Supplementary files for article "A robust shard inspection framework with efficient throughput and energy consumption for secure geolocation-based sharded blockchains"

In sharded blockchains, peers are divided into smaller groups (shards) that generate and verify blocks in parallel, offering enhanced throughput and reduced delays. These properties make sharded blockchains a promising solution for secure data management in Internet of Things (IoT) systems. Particularly, geolocation-based sharded blockchains assign geographically proximate peers to the same shard, enabling faster IoT transaction processing. Yet, peers in each shard can easily collude to falsely accept/reject blocks. To resolve this issue, in this paper, we propose a robust reputation-based shard inspection framework. The framework adopts the shard inspection mechanism where a group of inspectors selected from the most reputable peers randomly verify blocks in each shard. This enables avoiding collusion attacks and enhancing the security of each shard. However, additional block verifications during the inspection process can incur significant block delays and energy overheads. To reduce these overheads, we formulate an optimization problem that jointly determines the number of inspectors and the inspection interval to maximize the system utility, which is proportional to the blockchain throughput and energy consumption. We then develop a distributed algorithm that enables dividing the optimization problem into sub-problems solvable independently by each shard. Experimental results show that our framework can maximize the system utility, while maintaining high levels of security in each shard.

©IEEE, CC BY 4.0

Supplementary files for article "A robust shard inspection framework with efficient throughput and energy consumption for secure geolocation-based sharded blockchains"

In sharded blockchains, peers are divided into smaller groups (shards) that generate and verify blocks in parallel, offering enhanced throughput and reduced delays. These properties make sharded blockchains a promising solution for secure data management in Internet of Things (IoT) systems. Particularly, geolocation-based sharded blockchains assign geographically proximate peers to the same shard, enabling faster IoT transaction processing. Yet, peers in each shard can easily collude to falsely accept/reject blocks. To resolve this issue, in this paper, we propose a robust reputation-based shard inspection framework. The framework adopts the shard inspection mechanism where a group of inspectors selected from the most reputable peers randomly verify blocks in each shard. This enables avoiding collusion attacks and enhancing the security of each shard. However, additional block verifications during the inspection process can incur significant block delays and energy overheads. To reduce these overheads, we formulate an optimization problem that jointly determines the number of inspectors and the inspection interval to maximize the system utility, which is proportional to the blockchain throughput and energy consumption. We then develop a distributed algorithm that enables dividing the optimization problem into sub-problems solvable independently by each shard. Experimental results show that our framework can maximize the system utility, while maintaining high levels of security in each shard.

©IEEE, CC BY 4.0

Article abstractConsortium blockchains have attracted considerable interest from academia and industry due to their low-cost installation and maintenance. However, typical consortium blockchains can be easily attacked by colluding block validators because of the limited number of miners in the systems. To address this problem, in this article, we propose a novel block validation framework to enhance blockchain security. In the framework, the block validations are assisted and implemented by various lightweight nodes, e.g., edge devices, in addition to the typical blockchain miners. This improves the blockchain security but can cause an increased block validation delay and, thereby, reduced blockchain throughput. To tackle this challenge, we propose an effective method to select lightweight nodes based on their computing powers to maximize the blockchain throughput, and prove the uniqueness of the optimal nodes selection strategy. Security analysis and simulation results from the deployed consortium blockchain platform show that the proposed framework achieves higher throughput and security than the existing consortium blockchain models.© 2023 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.

Article abstractConsortium blockchains have attracted considerable interest from academia and industry due to their low-cost installation and maintenance. However, typical consortium blockchains can be easily attacked by colluding block validators because of the limited number of miners in the systems. To address this problem, in this article, we propose a novel block validation framework to enhance blockchain security. In the framework, the block validations are assisted and implemented by various lightweight nodes, e.g., edge devices, in addition to the typical blockchain miners. This improves the blockchain security but can cause an increased block validation delay and, thereby, reduced blockchain throughput. To tackle this challenge, we propose an effective method to select lightweight nodes based on their computing powers to maximize the blockchain throughput, and prove the uniqueness of the optimal nodes selection strategy. Security analysis and simulation results from the deployed consortium blockchain platform show that the proposed framework achieves higher throughput and security than the existing consortium blockchain models.© 2023 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.