Anomaly detection and location of malicious node for IoT based on smart contract in blockchain network - Haojie HUANG; Xiaoxiao WU; Gangqiang LI (物联网学报)
With the explosive growth of the number of distributed devices in the Internet of things (IoT) network,the security of decentralized multi-agent optimization algorithm has become the forefront problem.The distributed algorithms in the IoT network are vulnerable to data injection attacks from internal malicious node because each agent locally estimates its state without any supervision.In general,the detection methods for malicious node run independently in each agent,inducing issues such as closed data,single points of failure,opaque detection processes,and so on.The proposed strategy considered detecting via an aid of blockchain technology and smart contracts in Ethereum to detect malicious node in the network.Based on the decentralized and multiple backup features of blockchain technology,the multi-site backup features of the blockchain technology enabled data sharing and avoided single point failure.In addition,the contract code,execution process and result of the smart contract were open and transparent,and the contract code and result could not be tampered to ensure that the detection process could be traced and verified.Finally,the average consensus algorithm was adopted as an example,and the proposed strategy was verified on a simplified IoT network implemented by Raspberry Pi.