从网络聚类因子计算个人数据保护的方法

V. Akhramovich
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引用次数: 0

摘要

建立了数学模型,从网络聚类系数和社交网络中数据传输强度的角度对个人数据保护模型进行了研究。系统保护与系统规模(以及个人数据量)的依赖关系;信息安全威胁来自网络聚类因素。得到一个线性方程组,由等式组成:来自社会网络安全的信息流变化率和反映安全措施影响的系数、个人数据量、泄露率、来自网络聚类因素的信息保护变化、其大小、个人数据保护。通过求解微分方程组,得到了社会网络中个人数据保护指标在不同分量下的数学和图形依赖关系。考虑在系统稳态附近求解方程的三种选择,我们可以得出结论,基于耗散与固有频率之比的条件,后者衰减到某一值是周期性的,具有衰减幅度,或呈指数衰减规律。对系统行为进行更直观的分析,从方程的微分形式转向离散形式,并对系统存在的某个区间进行建模。给出了系统固有频率、振荡周期、衰减系数的数学关系和图形关系。对偏离系统静止位置的值进行了仿真建模。仿真结果表明,该社会网络保护系统是非线性的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
METHOD OF CALCULATING THE PROTECTION OF PERSONAL DATA FROM THE NETWORK CLUSTERING FACTOR
A mathematical model has been developed and a study of the model of personal data protection from network clustering coefficient and data transfer intensity in social networks has been carried out. Dependencies of protection of the system from the size of the system (and from the amount of personal data); information security threats from the network clustering factor. A system of linear equations is obtained, which consists of the equation: rate of change of information flow from social network security and coefficients that reflect the impact of security measures, amount of personal data, leakage rate, change of information protection from network clustering factor, its size, personal data protection. As a result of solving the system of differential equations, mathematical and graphical dependences of the indicator of personal data protection in the social network from different components are obtained. Considering three options for solving the equation near the steady state of the system, we can conclude that, based on the conditions of the ratio of dissipation and natural frequency, the attenuation of the latter to a certain value is carried out periodically, with decaying amplitude, or by exponentially decaying law. A more visual analysis of the system behavior is performed, moving from the differential form of equations to the discrete one and modeling some interval of the system existence. Mathematical and graphical dependences of the system natural frequency, oscillation period, attenuation coefficient are presented. Simulation modeling for values with deviation from the stationary position of the system is carried out. As a result of simulation, it is proved that the social network protection system is nonlinear.
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