Research On Theoretical Model Of Network "Gene" Map

With the widespread use of mobile Internet technology,the scope of human activities is no longer confined to the real world,and there is a phenomenon of virtual and real co-occurrence.Both online and offline behaviors have the possibility of encryption,anonymity,and movement.It is easy to provide opportunities for illegal elements to engage in illegal and criminal activities.At the same time,the obscuration or defect of identity information further increases the difficulty of law enforcement,and law enforcement officers cannot accurately identify entities based on behavioral data that conceals or loses identity information.When the identity information is separated from the behavior data,how to use the only behavior data to obtain the real identity of the entity becomes an urgent problem to be solved.This paper follows the principle that biological genes can uniquely identify an entity.Based on the concept of the "gene" map of the network,this paper has carried out further research and concrete.The network "gene" map is a new,predictable,comprehensible,inferential,and computable multidimensional structure that alleviates identity loss,identity obscuration,identity forgery,cross-site multiplicity in a completely new way.The problem of difficult identification of identity,that is,the problem that virtual identity and real identity are difficult to map,and it will provide important theoretical research value and practical practical guiding significance for accurately identifying,effectively preventing and accurately attacking illegal entities.The main research done in this paper is as follows:(1)Construction of the “gene” map framework.The "gene" map consists of: the network "gene" map consists of two categories: the identity "gene" group and the behavior "gene" group.The identity "gene" group can be subdivided into three categories: deterministic identity "gene" fragments,virtual identity "gene" fragments,and biometric "gene" fragments;the types of behaviors are more numerous,and the acquisition and analysis are more difficult,so the behavior The "gene" group is divided into mobile phone communication "gene" fragments,SMS communication "gene" fragments,email "gene" fragments,travel "gene" fragments,online shopping "gene" fragments,and delivery "genes" based on the data sources currently collected.Fragments,microblog "gene" fragments,instant messaging "gene" fragments,remotely manipulated "gene" fragments,online financial "gene" fragments,and later additions of other "gene" fragments."Gene" fragment splicing: The "gene" fragments are spliced according to the type of the fragments and the time of the fragments.The spliced "gene" fragments are only linked by the entity number,and are independent of each other,thus ensuring that the information is not filled in the later stage.It will interfere with other segments,thus ensuring that the "gene" map structure will not change significantly.(2)Determination of the content of the network "gene" fragment.According to the behavioral dynamics and statistical knowledge of different behavioral data,analyze the interval distribution,response distribution,position distribution,relationship distribution,etc.,in order to obtain the characteristic parameters and statistical characteristics of the target human behavior,and construct the behavior "gene".Fragment.The structure and construction process of the "gene" fragments of each behavior are similar.Therefore,this paper analyzes the three major segments of e-mail,delivery and instant communication in the behavioral "gene" group,and provides a close relationship.The algorithm is used to determine the stable contact of the entity,and at the same time,the unified logical structure of the behavior "gene" fragment is given to simplify the subsequent operations.(3)Similarity test of network "gene" fragments.In this paper,based on the complex internal composition of behavioral “gene” fragments,a similarity measure method combining the overall behavior characteristics and network relationship characteristics is proposed.At the same time,some values are symbolized in advance to reduce the impact of numerical volatility.Finally,several matching cases are analyzed,and the solution is given accordingly.