Research on Network Data Security Storage Optimization Management

Abstract

Due to the variety of data used by the network, data storage is classified and encrypted. The traditional storage method mainly uses the data feature to select a key. When the amount of network data increases, the key appears to be duplicated, resulting in a problem of low security of data storage. A secure method for network data storage with improved keys is proposed. The cluster head is optimized and transmitted based on the layer cluster routing protocol, and a dynamic key is introduced in the data transmission process, and the key between the network data storage nodes is set by using the chain key generated by the hash function. The Chen hyperchaotic system is used to obtain the random key of the network data storage, the modified bits of the random key are planarly coded, the context and decision of the data storage are obtained, and the MQ arithmetic coder is used for entropy coding to generate the corresponding data storage compression code. The stream is fed back to the output of the Chen hyperchaotic system and the new data storage key is output. The simulation results show that the improved storage method effectively increases the security of data storage. Introduction Key management is the most basic part of network security storage. However, most of the current methods have hidden dangers, and the remaining methods are regarded as safe [1-2]. In this context, the safe storage of network data is the fundamental way to solve the above problems, and has received extensive attention from experts and scholars, and has made some progress [3]. Literature [4] proposes a secure method for network data storage based on scrambler DES encryption. The method firstly scrambles each of the traditional 48-bit keys in the 16-round transformation, and improves it by using the anti-exhaustive search method, and introduces it into the secure storage of network data. This method is easy to implement, but it is easy to appear important data. The problem of loss; literature [5] proposed a secure data storage method based on RSA, combining two combination identities and RSA public key algorithm, and forming an improved public key algorithm. The introduction of additional password parameters in the network data security storage enables secure storage of network data. The time complexity of the method is low, but when the current algorithm is used for secure storage of network data, the network data storage router has a security problem of being attacked. Literature [6] studied the network data security storage method of the improved quantum key negotiation algorithm. The method first performs further parity comparison on the redundant partial data in the same division interval of the network, implements key negotiation according to the improved error correction efficiency, and effectively realizes secure storage of network data, but the implementation process is cumbersome. Aiming at the shortcomings of traditional algorithms, this paper proposes an improved algorithm. The simulation results prove that the improved method effectively enhances the security of data storage. Network Data Security Storage Principle In the process of secure storage of network data, when the client needs to perform data storage, upload the encryption and decryption master key and save it on the server to obtain the data storage encryption pairing key according to the generation process of the customer master key. Encryption of the pairing key and storage on the server enables secure storage of network data. The specific steps are as follows: 236 In the process of secure storage of network data, the following formula is used to express the key of the encryption and decryption when the client needs to perform data storage. EK(M) = CM×M Z×Y (1) M represents the client s uploaded encrypted data, CM represents the data storage server, and Z and Y represent the plaintext and ciphertext of the master key, respectively. In the process of secure storage of network data, the data storage encryption pairing key is obtained by using the following formula: EK(k) = CK × EK(M) (2) CK represents the data storage encryption function. The pairing key is encrypted and stored on the server based on the customer master key generation process. DK(CK) = DK(EK(k)) × EK(k) (3) DK represents the customer master key generation process. In summary, the network data security storage principle can be explained, thereby effectively completing the secure storage of network data. Improved Key Network Data Security Storage Selection of Cluster Head Node under Layered Cluster Routing and Data Transmission Mode In the network data security optimization storage process, the layer cluster routing protocol may divide the network into a multi-cluster structure, and each cluster includes a cluster head node and a cluster intra-node, and the intra-cluster node may send the collected data storage information. To the cluster head node of the cluster, the cluster head node fuses the received information and then delivers it to the aggregation node, and completes the authentication of the data node by introducing a key. The specific steps are detailed below. (1) Clustering stage In the clustering stage, the cluster head nodes are mainly selected and clustered, and all network nodes are first arbitrarily selected from 0 to 1 by a random number. If the random number is lower than a threshold in the current round election, then the corresponding node is defined as a cluster head node. The threshold of the node is calculated by the following formula. T(n) = { p 1−p×[r mod( 1 p )] 0 (4) p is the percentage of the desired cluster head node in the network, r is the number of rounds, and mod is the set of nodes in the current 1/p round that are not cluster head nodes. In the network data security optimization storage process, it is necessary to select a resource-rich node as a cluster head node, and it is necessary to estimate the resource consumption of the network node. Therefore, in the cluster head election process, each sensor node is arbitrarily selected between 0 and 1. A value is compared with the cluster head node selection threshold represented by T(n). If the selected random number is higher than the threshold, the node is defined as a cluster head node, and the threshold T(n) is calculated by the following formula: T(n)′′ = { T(n) × Erest−Eused Eaverage−Eused 0 (5) Erest, Eused, Eaverage represent the remaining resources of the node, the use resources, and the average resources of the cluster to which the node belongs.