Xie Qingqing, Wang Liangmin
School of Computer Science and Technology, Anhui University, Hefei 230601, China.
School of Computer Science and Communication Engineering, Jiangsu University, Zhenjiang 212013, China.
Sensors (Basel). 2016 Nov 25;16(12):1993. doi: 10.3390/s16121993.
With the wide use of mobile sensing application, more and more location-embedded data are collected and stored in mobile clouds, such as iCloud, Samsung cloud, etc. Using these data, the cloud service provider (CSP) can provide location-based service (LBS) for users. However, the mobile cloud is untrustworthy. The privacy concerns force the sensitive locations to be stored on the mobile cloud in an encrypted form. However, this brings a great challenge to utilize these data to provide efficient LBS. To solve this problem, we propose a privacy-preserving LBS scheme for mobile sensing data, based on the RSA (for Rivest, Shamir and Adleman) algorithm and ciphertext policy attribute-based encryption (CP-ABE) scheme. The mobile cloud can perform location distance computing and comparison efficiently for authorized users, without location privacy leakage. In the end, theoretical security analysis and experimental evaluation demonstrate that our scheme is secure against the chosen plaintext attack (CPA) and efficient enough for practical applications in terms of user side computation overhead.
随着移动感知应用的广泛使用，越来越多嵌入位置的数据被收集并存储在移动云中，如iCloud、三星云等。利用这些数据，云服务提供商（CSP）可以为用户提供基于位置的服务（LBS）。然而，移动云是不可信的。隐私问题迫使敏感位置以加密形式存储在移动云中。然而，这给利用这些数据提供高效的LBS带来了巨大挑战。为了解决这个问题，我们基于RSA（Rivest、Shamir和Adleman）算法和基于密文策略属性的加密（CP-ABE）方案，提出了一种针对移动感知数据的隐私保护LBS方案。移动云可以为授权用户高效地执行位置距离计算和比较，而不会泄露位置隐私。最后，理论安全分析和实验评估表明，我们的方案对选择明文攻击（CPA）是安全的，并且在用户端计算开销方面对于实际应用来说足够高效。
