移动支付安全理论模型及关键技术研究

With the rapid development of mobile payments and the sharply increasing user scales, mobile payment security has become one of the most important concerns of mobile users. Due to the coarse granularity authorization mechanism and the complicated environment of mobile payment systems, ensuring security and user experience, which are the two prerequisites of mobile payment, is facing various challenges. Specifically, the challenges include: (1) existing risk assessment models have narrow coverage and low accuracy over current mobile payment systems, due to various novel factors in mobile payment systems; (2) privacy leakage is commonplace in mobile computing environments, especially mobile Apps are over-collecting user data; (3) balancing security and usability is challenging.. Aiming at the above problems, this project investigates the systematic modeling and supporting techniques for mobile payment security. Specifically, this project will (1) construct security risk assessment model for mobile payments by combining extreme learning machine and fuzzy comprehensive evaluation technique; (2) study privacy-preserving cloud data access algorithms and intelligent optimization algorithms to promote the performance and usability of mobile payment systems; (3) investigate the best security strategies for mobile payment systems based on the dynamical programming approach. The proposed research in this project is expected to obtain theoretical underpinnings and practical assurance of mobile payment systems, which therefore can promote the sustainable development of mobile financial economy in the long run.

随着移动支付迅猛发展，用户规模急剧增加，移动支付安全成为中国网民最关心的问题之一。安全和便利是移动支付向前发展必须具备的两个前提条件，然而，由于移动操作系统的粗粒度授权机制、移动支付环境复杂等特性，导致移动支付面临较多挑战。主要的问题有：（1）移动支付安全涉及因素较多，现有的风险评估模型覆盖范围较窄、准确率较低；（2）隐私数据泄漏问题严重，尤其是来自应用程序的过量采集；（3）移动支付安全性和使用便利性之间的平衡难以解决。针对上述问题，本项目将深入探讨移动支付安全理论模型和关键技术，研究重点包括：（1）通过极限学习机和模糊综合评判方法构建移动支付风险评估模型；（2）基于移动云的隐私数据安全存取算法与智能优化算法，优化移动支付系统的性能及保障用户的使用便利性；（3）基于动态规划算法，研究移动支付最佳安全策略。本项目期望在理论研究和实际应用中取得创新成果，推动移动支付和移动互联网金融向前发展。

随着移动支付迅猛发展，用户规模急剧增加，移动支付安全成为中国网民最关心的问题之一。安全和便利是移动支付向前发展必须具备的两个前提条件，然而，由于移动操作系统的粗粒度授权机制、移动支付环境复杂等特性，导致移动支付面临较多挑战。主要的问题有：（1）移动支付安全涉及因素较多，现有的风险评估模型覆盖范围较窄、准确率较低；（2）隐私数据泄漏问题严重，尤其是来自应用程序的过量采集；（3）移动支付安全性和使用便利性之间的平衡难以解决。针对上述问题，本项目深入探讨了移动支付安全理论模型和关键技术，重点研究内容包括：（1）通过极限学习机和模糊综合评判方法构建移动支付风险评估模型；（2）基于移动云的隐私数据安全存取算法与智能优化算法，优化移动支付系统的性能及保障用户的使用便利性；（3）基于动态规划算法，研究移动支付最佳安全策略。在本项目的支持下，项目组设计了多个风险评估和用户反馈相关的模型，开发了一系列优化技术和相应的算法，并在学术期刊和会议上发表了54篇论文，这些成果可望推动移动支付和移动互联网金融向前发展。