Spatial crowdsourcing (SC) has recently emerged as a new crowdsourcing service paradigm, where workers move physically to designated locations to perform tasks. Most SC systems perform task assignment based on the spatial proximity between task locations and worker locations. Under such a strategy, workers can only perform tasks near them, which may result in low social welfare (i.e., the total profit of the platform and workers). In contrast, the newly emerging strategy of competitive task assignment (CTA) stimulates workers to compete for their preferred tasks, allowing optimization of the overall profit of SC systems. Among others, one novel CTA setting is competitive detour tasking, which allows workers to compete for tasks that need them to make detours from their original travel paths. However, it requires collecting each worker’s bidding profile which may expose private information. In light of this, in this article, we design, implement, and evaluate PrivCO, a new system framework enabling privacy-preserving competitive detour tasking services in SC. PrivCO delicately bridges state-of-the-art competitive detour tasking algorithms with lightweight cryptography, providing strong protections for workers’ bidding profiles. Extensive experiments over real-world datasets demonstrate that while offering strong security guarantees, PrivCO achieves social welfare comparable to the plaintext domain.

With the prosperity of mobile application markets, mobile advertising is becoming an increasingly important economic force. In order to maximize revenue, ads are recommended to be delivered to potentially interested users, which requires user targeting, i.e., analyzing users' profiles and exploring users' interests. However, collecting user personal information for targeted mobile advertising services raises critical privacy concerns. Although some solutions like anonymization and obfuscation have been proposed for privacy-aware targeted advertising, they undesirably face the issues of security, efficiency, and/or ad relevance. In this paper, we propose a practical system enabling secure and efficient targeted mobile advertising services. It allows the ad network to perform accurate user targeting, while ensuring strong privacy protection for mobile users. Specifically, we show how to properly leverage a cryptographic primitive called private stream searching to support secure, accurate, and practical targeted mobile ad delivery. Moreover, we propose secure billing schemes to enable the ad network to charge advertisers in a privacy-preserving manner. The security strength of our system is thoroughly analyzed. Through extensive experiments, we show that our system achieves practical efficiency on mobile devices.

The explosive growth of multimedia contents, especially videos, is pushing forward the paradigm of cloud-based media hosting today. However, the wide attacking surface of the public cloud and the growing security awareness from the society are both calling for data encryption before outsourcing to cloud. Under the circumstance of encrypted videos, how to still preserve all the service benefits of cloud media center remains to be fully explored. In this paper, we present a secure system architecture design as our initial effort toward this direction, which bridges together the advancements of video coding techniques and secure deduplication. Our design enables the cloud with the crucial deduplication functionality to completely eliminate the extra storage and bandwidth cost, which would have been incurred by hosting encrypted videos from different entities. The design is also carefully tailored to the scalable video coding (SVC) techniques to support heterogeneous networks and devices for high-quality adaptive video dissemination. We show fully functional system implementations with structure-aware encryption design and structure-aware deduplication strategies that are both completely compliant with the video format in SVC. Extensive security analysis and experiments via our prototype deployed on Azure cloud platform show the practicality of the design. Our work can also be easily extended to support other media applications that employ media files with scalable structures.

Multimedia contents, especially videos, are being exponentially generated today. Due to the limited local storage, people are willing to store the videos at the remote cloud media center for its low cost and scalable storage. However, videos may have to be encrypted before outsourcing for privacy concerns. For practical purposes, the cloud media center should also provide the deduplication functionality to eliminate the storage and bandwidth redundancy, and adaptively disseminate videos to heterogeneous networks and different devices to ensure the quality of service. In light of the observations, we present a secure architecture enabling the encrypted cloud media center. It builds on top of latest advancements on secure deduplication and video coding techniques, with fully functional system implementations on encrypted video deduplication and adaptive video dissemination services. Specifically, to support efficient adaptive dissemination, we utilize the scalable video coding (SVC) techniques and propose a tailored layer-level secure deduplication strategy to be compatible with the internal structure of SVC. Accordingly, we adopt a structure-compatible encryption mechanism and optimize the way how encrypted SVC videos are stored for fast retrieval and efficient dissemination. We thoroughly analyze the security strength of our system design with strong video protection. Furthermore, we give a prototype implementation with encrypted end-to-end deployment on Amazon cloud platform. Extensive experiments demonstrate the practicality of our system.

Mobile advertising has become a key economic force with the growing mobile app markets. Targeted advertising has been attracting the attention of business and research communities because of its high return on investment. However, the fact that it requires continuous collection of user profiles raises severe privacy concerns. In this paper, we propose a secure and practical mobile advertising architecture, which aims to enable targeted advertising over encrypted mobile user profiles. The proposed idea is based upon a cryptographic primitive, i.e., private stream searching (PSS). We first propose a basic construction of secure targeted mobile advertising. Thorough analysis shows that our basic design achieves semantic security. After that, we introduce a number of techniques to make our design more efficient for mobile devices. Experimental results demonstrate the practicality of our proposed architecture.