated-orcid":false,"given":"Anfeng","family":"Liu","sequence":"additional","affiliation":[{"name":"Central South University, Changsha, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0394-4635","authenticated-orcid":false,"given":"Naixue","family":"Xiong","sequence":"additional","affiliation":[{"name":"School of Computer Science, Sul Ross State University, Alpine, United States"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2788-3451","authenticated-orcid":false,"given":"Mianxiong","family":"Dong","sequence":"additional","affiliation":[{"name":"Muroran Institute of Technology, Muroran, Japan"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4819-621X","authenticated-orcid":false,"given":"Tian","family":"Wang","sequence":"additional","affiliation":[{"name":"Beijing Normal University-Hong Kong Baptist University United International College, Zhuhai, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7980-9651","authenticated-orcid":false,"given":"Shaobo","family":"Zhang","sequence":"additional","affiliation":[{"name":"Hunan University of Science and Technology, Xiangtan, China"}]}],"member":"320","published-online":{"date-parts":[[2024,12,24]]},"reference":[{"issue":"4","key":"e_1_3_1_2_2","first-page":"1893","article-title":"Towards private, robust, and verifiable crowdsensing systems via public blockchains","volume":"18","author":"Cai Chengjun","year":"2021","unstructured":"Chengjun Cai, Yifeng Zheng, Yuefeng Du, Zhan Qin, and Cong Wang. 2021. 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