An image partition security-sharing mechanism based on blockchain and chaotic encryption.

To ensure optimal use of images while preserving privacy, it is necessary to partition the shared image into public and private areas, with public areas being openly accessible and private areas being shared in a controlled and privacy-preserving manner. Current works only facilitate image-level sharing and use common cryptographic algorithms. To ensure efficient, controlled, and privacy-preserving image sharing at the area level, this paper proposes an image partition security-sharing mechanism based on blockchain and chaotic encryption, which mainly includes a fine-grained access control method based on Attribute-Based Access Control (ABAC) and an image-specific chaotic encryption scheme. The proposed fine-grained access control method employs smart contracts based on the ABAC model to achieve automatic access control for private areas. It employs a Cuckoo filter-based transaction retrieval technique to enhance the efficiency of smart contracts in retrieving security attributes and policies on the blockchain. The proposed chaotic encryption scheme generates keys based on the private areas' security attributes, largely reducing the number of keys required. It also provides efficient encryption with vector operation acceleration. The security analysis and performance evaluation were conducted comprehensively. The results show that the proposed mechanism has lower time overhead than current works as the number of images increases.

A Weighted GraphSAGE-Based Context-Aware Approach for Big Data Access Control.

Context information is the key element to realizing dynamic access control of big data. However, existing context-aware access control (CAAC) methods do not support automatic context awareness and cannot automatically model and reason about context relationships. To solve these problems, this article proposes a weighted GraphSAGE-based context-aware approach for big data access control. First, graph modeling is performed on the access record data set and transforms the access control context-awareness problem into a graph neural network (GNN) node learning problem. Then, a GNN model WGraphSAGE is proposed to achieve automatic context awareness and automatic generation of CAAC rules. Finally, weighted neighbor sampling and weighted aggregation algorithms are designed for the model to realize automatic modeling and reasoning of node relationships and relationship strengths simultaneously in the graph node learning process. The experiment results show that the proposed method has obvious advantages in context awareness and context relationship reasoning compared with similar GNN models. Meanwhile, it obtains better results in dynamic access control decisions than the existing CAAC models.

Dynamic Autonomous Cross Consortium Chain Mechanism in e-Healthcare.

Safe and scalable dynamic autonomous data interaction between medical institutions can increase the number of clinical trial records, which is of great significance for improving the level of medical trial collaboration, especially for clinical decision-making with regard to rare diseases. Through a preset authorization access and consensus mechanism, consortium chain provides integrity and traceability management for medical clinical data. However, how to enable users have ownership of their own medical data and share their medical data safely and dynamically between different medical institutions remains an area of particular concern. To achieve dynamic communication between medical consortium chains, this paper proposes (i) a cross-chain communication mechanism by simplifying the heterogeneous node communication topology and (ii) the construction rules of the node identity credibility path-proof to carry out dynamic construction and verification of the path-proof for cross-chain transactions. In addition, the consensus of the cross-chain transaction is modeled as a threshold digital signature process with multiple privileged subgroups; thus, the intra-chain consortium consensus based on the verification node list is extended to the cross-chain consensus. A smart contract deployment and execution scheme based on rational node value transfer mechanism is proposed by analyzing the value transfer game between nodes. Experimental results showed that the proposed scheme can not only enable patients to share their records safely and autonomously in an authorized medical consortium chain within milliseconds but also realize dynamic adaptive interaction among heterogeneous consortium chains.