With the popularity of location-based services (LBSs) and the explosive growth of spatial data, massive spatial data has been outsourced to cloud servers for storage and query services, such as spatial range and fuzzy keyword query. To protect data and user privacy, it is essential to encrypt the data and query requests before uploading them. However, encrypting the data makes search on ciphertext more challenging. Moreover, the existing schemes do not support spatial range and fuzzy keyword query (SFKQ for short) simultaneously. To this end, we first leverage the indecomposable property of primes and the Geohash algorithm to create an index vector and query trapdoor vector. We then propose concrete constructions for SFKQ, which support both spatial range query and fuzzy multikeyword query in a single interaction. Additionally, we carefully design a novel Geohash-based index structure (referred to as GeoTree) along with a pruning strategy to accelerate search efficiency. Finally, we provide the formal security analysis to demonstrate that the proposed SFKQ scheme is indistinguishable under chosen-plaintext attacks (IND-CPA), and we conduct comprehensive experiments to validate the accuracy and efficiency.

Federated learning (FL) in Vehicular Ad-hoc Networks (VANETs) enables vehicles to collaboratively train machine learning models by aggregating local gradients without revealing the training data. To ensure no gradient is revealed during aggregation, proposals are using a secret sharing-based strategy. A major bottleneck for applying these proposals in VANETs is the overhead of model aggregation across high-mobility vehicles. Particularly, the communication overhead grows exponentially due to the dynamic of VANETs. In the paper, we propose Batch-Aggregate, an efficient aggregation scheme for FL coping with high mobility and unstable connections of VANETs. By encoding the linear encryption into a short group signature, we combine authentication into aggregation protocol. When a registered vehicle trains its local model and sends the masked gradients to the nearby Road-side Unit (RSU), the RSU can independently check the gradients for validity and aggregate the parameters in a batch way. Thus, the computation time of the aggregator will be reduced to$\mathcal {O}(n)$while the gradients can be aggregated in one communication round per training iteration. Moreover, our scheme provides privacy properties such as anonymity and unlinkability. The simulations show that the computation overhead of Batch-Aggregate grows linearly under the batch-enabled scheme, which reduces up to 50% over the existing schemes.

Real-time and interactive traffic information sharing systems are crucial in the Internet of Vehicles (IoV) as they enable vehicles to make informed decisions, thereby improving the efficiency of intelligent transportation systems (ITS). Message authentication ensures the accuracy, integrity, and tamper-resistance of information in IoV. Existing schemes aim to achieve time-critical message authentication . However, these schemes are time-consuming and cannot meet the real-time requirements of IoV. Additionally, there are issues with latency in data synchronization and data redundancy when vehicles traverse different domains. We propose an efficient, distributed, and resistant-to-malicious-attacks authentication scheme based on the reputation mechanism. Our scheme supports batch verification, enabling fast authentication. By leveraging the decentralized and ledger-synchronized features of blockchain , our distributed scheme reduces data redundancy. We also employ a reputation mechanism to ensure reliable reports in IoVs. We experimentally confirm that our scheme outperforms EADA (59.73%), RCoM (76.35%), MLGSDT (63.36%), and TRAJ (82.08%). This approach provides a secure and reliable solution for report authentication.

The blockchain technology achieves security by sacrificing prohibitive storage and computation resources. However, in mobile systems, the mobile devices usually offer weak computation and storage resources. It prohibits the wide application of the blockchain technology. Edge computing appears with strong resources and inherent decentralization, which can provide a natural solution to overcoming the resource-insufficiency problem. However, applying edge computing directly can only relieve some storage and computation pressure. There are some other open problems, such as improving confirmation latency, throughput, and regulation. To this end, we propose an edge-computing-based lightweight blockchain framework (ECLB) for mobile systems. This paper introduces a novel set of ledger structures and designs a transaction consensus protocol to achieve superior performance. Moreover, considering the permissioned blockchain setting, we specifically utilize some cryptographic methods to design a pluggable transaction regulation module. Finally, our security analysis and performance evaluation show that ECLB can retain the security of Bitcoin-like blockchain and better performance of ledger storage cost in mobile devices, block mining computation cost, throughput, transaction confirmation latency, and transaction regulation cost.

Vehicular Ad-hoc Networks (VANETs) supporting the seamless operation of autonomous vehicles introduce various network-connected devices. The widespread devices are engaged in VANETs so that users can enjoy advantageous computing and reliable services. The combination brings in massive real-time message propagation and dissemination, which would be leveraged by the adversaries to perform data association, integration analysis and privacy mining. To address such challenges, existing authentication schemes use n pseudonym certificates for pre-defined k times and try to keep the vehicles anonymous. These schemes require fresh certificates for each authentication process, which cost more communication and storage resources. In this paper, we propose a novel privacy-preserving authentication protocol (P2BA) in bilinear groups, where a registered vehicle signs a traffic-related message and sends it to the nearby Road-side Unit (RSU) together with its blinded certificate. The RSU is able to independently check the message for validity based on a non-interactive zero-knowledge proof protocol. In this way, the computation time has been reduced fromO(n) toO(1) while the storage overhead fromO(nk) toO(n) compared to anonymous authentication protocols. Moreover, our scheme provides privacy properties such as anonymity and unlinkability. The simulations show that the message authentication can be processed by individual RSUs within 1 ms under the batch-enabled scheme, which outperforms the existing schemes in terms of computation overhead and latency.

In this paper, a novel digital video resolution enhancement algorithm based on adaptive directional interpolation is proposed, where the directionality of the edge structure and the nonlocal self-similarity prior within the current frame as well as its adjacent frames are both considered. First, we establish the regularization equation that conforms to the prior model of a video frame and then take the classic bicubic interpolation result as the initial estimation to iteratively solve the restoration equation, in which the edge structures and contours in low resolution (LR) input are reconstructed to estimate and refine the desired high resolution (HR) output. Experimental results show that the proposed algorithm can effectively enhance the clarity of a video frame, with satisfying subjective visual quality and PSNR value.

This paper proposes an efficient and simple architecture for 9/7 discrete wavelet transform based on distributed arithmetic. To derive new proposed architecture, we consider the periodicity and symmetry of DWT to optimize the performance and reduce the computational redundancy. The inner product of coefficient matrix of DWT is distributed over the input by careful analysis of input, output and coefficient word lengths. In the coefficient matrix, linear maps are used to assign the necessary computation to processing elements in space domain. Moreover, the proposed architecture has regular data flow, and low control complexity. The result is a low hardware complexity DWT processor for 9/7 transforms, which allows two times faster clock than the direct implementation. This design is very suitable for image compression systems, e.g., JPEG2000 and MPEG4