CN112597146A - Criminal investigation application system and method based on WIFI big data - Google Patents
Criminal investigation application system and method based on WIFI big data Download PDFInfo
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Abstract
The invention discloses a criminal investigation application system and method based on WIFI big data, which are used for solving the problems of single investigation working method, large workload of artificial feature extraction and application of artificial subjective factors to criminal investigation, and comprise a collection layer, a storage layer, an analysis layer and an application layer; the acquisition layer is used for acquiring and recording original user data and sending the original user data to the storage layer; the storage layer is used for collecting original user data in real time and accessing the original user data to the analysis layer through the unified data bus; the analysis layer is used for acquiring original user data and analyzing the original user data in real time, the invention utilizes the probe equipment to acquire the MAC address of the mobile terminal in a radiation range, and carries out modeling analysis by combining the acquired data with the specific application requirements of public security criminal investigation, thereby integrating the investigation thinking, habits, methods and requirements of a commander, a researcher and a detector in the actual investigation activity into a system and carrying out a brand-new investigation hand for searching and tracking criminal suspects by signals.
Description
Technical Field
The invention relates to the technical field of criminal investigation application of big data, in particular to a criminal investigation application system and method based on WIFI big data.
Background
With the development of the urban informatization degree and the maturity of the intelligent terminal equipment technology, the WIFI can be used for signal acquisition and is also recognized as a new investigation means by the public security department. Police affair application construction such as data collision, fence early warning, track tracking and the like is carried out based on a big data technology, investigation thinking, habits, methods and requirements of a commander, a researcher and a detector in actual investigation activities are integrated into a system, development directions of service police affairs of brand-new investigation means are actively explored, the situation that the investigation work method is single is changed, the police affair mode is promoted to be changed from 'service driving' to 'data perception, investigation and prediction', and the development directions of future police affair reform are actively explored.
Disclosure of Invention
The invention aims to provide a criminal investigation application system and method based on WIFI big data in order to solve the problems of single investigation working method, large workload of manually extracting features and application of artificial subjective factors to criminal investigation; the invention utilizes the probe equipment to collect the MAC address of the mobile terminal in the radiation range, carries out modeling analysis by combining the collected data with the specific application requirements of public security criminal investigation, integrates the investigation thinking, habits, methods and requirements of commanders, judges and inspectors in the actual investigation activities into a system, and carries out a brand-new investigation hand for searching and tracking criminal suspects by signals;
the purpose of the invention can be realized by the following technical scheme: a criminal investigation application system based on WIFI big data comprises a collection layer, a storage layer, an analysis layer and an application layer;
the acquisition layer is used for acquiring and recording original user data and sending the original user data to the storage layer; the storage layer is used for collecting original user data in real time and accessing the original user data to the analysis layer through the unified data bus; the analysis layer is used for acquiring original user data and performing real-time data analysis on the original user data, and the specific process is as follows: building a big data computing platform through hadoop, performing standard SQL distributed data computing and mining by using Hive, performing real-time data stream analysis and computation by Spark, and sending the analysis result to an application layer for display; and the application layer performs data application on the criminal investigation business requirements through a big data technology.
The storage layer establishes distributed mass data retrieval service through the elastic search and performs unified storage of data through an HDFS distributed database and an HBase database.
Preferably, the data application of the application layer specifically includes: the method comprises the steps of fusing and deeply mining mass data through a big data technology, taking criminal investigation actual combat as a leading project, carrying out difference comparison and sequencing on classified data aiming at high-dimensional complex big data clustering analysis and data collision algorithm research, analyzing other overall relations and incidence relations, and establishing a data analysis research and judgment model, wherein the data analysis research and judgment model comprises fence early warning, data collision, track tracking and multi-functional data real-time application of searching for the same pedestrian.
Preferably, the acquisition layer is also provided with monitoring equipment in each monitoring area in advance and captures the MAC address of the mobile terminal passing through the radiation range through the monitoring equipment; the monitoring device comprises probe equipment with an MAC acquisition function, front-end equipment with a WIFI probe function and an acquisition module for acquiring and recording original user data.
Preferably, the acquisition layer also registers the device model of the monitoring device, the fixed position and the longitude and latitude data.
Preferably, the original user data includes a MAC address, a timestamp, and geographical location information; the MAC addresses correspond to different monitoring devices, namely the different monitoring devices correspond to unique MAC addresses; the time stamp is the time point when the acquisition module acquires the original user data; the geographical position information is the geographical position information of the WIFI probe, namely the geographical position information of the monitoring area.
A criminal investigation application method based on WIFI big data is characterized by comprising the following steps:
s1: data acquisition: acquiring and recording original user data through monitoring equipment which is installed in each monitoring area in advance; the monitoring equipment comprises probe equipment with an MAC (media access control) acquisition function, front-end equipment with a WIFI (wireless fidelity) probe function and an acquisition module for acquiring and recording original user data, wherein the original user data comprises an MAC address, a timestamp and geographical position information; the MAC addresses correspond to different monitoring devices, namely the different monitoring devices correspond to unique MAC addresses; the time stamp is the time point when the acquisition module acquires the original user data; the geographical position information is the geographical position information of the WIFI probe;
s2: data storage: establishing distributed mass data retrieval service for the original user data in the S1 through an Elasticissearch, and performing unified storage on the data through an HDFS distributed database and an HBase database;
s3: and (3) data analysis: analyzing the original user data stored in S2, building a big data computing platform through hadoop, computing and mining standard SQL distributed data by using Hive, analyzing and computing real-time data stream by Spark and sending the analyzed result to an application layer for display;
s4: application display: the method comprises the steps of fusing and deeply mining mass data through a big data technology, taking criminal investigation actual combat as a leading project, carrying out difference comparison and sequencing on classified data aiming at high-dimensional complex big data cluster analysis and data collision algorithm research, analyzing other overall relations and incidence relations, and establishing a data analysis and study model.
Compared with the prior art, the invention has the beneficial effects that:
1. the invention realizes the preprocessing of the original user data, is compatible with the information of equipment of multiple manufacturers, saves the storage space and improves the operation speed;
2. the invention combines the concrete application requirements of public security criminal investigation to carry out modeling analysis, integrates the investigation thinking, habits, methods and requirements of commanders, judges and investigators in the actual investigation activities into a system, and carries out a brand-new investigation means for searching and tracking criminal suspects by signals.
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In order to facilitate understanding for those skilled in the art, the present invention will be further described with reference to the accompanying drawings.
FIG. 1 is a functional block diagram of the present invention;
FIG. 2 is an overall flow chart of the present invention.
Detailed Description
The technical solutions of the present invention will be described clearly and completely with reference to the following embodiments, and it should be understood that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Referring to fig. 1-2, a criminal investigation application system and method based on WIFI big data includes an acquisition layer, a storage layer, an analysis layer and an application layer;
the acquisition layer, before the terminal device accesses the AP, the terminal device and the AP need to send some plaintext data packets to identify their respective existence, and the data packets contain the MAC address information of the terminal; meanwhile, the basic data such as the longitude and latitude, the detection time, the terminal type, the brand and the like of the AP equipment are also included; for the condition of accessing wireless AP equipment of a plurality of different manufacturers, a UDP packet receiving and analyzing technology based on AP probe modules of different manufacturers is adopted to realize the analysis of data sent by the AP equipment probe modules of different manufacturers; in addition, due to the fact that the number of wireless AP equipment is large, the amount of received probe data is large, dynamic expansion is achieved by the aid of a UDP-based distributed cluster, and receiving and analyzing of massive AP probe data are met;
the storage layer adopts three systems of HDFS, HBase and elastic search to uniformly store data; the HDFS is the basis of data storage management in a Hadoop system; the HDFS distributed advantage is fully utilized, the HDFS is used as a basic file storage platform, the HDFS can be well expanded and cleaned for continuously growing big data, a consistency model of the file is simplified, and a high-throughput application program data access function is provided through streaming data access; in the face of mass data query, very high requirements are put forward on data structure design and performance optimization of a system, and a traditional database can hardly complete multi-condition query; in order to realize mass data second-round query, the system adopts an HBase database for data which needs random access and real-time reading and writing, establishes distributed mass data retrieval service based on the Elasticissearch, serves as a query inlet of an HBase data warehouse, and realizes result return within a few seconds; HBase is a distributed database with high reliability, high performance, column orientation, scalability and real-time reading and writing; the method comprises the steps of utilizing a Hadoop HDFS as a basic file storage system, utilizing Hadoop MapReduce to process mass data in HBase, and utilizing a Zookeeper as distributed cooperative service; in addition, the HBase technology can build a large-scale structured storage cluster on a low-cost PC Server, so that the system has PB-level data storage capacity and can save system capital investment; in the system, considering that the data volume is huge, the requirements on the performance and the storage space of the distributed server nodes are high, and the LZO compression technology is adopted to compress the original data to about 12 percent, so that the storage resources are reduced by 78 percent;
the analysis layer is used for building a big data computing platform based on hadoop, performing standard SQL distributed data computing and mining by using Hive, and performing real-time data stream analysis and computing based on Spark to support complex data mining algorithms and graph computing algorithms, such as computation and analysis of close persons and pedestrians;
the application layer adopts an advanced big data technology to realize fusion and deep mining of mass data, the project is dominated by criminal investigation actual combat, the classified data are subjected to difference comparison and sequencing aiming at high-dimensional complex big data cluster analysis and data collision algorithm research, other overall relations and incidence relations are analyzed, a data analysis research and judgment model is established, fence early warning, data collision, trajectory tracking and multi-functional data real-time application of searching for the same pedestrian are supported, and auxiliary decision information is provided for investigation, research and judgment and case analysis;
example 1: presetting a designated area, scanning a preset mobile terminal target in the designated area in real time, if so, acquiring a signal of the MAC, acquiring position information in the signal, and sending target MAC information to the platform to form an alarm;
processing according to the collision area selected by the map frame to generate an area data set, performing data collision by utilizing the and, or, non-or combined relation between sets, and analyzing an effective data result through the data collision. The collision analysis provides the function selection supporting the generation of a set support and/or non-self-defined set on a panel after the selection of the map is successful in the area selection of the map frame each time. Mass data screening is carried out through MAC address collision, and case handling efficiency is improved;
and carrying out track analysis on any mobile phone MAC which enters the WIFI coverage range. For a specified MAC address, after entering a certain WIFI coverage, acquiring a WIFI acquisition equipment MAC information set accessed by the mobile phone according to a time sequence, and displaying a behavior track of the mobile phone on a map through the set;
and (3) searching the MAC address based on two dimensions of AP (access point) place and time, calculating and analyzing whether different MACs have the same behavior track at the same time or not, and searching the same person.
Criminal investigation application method based on WIFI big data
And S1, data acquisition: and installing front-end equipment with a WIFI probe function in each monitoring area in advance. Capturing the MAC address of the mobile terminal passing through the radiation range by the front-end equipment;
a user can place equipment in a monitored area according to actual conditions, and original user data comprises an MAC address, a timestamp and geographical position information; the MAC address corresponds to different devices, namely different devices correspond to a unique MAC address; the time stamp is the time point when the acquisition module acquires the original user data; the geographical position information is the geographical position information of the WIFI probe, namely the geographical position information of the monitoring area where the equipment corresponding to the original user data is located.
S2 data storage: storing the user data transmitted in S1; s2 is connected to the analysis module S3 for storing and transmitting the user data to the data classification.
S3 data analysis: performing data modeling such as correlation analysis on user data; the data analysis is connected to S4 and the analysis result is sent to the service exhibition.
The correlation analysis specifically comprises: whether the same-pedestrian condition and the close-pedestrian condition exist can be analyzed through the data related to the co-occurrence of the crowd and the cosine, and the personnel information and the record of the same-pedestrian are analyzed;
and (3) anomaly analysis: obtaining abnormal records of high risk groups and places through three-dimensional abnormal analysis of the places, the time and the groups;
frequency analysis: through dividing the occurrence frequency and time of the crowd, analyzing to obtain the frequent-going place and frequent-place information of the crowd, and indirectly judging the occupational information of the crowd;
and (3) condition analysis: and analyzing information such as clothes and eating habits of people, interest and entertainment and the like according to the AP data, the AP tags and the third party tags.
S4 application show: the method is characterized in that an advanced big data technology is adopted to realize fusion and deep mining of mass data, the project is dominated by criminal investigation actual combat, the classified data are subjected to difference comparison and sequencing aiming at high-dimensional complex big data cluster analysis and data collision algorithm research, other overall relations and incidence relations are analyzed, a data analysis research and judgment model is established, fence early warning, data collision, trajectory tracking and multifunctional data real-time application of searching the same pedestrian are supported, and auxiliary decision information is provided for investigation, research and judgment and case analysis.
When the invention is used, the acquisition layer acquires and records original user data and sends the original user data to the storage layer; the storage layer collects original user data in real time and accesses the analysis layer through a unified data bus; the analysis layer acquires original user data and performs real-time data analysis on the original user data, a big data computing platform is built through hadoop, standard SQL distributed data computing and mining are performed through Hive, real-time data stream analysis and computing are performed through Spark, and an analysis result is sent to the application layer to be displayed; the application layer carries out data application on criminal investigation business requirements through a big data technology; the method and the device realize the preprocessing of the original user data, are compatible with the information of equipment of multiple manufacturers, save the storage space and improve the operation speed; modeling analysis is carried out by combining specific application requirements of public security criminal investigation, investigation thinking, habits, methods and requirements of commanders, judges and investigators in actual investigation activities are merged into a system, and a brand-new investigation means for searching and tracking criminal suspects by signals is carried out.
The preferred embodiments of the invention disclosed above are intended to be illustrative only. The preferred embodiments are not intended to be exhaustive or to limit the invention to the precise forms disclosed. Obviously, many modifications and variations are possible in light of the above teaching. The embodiments were chosen and described in order to best explain the principles of the invention and the practical application, to thereby enable others skilled in the art to best utilize the invention. The invention is limited only by the claims and their full scope and equivalents.
Claims (7)
1. A criminal investigation application system based on WIFI big data is characterized by comprising an acquisition layer, a storage layer, an analysis layer and an application layer;
the acquisition layer is used for acquiring and recording original user data and sending the original user data to the storage layer; the storage layer is used for collecting original user data in real time and accessing the original user data to the analysis layer through the unified data bus; the analysis layer is used for acquiring original user data and performing real-time data analysis on the original user data, and the specific process is as follows: building a big data computing platform through hadoop, performing standard SQL distributed data computing and mining by using Hive, performing real-time data stream analysis and computation by Spark, and sending the analysis result to an application layer for display; and the application layer performs data application on the criminal investigation business requirements through a big data technology.
2. The WIFI big data based criminal investigation application system of claim 1, wherein the storage layer establishes a distributed mass data retrieval service through an Elasticissearch and performs unified data storage through an HDFS distributed database and an HBase database.
3. The criminal investigation application system based on WIFI big data as claimed in claim 1, wherein the data application of the application layer is specifically: the method comprises the steps of fusing and deeply mining mass data through a big data technology, taking criminal investigation actual combat as a leading project, carrying out difference comparison and sequencing on classified data aiming at high-dimensional complex big data clustering analysis and data collision algorithm research, analyzing other overall relations and incidence relations, and establishing a data analysis research and judgment model, wherein the data analysis research and judgment model comprises fence early warning, data collision, track tracking and multi-functional data real-time application of searching for the same pedestrian.
4. The criminal investigation application system based on WIFI big data as claimed in claim 1, wherein the acquisition layer is further provided with a monitoring device in each monitoring area in advance and captures a passing mobile terminal MAC address in a radiation range through the monitoring device; the monitoring device comprises probe equipment with an MAC acquisition function, front-end equipment with a WIFI probe function and an acquisition module for acquiring and recording original user data.
5. The criminal investigation application system based on WIFI big data as claimed in claim 2, wherein the collection layer also registers the device model and the fixed location and longitude and latitude data of the monitoring device.
6. A WIFI big data based criminal investigation application system according to claim 3, characterized in that the original user data includes MAC address, timestamp and geographical location information; the MAC addresses correspond to different monitoring devices, namely the different monitoring devices correspond to unique MAC addresses; the time stamp is the time point when the acquisition module acquires the original user data; the geographical position information is the geographical position information of the WIFI probe, namely the geographical position information of the monitoring area.
7. A criminal investigation application method based on WIFI big data is characterized by comprising the following steps:
s1: data acquisition: acquiring and recording original user data through monitoring equipment which is installed in each monitoring area in advance; the monitoring equipment comprises probe equipment with an MAC (media access control) acquisition function, front-end equipment with a WIFI (wireless fidelity) probe function and an acquisition module for acquiring and recording original user data, wherein the original user data comprises an MAC address, a timestamp and geographical position information; the MAC addresses correspond to different monitoring devices, namely the different monitoring devices correspond to unique MAC addresses; the time stamp is the time point when the acquisition module acquires the original user data; the geographical position information is the geographical position information of the WIFI probe;
s2: data storage: establishing distributed mass data retrieval service for the original user data in the S1 through an Elasticissearch, and performing unified storage on the data through an HDFS distributed database and an HBase database;
s3: and (3) data analysis: analyzing the original user data stored in S2, building a big data computing platform through hadoop, computing and mining standard SQL distributed data by using Hive, analyzing and computing real-time data stream by Spark and sending the analyzed result to an application layer for display;
s4: application display: the method comprises the steps of fusing and deeply mining mass data through a big data technology, taking criminal investigation actual combat as a leading project, carrying out difference comparison and sequencing on classified data aiming at high-dimensional complex big data cluster analysis and data collision algorithm research, analyzing other overall relations and incidence relations, and establishing a data analysis and study model.
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