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Designing an auction-based incentive mechanism is a widely adopted approach. However, platforms operating in the unrestricted Internet environment are inevitably vulnerable to various types of malicious behaviors. While most existing studies focus solely on countering a single type of malicious behaviors, their approaches often lead to a decline in task acceptance rates, ultimately impacting the system\u2019s utility. To address this challenge, we propose an incentive mechanism to resist multiple malicious user behaviors in a reverse auction, including monopoly and malicious competition. The PT-IM model is first introduced to identify and exclude monopolistic users through the calculation of tolerance price and user capability. Additionally, a novel task area division method is implemented within PT-IM to improve the task acceptance rate. Building on this foundation, we develop the enhanced model EPT-IM to further mitigate malicious competition among users through primary selection and secondary selection conditions. We conduct both theoretical and experimental analysis to evaluate EPT-IM. The results demonstrate that the proposed mechanism effectively resists malicious behaviors of users and surpasses other incentive mechanisms in terms of overall performance.<\/jats:p>","DOI":"10.1186\/s42400-025-00449-3","type":"journal-article","created":{"date-parts":[[2025,11,27]],"date-time":"2025-11-27T01:02:05Z","timestamp":1764205325000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Incentive mechanisms for crowdsensing: safeguarding against malicious behaviors"],"prefix":"10.1186","volume":"8","author":[{"given":"Haoran","family":"Yin","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3052-3828","authenticated-orcid":false,"given":"Jun","family":"Tao","sequence":"additional","affiliation":[]},{"given":"Dingwen","family":"Chi","sequence":"additional","affiliation":[]},{"given":"Yongji","family":"Chen","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2025,11,27]]},"reference":[{"issue":"8","key":"449_CR1","doi-asserted-by":"publisher","first-page":"2576","DOI":"10.1109\/TMC.2020.2987881","volume":"20","author":"Z Cai","year":"2020","unstructured":"Cai Z, Duan Z, Li W (2020) Exploiting multi-dimensional task diversity in distributed auctions for mobile crowdsensing. 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