Low-energy consumption large-scale network data safety fusion method based on probability distribution

Abstract

The present invention discloses a low-energy consumption large-scale network data safety fusion method based on probability distribution. The method mixes the data acquired by the general nodes in a network by adding a disturbance data technology, a cluster head adds the data of the sub-nodes simply, and a base station finishes the decryption operation. By analyzing a probability distribution model with which the random variables for acquiring data comply, and when the number of the sub-nodes monitored by attackers is smaller, the decryption data precision does not reach an error threshold set by users, while the base station possessing the whole network data can decrypt the acquired data at a precision needed by users, and the number of the data packets needing to be intercepted to decrypt the data precisely can be estimated approximately by a formula. The low-energy consumption large-scale network data safety fusion method based on probability distribution effectively overcomes the difficulty of distributing the secret keys by a conventional method, and enables the network transmission cost to be reduced.

Description

technical field [0001] The invention relates to the technical field of communication security, in particular to a data security fusion method for the perception layer of the Internet of Things. Background technique [0002] The Internet of Things perception layer network has the characteristics of self-organization, large-scale, and low power consumption. The main purpose of applying data fusion technology to the perception layer network is to reduce the transmission overhead of the network and reduce the consumption rate of network resources. [0003] Perception nodes have low computing and processing capabilities. Therefore, the existing data fusion methods are all based on lightweight algorithms. While data fusion reduces network transmission overhead, it also has certain security issues. The security threats at the end nodes of the perception layer include unauthorized reading of node information, node unavailability, fake nodes and malicious code attacks. The securi...

AI Technical Summary

Problems solved by technology

Another difficulty encountered by the traditional data security fusion method is that the fusion algorithm needs to use the ID number of the node, and the ID number is different from the data, and its statistical characteristics have no reference value, and the ID number cannot be fused like the collected data

Therefore, the traditional data security fusion algorithm is inconvenient to manage and has high transmission overhead

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