User-Centric Data Management in Decentralized Internet of Behaviors System

TL;DR

This paper presents a blockchain-based framework for secure, privacy-preserving data management in the Internet of Behaviors, addressing security risks and improving efficiency through innovative cryptographic and consensus techniques.

Contribution

It introduces a novel distributed IoB data storage and sharing framework utilizing zero-knowledge proofs and an improved consensus protocol for enhanced security and efficiency.

Findings

Reduced average consensus time by 74%

Decreased authentication time by 56%

Effective multi-scenario IoB data management

Abstract

The Internet of Behaviors (IoB) is an emerging concept that utilizes devices to collect human behavior and provide intelligent services. Although some research has focused on human behavior analysis and data collection within IoB, the associated security and privacy challenges remain insufficiently explored. This paper analyzes the security and privacy risks at different stages of behavioral data generating, uploading, and using, while also considering the dynamic characteristics of user activity areas. Then, we propose a blockchain-based distributed IoB data storage and sharing framework, which is categorized into sensing, processing, and management layers based on these stages. To accommodate both identity authentication and behavioral privacy, zero-knowledge proofs are used in the sensing layer to separate the correlation between behavior and identity, which is further extended to a distributed architecture for cross-domain authentication. In the processing layer, an improved consensus protocol is proposed to enhance the decision-making efficiency of distributed IoB by analyzing the geographical and computational capability of the servers. In the management layer, user permission differences and the privacy of access targets are considered. Different types of behavior are modeled as corresponding relationships between keys, and fine-grained secure access is achieved through function secret sharing. Simulation results demonstrate the effectiveness of the proposed framework in multi-scenario IoB, with average consensus and authentication times reduced by 74% and 56%, respectively.