Big Data Privacy Protection Model Based on Multi-level Trusted System

DOI

10.2991/ncce-18.2018.18How to use a DOI?

Keywords

Multi-level Trusted System Model; Risk Sub-group and Risk Level; Price Point Model; Privacy Value; Privacy Cost Model; Pricing Model; Symmetric and Asymmetric Encryption Algorithms.

Abstract

This paper introduces and inherit the multi-level trusted system model that solves the Trojan virus by encrypting the privacy of user data, and achieve the principle: "not to read the high priority hierarchy, not to write the hierarchy with low priority”. Thus ensuring that the low-priority data privacy leak does not affect the disclosure of high-priority data privacy. This paper inherits the multi-level trustworthy system model of Trojan horse and divides seven different risk levels. The priority level 1 ~ 7 represent the low to high value of user data privacy, and realize seven kinds of encryption with different execution efficiency Algorithm, the higher the priority, the greater the value of user data privacy, at the expense of efficiency under the premise of choosing a more encrypted encryption algorithm to ensure data security. For enterprises, the price point is determined by the unit equipment users to decide the length of time. The higher the risk sub-group algorithm, the longer the encryption time. The model assumes that users prefer the lower priority encryption algorithm to ensure efficiency. This paper proposes a privacy cost model for each of the seven risk subgroups. Among them, the higher the privacy cost, the higher the priority of the risk sub-group, the higher the price the user needs to pay to ensure the privacy of the data. Furthermore, by introducing the existing pricing model of economics and the human traffic model proposed by this paper and fluctuating with the market demand, this paper improves the price of unit products when the market demand is low. On the other hand, when the market demand increases, the profit of the enterprise will be guaranteed under the guidance of the government by reducing the price per unit of product. Then, this paper introduces the dynamic factors of consumers' mood and age to optimize. At the same time, seven algorithms are selected from symmetric and asymmetric encryption algorithms to define the enterprise costs at different levels. Therefore, the proposed model solves the continuous influence caused by cascading events and ensures that the disclosure of low-level data privacy of users does not affect the high-level data privacy, thus greatly improving the safety of the private information of user.

Copyright

© 2018, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Nan Zhang
AU  - Zehua Liu
AU  - Hongfeng Han
PY  - 2018/05
DA  - 2018/05
TI  - Big Data Privacy Protection Model Based on Multi-level Trusted System
BT  - Proceedings of the 2018 International Conference on Network, Communication, Computer Engineering (NCCE 2018)
PB  - Atlantis Press
SP  - 103
EP  - 109
SN  - 1951-6851
UR  - https://doi.org/10.2991/ncce-18.2018.18
DO  - 10.2991/ncce-18.2018.18
ID  - Zhang2018/05
ER  -