Privacy Protection Of Online Big Data Based On Social Platforms

In the context of the era of big data,it is becoming more and more important to analyze the security issues and development status of social platforms and study the privacy data security issues in social platforms.This article aims to protect privacy-sensitive data by encrypting it to achieve protection As a result,chaos encryption is used for encryption.With the promulgation of the National Cryptography Law and the current demand for data currency encryption,the chaotic cryptosystem will be increasingly applied to more fields.Chaotic ciphers use the properties of chaos,namely determinism,randomness,ergodicity and sensitivity to initial conditions,can use software to generate sequences,which changes the traditional cryptography to use physical noise source chips to generate sequences.In terms of analysis technology,I used the Hadoop distributed open source system under the big data platform,combining big data technology with the chaotic encryption to improve the security of private data.Using the Hadoop platform for encryption,a method for analyzing social network data based on the Hadoop platform is proposed,and these private data are encrypted using a hybrid encryption system.The specific work is as follows:(1)This paper designs a hybrid encryption algorithm.First use the hyper-chaotic system to generate two hyper-chaotic sequences and there is nothing uncorrelated,then the two unrelated hyper-chaotic sequences are XORed with the plain text,so that the first encryption is completed,and then Next,encrypt the ciphertext encrypted for the first time and then encrypt it for the second time,and then encrypt the ciphertext encrypted with the sequence generated by the conic curve for the first time.Finally,an experiment was built and analyzed.The encryption algorithm has a large space in terms of secret keys and high statistical properties of the ciphertext.These indicators are very important indicators in the field of password security.Block,the plaintext and ciphertext analyzed after two encryptions do not have any connection,so special plaintext or ciphertext cannot be used for cracking,and the algorithm uses non-linear operations,which can effectively resist when selecting the plaintext attack This shows that the algorithm is very safe.(2)A privacy data encryption system based on Hadoop social platform is designed.Using big data technology,the ability to analyze the privacy data of large-scale social networks is greatly improved.There are four levels in this system.The first level is user interaction,the second level is data preprocessing,the third level is private data mining and encryption,and the fourth level is distributed storage and computing.The three-layer privacy data mining and encryption is to use the Hadoop platform to mine and analyze the massive data on the social network to obtain the association rules between the private information to find the private information and encrypt it.(3)An association rule mining algorithm is designed.Due to the huge amount of data,the traditional FP-growth association rule mining algorithm cannot meet the current needs.An upgraded association rule mining algorithm(TFP)is designed,which fully considers the mining on the big data platform,and also considers the communication problem of each node,so the algorithm can optimize the communication to solve the load The balance problem and the consumption problem of communication between various nodes.The implementation shows that this method does improve the efficiency,and the communication balance of each node is checked.The overall efficiency is higher than the ordinary FP-growth algorithm.