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With the growing popularity of cloud storage, to guarantee the security of outsourced data becomes more and more important. In this paper, we make the first attempt to explore the intrinsic relationship between secure cloud storage and homomorphic encryption scheme, based on which we present a Generic way to design a Secure Cloud Storage protocol, denoted as G-SCS , using any homomorphic encryption scheme (HES). The proposed G-SCS is secure under a definition that satisfy the security requirement of cloud storage. To address various issues in real application scenarios, we further extend the protocol to support deterministic and randomized auditing, data dynamics (i.e., data insertion, deletion and modification), as well as third-party public auditing, while preserving the efficiency and security of the protocol. By instantiating all abstract semantics in G-SCS , we construct three concrete secure cloud storage protocols using RSA-based, Paillier-based and DGHV-based HESs, which are multiplicatively, additively and fully HESs, respectively. We conduct extensive theoretical analysis and experimental evaluations to validate the practicability of the proposed protocol.

The ever-increasing mobile video services and users’ demand for better video quality have boosted research into the video Quality-of-Experience. Recently, the concept of Quality-of-Experience has evolved to Quality-of-Engagement, a more actionable metric to evaluate users’ engagement to the video services and directly relate to the service providers’ revenue model. Existing works on user engagement mostly adopt uniform models to quantify the engagement level of all users, overlooking the essential distinction of individual users. In this paper, we first conduct a large-scale measurement study on a real-world data set to demonstrate the dramatic discrepancy in user engagement, which implies that a uniform model is not expressive enough to characterize the distinctive engagement pattern of each user. To address this problem, we propose PE, a personalized user engagement model for mobile videos, which, for the first time, addresses the user diversity in the engagement modeling. Evaluation results on a real-world data set show that our system significantly outperforms the uniform engagement models, with a 19.14% performance gain.

In delay tolerant networks (DTN), the social attributes of nodes show long-term stability, which can be leveraged for more effective routing. In this paper, we first present a novel way of constructing social circles based on the node clustering phenomena in DTN. Then, considering that the forwarding capability of nodes is significantly different, we propose a spray strategy based on social circles (named SC-SS) to improve the spray-and-wait routing algorithm. SC-SS selects the next hop based on the social circle of nodes in the spray phase. Instead of fixing the initial number of copies, we design an adaptive multiple spray-and-wait routing algorithm based on social circles (named SC-AMSW) to further improve the performance of SC-SS. SC-AMSW selectively sprays messages multiple times in the wait phase and determines an appropriate number of redundant message copies based on delivery predictability. We conduct extensive simulations to confirm the effectiveness of our proposed routing algorithms in DTN.

Today’s blockchain system provides two incentives for participants: block reward and transaction fee. However, these incentives benefit block miners more than ordinary participants. Besides, the message propagation relies on the volunteer work of these participants. We consider that there could be a third incentive to reward the relay process in the blockchain network. Nodes should be paid for corresponding relay work and incentives to expedite message propagation. We take advantage of the payment nature of blockchain and the characteristics of the UTXO Model, and propose a relay payment scheme to tackle the relay incentive issue. UTXO (unspent transaction output) is an abstract ownership of cryptocurrency and it represents a chain of payment relations between transactions. Any legal transaction should have valid UTXO(s) and generate new UTXO(s) to accomplish payment process. Native token in blockchain provides a straight and favorable payment method, and the UTXO model binds the interest of relay nodes and message originator. Then we model a cooperative, competitive relay game based on our scheme. We analyze the equilibrium results and run massive simulations on different datasets. This incentive scheme is free-rider resilient and could further expand to meet diverse relay requirement via transaction scripts in UTXO model. Our discussion and results help explore the relay incentives in the blockchain network and draw an example for the design of new blockchain systems.

In the Internet of Things (IoT), the mobile smart devices with powerful sensing capability help mobile crowdsourcing become an important paradigm to sense environment information. The social Internet of Things paradigm can be exploited for complex task crowdsourcing by forming a collaborative team of socially connected nodes (i.e., smart devices). Few existing team crowdsourcing studies have ever satisfied requirements of trustworthy sensing data and collaborative communication among team members. In this paper, we design TAQ-Crowd (Trust-Aware sensing Quality estimation for team Crowdsourcing), a social team crowdsourcing framework for Social Internet of Things systems. Within TAQ-Crowd , we first incorporate the consideration of trustworthy relationships between nodes into sensing data quality evaluation for TAQ model design. Then, we design a task assignment algorithm CS-Selection , in which the sensing quality guides the participant selection to maximize the overall task valuation under a budget constraint. Meanwhile, we consider a variant of the classic Traveling Salesman Problem (TSP) to extract a tree-structured routing network for team communication. Solving the team crowdsourcing problem concerns participating device selection and task cooperation, which involves two coupling NP-hard problems. The two coupling problems can be transformed into an essentially submodular cost submodular knapsack problem to be solved by the greedy task assignment strategy. Finally, extensive simulation experiments are conducted. The results show that TAQ-Crowd significantly outperforms state-of-art approaches in team formation with at least ( 1 − 1 ∕ e ) ∕ 2 approximation ratio. Furthermore, the achieved superior performance can validate our proposed trust-aware sensing quality estimation.

With the dramatic growth of online video services and video traffic, video service providers and network operators have keen interest in improving viewer engagement. Viewer engagement is mainly influenced by four aspects: service quality metrics (e.g., rebuffer time), network quality metrics (e.g., physical-layer data rate), video content (e.g., video length) and viewer demography. Previous works only partially consider some of these factors due to limitation of the dataset. In this paper, we develop an experimental platform with more than 50 self-deployed routers in our university campus, collecting information regarding all four aspects of engagement-related factors. Correlation and information gain analysis show that different viewer groups and video content types have different engagement patterns. Furthermore, we analyze each factor's significance in determining viewer engagement. Finally, we propose to build personalized models to better predict viewer engagement, with bootstrapping customized models for new viewers.