Secure and Real-Time Traceable Data Sharing in Cloud-Assisted IoT
Jintian Lu, Weilong Li, Jiakun Sun, Ruizhi Xiao, Bolin Liao
Abstract
Cloud-assisted Internet of Things (IoT) has become an increasingly popular paradigm to greatly improve the performance of IoT applications by delegating the cloud to manage the massive IoT data. How to achieve secure and real-time traceable data sharing (STDS) is crucial in this paradigm, especially, a large amount of sensitive data produced by IoT devices needs to be stored or accessed to/from the clouds. This article proposes an STDS scheme, which leverages the acrlong DIFC model to allow data owners to not only securely and efficiently share their data produced by IoT devices with data users but also have the capability of tracking the data users’ identity with nonrepudiation based on the hash chain technique. Subsequently, the acrlong HLPN, acrlong SMT-Lib, and Z3 solver are used to formally analyze and verify STDS based on acrlong BMC technique to prove the correctness and security STDS. The formal analysis results show that STDS fulfills its intended security goals. Finally, the performance evaluation results have demonstrated the efficiency of STDS.