Blockchain innovation has picked up expanding consideration from investigating and industry over the later a long time. It permits actualizing in its environment the smart-contracts innovation which is utilized to robotize and execute deals between clients. Blockchain is proposed nowadays as the unused specialized foundation for a few sorts of IT applications. Blockchain would aid avoid the duplication of information because it right now does with Bitcoin and other cryptocurrencies. Since of the numerous hundreds of thousands of servers putting away the Bitcoin record, it’s impossible to assault and alter. An aggressor would need to change the record of 51 percent of all the servers, at the precise same time. The budgetary fetched of such an assault would distantly exceed the potential picks up. The same cannot be said for our private data that lives on single servers possessed by Google and Amazon. In this paper, we outline major Blockchain technology that based as solutions for IOT security. We survey and categorize prevalent security issues with respect to IoT data privacy, in expansion to conventions utilized for organizing, communication, and administration. We diagram security necessities for IoT together with the existing scenarios for using blockchain in IoT applications.
To solve the problem of large recognition errors in traditional attack information identification
methods, we propose a machine learning (ML)-based identification method for electric power Internet attack
information. Based on the Internet attack information, an Internet attack information model is constructed, the
identification principle of the power Internet attack information is analysed based on ML, hash fixing is conducted to
ensure that the same attack information will be assigned to the same thread and that the deviation generated by noise
can be avoided so that the real-time lossless processing of the power Internet attack information can be ensured. The
vulnerability adjacency matrix is constructed, and the vulnerability is quantitatively evaluated to complete the design
of the optimal identification scheme for power Internet attack information. The experimental results show that the
identification accuracy of the method can reach 98%, which can effectively reduce the risk of power Internet network
attacks and ensure the safe and stable operation of the network.
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