Recently, generative AI has attracted much attention from both academic and industrial fields, which has shown its potential, especially in the data generation and synthesis aspects. Simultaneously, secure and privacy-preserving mobile crowdsensing (SPPMCS) has been widely applied in data collection/ acquirement due to an advantage on low deployment cost, flexible implementation, and high adaptability. Since generative AI can generate new synthetic data to replace the original data to be analyzed and processed, it can lower data attacks and privacy leakage risks for the original data. Therefore, integrating generative AI into SPPMCS is feasible and significant. Moreover, this paper investigates an integration of generative AI in SPPMCS, where we present potential research focuses, solutions, and case studies. Specifically, we firstly review the preliminaries for generative AI and SPPMCS, where their integration potential is presented. Then, we discuss research issues and solutions for generative AI-enabled SPPMCS, including security defense of malicious data injection, illegal authorization, malicious spectrum manipulation at the physical layer, and privacy protection on sensing data content, sensing terminals' identification and location. Next, we propose a framework for sensing data content protection with generative AI, and simulations results have clearly demonstrated the effectiveness of the proposed framework. Finally, we present major research directions for generative AI-enabled SPPMCS.

翻译：近年来，生成式人工智能在学术和工业领域引起了广泛关注，尤其在数据生成与合成方面展现出巨大潜力。与此同时，安全与隐私保护的移动群智感知（SPPMCS）因具有部署成本低、实现灵活、适应性高等优势，已在数据采集/获取中得到广泛应用。由于生成式AI可生成新的合成数据替代原始数据进行处理与分析，从而降低原始数据遭受攻击和隐私泄露的风险，因此将生成式AI集成到SPPMCS中具有可行性与重要意义。本文进一步探讨了生成式AI在SPPMCS中的融合方式，提出了潜在的研究重点、解决方案及案例研究。具体而言，我们首先综述了生成式AI与SPPMCS的基础知识，并阐明了二者的融合潜力；随后，讨论了生成式AI赋能SPPMCS的研究问题与解决方案，包括针对恶意数据注入的安全防御、非法授权防御、物理层恶意频谱操控防御，以及感知数据内容、感知终端身份与位置的隐私保护；接着，提出了基于生成式AI的感知数据内容保护框架，仿真结果清晰验证了该框架的有效性；最后，展望了生成式AI赋能SPPMCS的主要研究方向。