Fine-Grained Task Access Control System for Mobile Crowdsensing

Abstract

Mobile crowdsensing enables people to collect and process a massive amount of information by using social resources without any cost on sensor deployment or model training. Many schemes focusing on the problems of task assignment and privacy preservation have been proposed so far. However, the privacy-preserving of requesters and task access control, which are vital to mobile crowdsensing, is barely considered in the literature. To address the aforementioned issues, a fine-grained task access control system for mobile crowdsensing is proposed. In particular, the requester can decide the group of task performers who can access the task by utilizing attribute-based encryption technology. T he untrusted crowdsensing platform cannot obtain any sensitive information concerning the requester or the task, while the qualified task performers are capable of retrieving tasks within 0.85 ms. Security analysis and experimental results are presented to show the feasibility and efficiency of the proposed system.

Privacy-Preserving Task Distribution Mechanism with Cloud-Edge IoT for the Mobile Crowdsensing

“…Focus on the efficiency improvement, Tang et al [33] indicated to alleviate the computational overheads of task encryption and decryption phase with online/offline encryption [34] and outsourced decryption [35] technology and designed to recommend the optimal task for task performers with the claimed "win-win" strategy. More recently, Wang et al [10] presented a fine-grained access control protocol for the mobile crowdsensing platform, which enables the lightweight keyword generation and search and specifies the crowdsensing platform to predecrypt the ciphertext to reduce the computational overheads of the task performer side. However, their proposal is insecure unless they assumed the crowdsensing platform to be fully trusted, since they direct deliver the performer's user secret key to the crowdsensing platform.…”

“…As a flexible crowdsensing strategy emphasizes open participation, participatory mobile crowdsensing enables the urban administrator to publish some "tasks" in the crowdsensing platform, and then, any resident owns a fair opportunity to bid for these tasks. In a more professional view, as illustrated in Figure 1 [10], the urban administrator acts as the requester, designs, and releases tasks to the crowdsensing platform.…”

“…Inspired by that, the latest research works put forward the solutions for the secure task distribution in mobile crowdsensing. However, there exist some gaps between these theoretically feasible solutions [10,22,24,26,36] and the practicality of mobile crowdsensing. Specifically, first, there is a practical issue that task performers have to locate their desired task among the stored ciphertext before downloading and decryption.…”

“…Although there are some ABE-based solutions [26] that support keyword search, they are also hard to be practically deployed on mobile crowdsensing platforms for their cumbersome search procedures. Secondly, existing solutions (such as [10,22]) are subject to heavy computational and storage overheads of the mobile terminal in the decryption side.…”

“…To alleviate the computational overheads of the resourceconstrained device on the task performer side, we delegate the decryption operation that should be assumed by the performer to the edge device in Scheme 2. Distinct from [10], in our solution, the edge device is considered to be semitrusted, which implies that we can prevent it from obtaining sensitive information including the user secret key.…”