Scalability prevents public blockchains from being widely adopted for Internet of Things (IoT) applications such as supply chain management. Several existing solutions focus on increasing the transaction count, but none of them address scalability challenges introduced by resource-constrained IoT device integration with these blockchains, especially for the purpose of supply chain ownership management. Thus, this paper solves the issue by proposing a scalable public blockchain-based protocol for the interoperable ownership transfer of tagged goods, suitable for use with resource-constrained IoT devices such as widely used Radio Frequency Identification (RFID) tags. The use of a public blockchain is crucial for the proposed solution as it is essential to enable transparent ownership data transfer, guarantee data integrity, and provide on-chain data required for the protocol. A decentralized web application developed using the Ethereum blockchain and an InterPlanetary File System is used to prove the validity of the proposed lightweight protocol. A detailed security analysis is conducted to verify that the proposed lightweight protocol is secure from key disclosure, replay, man-in-the-middle, de-synchronization, and tracking attacks. The proposed scalable protocol is proven to support secure data transfer among resource-constrained RFID tags while being cost-effective at the same time.

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10098889PMC
http://dx.doi.org/10.3390/s23073433DOI Listing

Publication Analysis

Top Keywords

lightweight protocol
12
supply chain
12
protocol interoperable
8
public blockchain-based
8
chain ownership
8
ownership management
8
resource-constrained iot
8
rfid tags
8
data transfer
8
proposed lightweight
8

Similar Publications

This paper introduces a novel energy-efficient lightweight, void hole avoidance, localization, and trust-based scheme, termed as Energy-Efficient and Trust-based Autonomous Underwater Vehicle (EETAUV) protocol designed for 6G-enabled underwater acoustic sensor networks (UASNs). The proposed scheme addresses key challenges in UASNs, such as energy consumption, network stability, and data security. It integrates a trust management framework that enhances communication security through node identification and verification mechanisms utilizing normal and phantom nodes.

View Article and Find Full Text PDF

Due to the openness of communication channels and the sensitivity of the data being collected and transmitted, securing data access and communication in IoT systems requires robust ECC-based authentication and key agreement (AKA) protocols. However, designing an AKA protocol for IoT presents significant challenges, as most IoT sensors are deployed in resource-constrained, unattended environments with limited computational power, connectivity, and storage. To achieve anonymous authentication, existing solutions typically rely on shared temporary public keys to mask device IDs or validate sender certificates, which increases the computational overhead.

View Article and Find Full Text PDF

Serine-modified silver nanoparticle porous spray membrane: A novel approach to wound infection prevention and inflammation reduction.

Int J Pharm

January 2025

College of Pharmaceutical Sciences, Zhejiang University, 866 Yuhangtang Road, Hangzhou, Zhejiang 310058, PR China. Electronic address:

Traditional wound care preparations frequently face challenges such as complex care protocols, poor patient compliance, limited skin permeability, lack of aesthetics, and inconvenience, in addition to the risk of bacterial infection. We developed a spray film preparation containing nanocellulose and L-serine modified nanosilver, capable of rapidly forming a transparent film on the skin within minutes of application. The incorporation of nanocellulose imparted protective, moisturizing, and breathable properties to the film, allowing for easy removal after use.

View Article and Find Full Text PDF
Article Synopsis
  • Smart wearables are essential for health monitoring and assisting the elderly or individuals with disabilities, but current machine learning methods face high resource demands and limited scalability.
  • This research introduces a new behavior detection approach that combines multi-source sensing with logical reasoning, aiming to streamline the process of behavior recognition.
  • The developed system achieves over 90% accuracy in recognizing 11 daily activities while significantly reducing the need for extensive training data compared to traditional machine learning methods.
View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!