The trust management and the identity authentication in the Vehicular Edge Computing (VEC) is the critical part of data security. However, most of the existing authentication schemes fail to fully address the data trust issue among edge computing nodes in cross-regional communications, and lack anonymous security features. In this paper, a lightweight Multi-entity Authenticated Group Key Agreement (MAGKA) protocol is proposed for blockchain-based VEC networks. The proposed blockchain network built from the roadside units is to ensure the un-deniability of any data exchanged among the edge networks to provide data trust management. The MAGKA protocol substantiates the lightweight authentication between the vehicles, the roadside unit, and the trusted authority anonymously, allowing the vehicles to join or leave the edge network dynamically on the premise of ensured security. The security analysis shows that MAGKA protocol can resist common attacks effectively. In addition, the performance evaluation shows that the MAGKA reduces the computational cost for the low-power node and powerful node by 75% and 50%, respectively, over the existing authentication protocols.

In this paper, we developed a color model to cancel the dependency between color channels, which enables us to separate spectral processing from, spatial processing. We introduced Independent Component Analysis (ICA) transformation in the wavelet domain to decorrelate the subband color joint statistics. The decorrelated joint color conditional histograms display scaling of variance. Gaussian Scale Mixture (GSM) was used to model the subband color statistics and a normalization scheme was adapted to cancel the pair-wise color subband statistical dependency. This color model was combined with the Portilla/Simoncelli texture model to construct the color texture model. Based on this model, features were extracted and the corresponding color texture synthesis scheme was developed.

In this paper we propose a novel system of semantic feature extraction and retrieval for interior design and decoration application. The system, V/sup 2/ID (virtual visual interior design), uses colored texture and spatial edge layout to obtain simple information about global room environment. We address the domain specific segmentation problem in our application and the techniques for obtaining semantic features from a room environment. We also discuss heuristics for making use of these features (color, texture or shape) to retrieve objects from an existing database. The final resynthesized room environment with original scene and novel object from database is created for the purpose of animation and virtual room walkthrough.