High-Efficiency Traceability Mechanism for Multimedia Data in Consumer Internet of Things Combined with Blockchain

In the context of the rapid development of Consumer Internet of Things (CIoT), the manipulation and unauthorized distribution of multimedia content have raised serious concerns regarding copyright protection and data authenticity. Ensuring secure traceability and authenticity in complex network environments remains a major challenge. Traditional blockchain mechanisms often suffer from high latency during large-scale data queries, making them unsuitable for real-time CIoT applications. To address this, this paper proposes a high-efficiency blockchain-based multimedia data security traceability method. First, blockchain is integrated with the PROV model to guarantee operation transparency and data credibility. Second, a joint index structure comprising a fast index (using traceability positioning tables for cross-block jumps) and a multi-bucket index (using self-balancing binary trees) is designed. Experimental results demonstrate that compared to traditional blockchain and SEBDB methods, the proposed mechanism remains stable as data volume exceeds 2000 records. Specifically, the query time growth rate is significantly lower than linear scanning methods (12-18% vs. 45-62% for traditional methods), and the number of traversed records is reduced by 60-75% by avoiding full-chain traversal, verifying the method's superiority in handling high-frequency CIoT multimedia queries while providing protection against tampering and unauthorized distribution.

Authors

Institutions

Publication Details

Journal
Sensors
Published
2025-12-22
DOI
https://doi.org/10.3390/s26010074
Primary Topic
Blockchain Technology Applications and Security
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

High-Efficiency Traceability Mechanism for Multimedia Data in Consumer Internet of Things Combined with Blockchain

Tianyi Yan, Gang Hu, Xiaorui Zhang, Jimin Chen
Sensors
Blockchain Technology Applications and Security
article

High-Efficiency Traceability Mechanism for Multimedia Data in Consumer Internet of Things Combined with Blockchain

Tianyi Yan, Gang Hu, Xiaorui Zhang, Jimin Chen
article en

Abstract

In the context of the rapid development of Consumer Internet of Things (CIoT), the manipulation and unauthorized distribution of multimedia content have raised serious concerns regarding copyright protection and data authenticity. Ensuring secure traceability and authenticity in complex network environments remains a major challenge. Traditional blockchain mechanisms often suffer from high latency during large-scale data queries, making them unsuitable for real-time CIoT applications. To address this, this paper proposes a high-efficiency blockchain-based multimedia data security traceability method. First, blockchain is integrated with the PROV model to guarantee operation transparency and data credibility. Second, a joint index structure comprising a fast index (using traceability positioning tables for cross-block jumps) and a multi-bucket index (using self-balancing binary trees) is designed. Experimental results demonstrate that compared to traditional blockchain and SEBDB methods, the proposed mechanism remains stable as data volume exceeds 2000 records. Specifically, the query time growth rate is significantly lower than linear scanning methods (12-18% vs. 45-62% for traditional methods), and the number of traversed records is reduced by 60-75% by avoiding full-chain traversal, verifying the method's superiority in handling high-frequency CIoT multimedia queries while providing protection against tampering and unauthorized distribution.

SensorsVol. 26(1)
Nanjing Tech University (CN), Anhui University of Technology (CN)
National Natural Science Foundation of China
Peace, Justice and strong institutions
Openalex Percentile: Top 24%
Blockchain Technology Applications and Security
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.