【Author】
Arifeen, Murshedul; Ghosh, Tapotosh; Islam, Rakibul; Ashiquzzaman, Akm; Yoon, Juncheol; Kim, Jinsul
【Source】INTERNET OF THINGS
【Abstract】Conventional blockchain technologies developed for cryptocurrency applications involve complex consensus algorithms which are not suitable for resource constrained Internet of Things (IoT) devices. Therefore, several lightweight consensus mechanisms that are suitable for IoT devices have been proposed in recent studies. However, these lightweight consensus mechanisms do not verify the originality of the data generated by the IoT devices, so false and anomalous data may pass through and be stored in the ledger for further analysis. In this work to address the data originality verification problem, we propose an autoencoder (AE)-integrated Chaincode (CC)-based consensus mechanism in which the AE differentiates normal data from anomalous data. The AE is invoked through the CC once a transaction is initiated; the result returned from the AE to the CC is stored in the ledger. We have conducted a case study to train and test the AE model on the IoTID20 dataset. Also, Minifabric (MF) is used to implement the CC and illustrate the CC operation that stores only original IoT data. Moreover, the performance has been shown for the CC in terms of latency and throughput.
【Keywords】IoT; Autoencoder; Blockchain; Hyperledger; Security
【标题】基于自动编码器的区块链工业物联网的共识机制
【摘要】为加密货币应用开发的传统区块链技术涉及复杂的共识算法，不适合资源有限的物联网（IoT）设备。因此，在最近的研究中提出了几个适合物联网设备的轻量级共识机制。然而，这些轻量级的共识机制并没有验证物联网设备产生的数据的原始性，因此虚假和异常的数据可能会通过并存储在账本中，以供进一步分析。在这项工作中，为了解决数据的原始性验证问题，我们提出了一个自动编码器（AE）--集成的基于Chaincode（CC）的共识机制，其中AE区分了正常数据和异常数据。一旦交易开始，AE就会通过CC被调用；AE返回给CC的结果被存储在账本中。我们进行了一个案例研究，在IoTID20数据集上训练和测试AE模型。同时，Minifabric（MF）被用来实现CC，并说明了只存储原始物联网数据的CC操作。此外，CC在延迟和吞吐量方面的性能也得到了展示。
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