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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 endto-end deployment on Amazon cloud platform. Extensive experiments demonstrate the practicality of our system.

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This paper presents our research on secure and accurate targeted mobile coupon delivery. Our goal is to enable the secure delivery of targeted coupons to eligible users equipped with mobile devices, whose behavioral profiles accurately satisfy the targeting profile defined by the vendor. Our design well preserves user privacy, and further provides the strict security guarantee of vendor protection, by verifying user's eligibility for a coupon without revealing the vendor's targeting profile. We first show a basic approach which can effectively address the challenges posed by secure and accurate targeted coupon delivery, via properly leveraging Yao's garbled circuits. In order to achieve practical performance for resource-limited mobile devices, we then present our proposed design, which imposes lightweight workload on the user side, via properly bridging together homomorphic encryption and Yao's garbled circuits. We implement a preliminary user-side prototype and deploy it on an Android smartphone to evaluate the performance. Extensive experimental results demonstrate that our proposed design achieves practical performance for mobile devices.INDEX TERMS Targeted coupon delivery, user privacy, vendor protection, mobile, behavioral targeting.