CN110971476A - Method and system for analyzing file downloading behavior and intelligent terminal - Google Patents
Method and system for analyzing file downloading behavior and intelligent terminal Download PDFInfo
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- CN110971476A CN110971476A CN201811147518.2A CN201811147518A CN110971476A CN 110971476 A CN110971476 A CN 110971476A CN 201811147518 A CN201811147518 A CN 201811147518A CN 110971476 A CN110971476 A CN 110971476A
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L43/00—Arrangements for monitoring or testing data switching networks
- H04L43/10—Active monitoring, e.g. heartbeat, ping or trace-route
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L43/00—Arrangements for monitoring or testing data switching networks
- H04L43/16—Threshold monitoring
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L63/00—Network architectures or network communication protocols for network security
- H04L63/02—Network architectures or network communication protocols for network security for separating internal from external traffic, e.g. firewalls
- H04L63/0227—Filtering policies
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L63/00—Network architectures or network communication protocols for network security
- H04L63/14—Network architectures or network communication protocols for network security for detecting or protecting against malicious traffic
- H04L63/1408—Network architectures or network communication protocols for network security for detecting or protecting against malicious traffic by monitoring network traffic
- H04L63/1416—Event detection, e.g. attack signature detection
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L63/00—Network architectures or network communication protocols for network security
- H04L63/14—Network architectures or network communication protocols for network security for detecting or protecting against malicious traffic
- H04L63/1408—Network architectures or network communication protocols for network security for detecting or protecting against malicious traffic by monitoring network traffic
- H04L63/1425—Traffic logging, e.g. anomaly detection
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L67/00—Network arrangements or protocols for supporting network services or applications
- H04L67/01—Protocols
- H04L67/06—Protocols specially adapted for file transfer, e.g. file transfer protocol [FTP]
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L67/00—Network arrangements or protocols for supporting network services or applications
- H04L67/34—Network arrangements or protocols for supporting network services or applications involving the movement of software or configuration parameters
Abstract
The field relates to the field of network data processing, in particular to a method and a system for analyzing file downloading behaviors and an intelligent terminal. The method comprises the following steps: monitoring the downloading behavior within a first threshold time range, and acquiring downloading log data of an appointed user within the first threshold time range; processing the downloaded log data; performing statistical analysis on the processed download log data, and judging the type of the user download behavior according to the statistical analysis result; and analyzing the downloading behavior according to the statistical analysis result and the type of the user downloading behavior, and judging whether the user downloading behavior violates rules. The real-time automatic monitoring of the file downloading behavior of the staff in the company is realized through the computer, a large amount of manpower and material resources are not required to be consumed, the safety of the company document is effectively guaranteed, and the property of the company is protected.
Description
Technical Field
The field relates to the field of network data processing, in particular to a method and a system for analyzing file downloading behaviors and an intelligent terminal.
Background
With the rapid development of networking and informatization, security and confidentiality work faces new situations and new problems for enterprises, particularly security-related units, and confidentiality management work particularly in security-related units needs to be paid more attention. A large number of electronic documents are circulated inside every day in a unit, and if no good internal control measures exist, huge risk of disclosure can be brought.
At present, enterprises manage the confidential electronic documents in a mode of combining a confidential management system and a management system so as to realize the management and control of the divulgence risk. All newly-built electronic documents need to be subjected to file privacy determination through a privacy determination management system, and circulation of the confidential documents is controlled in a mode of leading and checking layer by layer. The method has great passivity and lacks of control on malicious illegal operation; meanwhile, users with authority can download company internal files in a large batch, then the internal files are sent to other people, in addition, as long as the users receive electronic documents, the users with authority can open and browse whether or not, the illegal behaviors bring great risk of disclosure, the management and control are difficult by means of manual management, and the requirement of a unit on risk management of disclosure cannot be met completely.
Disclosure of Invention
The invention provides an analysis method and system for file downloading behaviors and an intelligent terminal, and aims to solve the problems that a large number of internal files cannot be downloaded by internal staff of a monitoring company in real time and automatically, manual monitoring consumes manpower and material resources, efficiency is low, and great risk of disclosure cannot be prevented.
In order to solve the technical problem, the embodiment of the invention adopts the following technical scheme:
in one aspect, an embodiment of the present invention provides a method for analyzing a file downloading behavior, where the method includes:
monitoring the downloading behavior within a first threshold time range, and acquiring downloading log data of an appointed user within the first threshold time range; processing the downloaded log data; performing statistical analysis on the processed download log data, and judging the type of the user download behavior according to the statistical analysis result; and analyzing the downloading behavior according to the statistical analysis result and the type of the user downloading behavior, and judging whether the user downloading behavior violates rules.
Furthermore, the user performs downloading behavior analysis once after downloading each time.
Furthermore, the downloading behavior analysis is carried out once after the set time condition is met.
Further, before processing the download log data, the method further comprises the step of performing deduplication filtering on invalid download data in the download log data.
Further, the invalid download data comprises a plurality of downloads of the same attribute file by the user within a second threshold time.
Further, the second threshold time is 1 minute.
Further, the statistical analysis includes calculating one or more of a mathematical sample variance, and expected value of the download log data corresponding to the download behavior of the user within the first threshold time range.
In a second aspect, an embodiment of the present invention further provides an analysis system for file downloading behavior, including: the monitoring module is used for monitoring the downloading behavior within a first threshold time range; the log acquisition module is used for acquiring downloaded log data; the data processing module is used for processing the downloaded log data; the data statistics module is used for carrying out statistics analysis on the processed download log data; the analysis and judgment module is used for judging whether the downloading behavior of the user is illegal;
further, the log acquisition module stores the acquired download log data to the HDFS;
further, the data processing module processes data by using a SparkStreaming technology;
further, the data processing module comprises a filtering unit, and the filtering unit is used for filtering the downloaded log data acquired by the log acquisition module, extracting effective data information, and finally generating a Hive table to be stored in the HDFS;
further, the data processing module reads data from Hive based on a Spark data analysis engine and converts the data into a DataFrame;
further, the data processing module comprises a deduplication unit, and performs deduplication processing on the data in the generated DataFrame;
further, the data statistics module calculates one or more of a mathematical sample variance, a variance and an expected value of the downloading behavior of each user within a first threshold time range by using a spark sql module.
In a third aspect, an embodiment of the present invention provides an intelligent terminal, where an analysis system for the file downloading behavior is provided on the intelligent terminal.
The method, the system and the intelligent terminal for analyzing the file downloading behavior have the following beneficial effects that: monitoring the downloading behavior within a first threshold time range, and acquiring downloading log data of an appointed user within the first threshold time range; processing the downloaded log data; performing statistical analysis on the processed download log data, and judging the type of the user download behavior according to the statistical analysis result; and analyzing the downloading behavior according to the statistical analysis result and the type of the user downloading behavior, and judging whether the user downloading behavior is illegal. The real-time automatic monitoring of the file downloading behavior of the staff in the company is realized through the computer, a large amount of manpower and material resources are not required to be consumed, the safety of the company document is effectively guaranteed, and the property of the company is protected.
Drawings
FIG. 1 is a flowchart illustrating a method for analyzing file downloading behavior according to an embodiment of the present invention;
fig. 2 is a schematic diagram of an analysis system for file downloading behavior according to an embodiment of the present invention.
Detailed Description
The technical solutions in the present invention will be described clearly and completely with reference to the accompanying drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only some embodiments of the present invention, not all embodiments.
The embodiment of the invention discloses a method for analyzing file downloading behaviors, wherein a flow chart of the method is shown in figure 1 and comprises the following steps:
s1: monitoring the downloading behavior within a first threshold time range, and acquiring downloading log data of an appointed user within the first threshold time range;
monitoring the downloading behavior of a specified user within a first threshold time range, and generating downloading log data of the user, wherein the downloading log data has a format of a clear log and information needing to be stored is determined for convenience of statistics; the download log data of the user comprises identity information of the user, download amount of the file, attribute information of the file, information of download behavior and the like;
s2: processing the downloaded log data;
before processing the downloaded log data, carrying out duplicate removal and filtration on invalid downloaded data in the downloaded log data; the invalid download data comprises data which are not used in statistical analysis and multiple download data of the same attribute file within a second threshold time by the user; the second threshold time can be 1 minute, and can also be set by self-definition;
storing the downloaded log data on the HDFS, processing the data by using a big data technology, filtering the downloaded log data in the process of reading and storing the downloaded log data to the HDFS, removing data which are not used in statistical analysis, processing the format of the downloaded log data, extracting data information which is useful for calculation, and finally storing the data information into a Hive table; the processing program is based on a Spark engine, the download log data are read from the Hive table, the download log data are converted into a DataFrame after being read, then the download records of each user are subjected to deduplication processing as required, and repeated download data of the same attribute file are removed within a second threshold time; processing the downloaded log data in real time by using a spark streaming technology;
s3: performing statistical analysis on the processed download log data, and judging the type of the user download behavior according to the statistical analysis result;
adopting a spark sql module to calculate one or more of a mathematical sample variance, a variance and an expected value of the downloading behavior of each user in a first threshold time range for the processed downloading log data; the first threshold time range can be set in a self-defined mode; analyzing the variance, variance and expected value of the mathematical sample, classifying the downloading behaviors of the corresponding users according to the analysis result, and distinguishing the downloading behaviors into four types, namely intermittent mass downloading, uniform mass downloading and the like; each type of downloading behavior corresponds to different threshold ranges of downloading amount;
s4: analyzing the downloading behavior according to the statistical analysis result and the type of the user downloading behavior, and judging whether the user downloading behavior is illegal;
each type of user downloading behavior corresponds to different threshold ranges of downloading amount; the downloading behavior analysis comprises the steps of analyzing and comparing a corresponding statistical analysis result of a user with a downloading amount threshold range corresponding to the type of the downloading behavior of the user, and judging whether the downloading behavior of the user is illegal or not; if the corresponding statistical analysis result of the user exceeds the threshold range of the downloading amount corresponding to the downloading behavior type of the user, judging that the downloading behavior of the user is illegal;
if the real-time analysis is carried out, carrying out one-time downloading behavior analysis after each downloading by the user;
and if the analysis is timing analysis, performing one-time downloading behavior analysis after the set time condition is met.
The embodiment of the invention discloses an analysis system for file downloading behaviors, which comprises the following steps: the system comprises a monitoring module 1, a log obtaining module 2, a data processing module 3, a data statistics module 4 and an analysis and judgment module 5;
the monitoring module 1 is used for monitoring the downloading behavior within a first threshold time range; the monitoring module 1 monitors the downloading behavior of a specified user within a first threshold time range, and generates the downloading log data of the user; the download log data of the user comprises identity information of the user, download amount of the file, attribute information of the file, information of download behavior and the like;
the log obtaining module 2 is used for obtaining downloaded log data; the log acquisition module 2 stores the acquired downloaded log data to the HDFS; the downloaded log data acquired by the log acquisition module 2 has a format for determining a log and information needing to be stored;
the data processing module 3 is used for processing the downloaded log data; the data processing module 3 comprises a filtering unit 31 and a deduplication unit 32; the data processing module 3 processes the data in real time by using a spark streaming technology; the filtering unit 31 filters the downloaded log data acquired by the log acquiring module 2, extracts effective data information, and finally generates a Hive table to be stored in the HDFS; reading data from Hive based on Spark data analysis engine, and converting the data into DataFrame; the deduplication unit 32 performs deduplication processing on the generated data frame;
the data statistical module 4 is used for carrying out statistical analysis on the processed download log data; the data statistics module 4 calculates one or more of a mathematical sample variance, a variance and an expected value of a downloading behavior of each user in a first threshold time range by using a spark sql module;
the analysis and judgment module 5 is used for judging whether the downloading behavior of the user is illegal; the analysis and judgment module 5 performs analysis and judgment by combining the statistical result of the data statistical module 4 and the download log data of the log acquisition module 2, and judges whether the corresponding user download behavior is illegal.
It is to be understood that the present invention has been described with reference to certain embodiments, and that various changes in the features and embodiments, or equivalent substitutions may be made therein by those skilled in the art without departing from the spirit and scope of the invention. In addition, many modifications may be made to adapt a particular situation or material to the teachings of the invention without departing from the essential scope thereof. Therefore, it is intended that the invention not be limited to the particular embodiment disclosed, but that the invention will include all embodiments falling within the scope of the appended claims.
Claims (15)
1. A method for analyzing file downloading behavior, the method comprising:
monitoring the downloading behavior within a first threshold time range, and acquiring downloading log data of an appointed user within the first threshold time range;
processing the downloaded log data;
performing statistical analysis on the processed download log data, and judging the type of the user download behavior according to the statistical analysis result;
and analyzing the downloading behavior according to the statistical analysis result and the type of the user downloading behavior, and judging whether the user downloading behavior violates rules.
2. The method for analyzing file downloading behavior according to claim 1, wherein: and the user performs downloading behavior analysis once after downloading each time.
3. The method for analyzing file downloading behavior according to claim 1, wherein: and performing downloading behavior analysis once when the set time condition is met.
4. The method for analyzing file downloading behavior according to claim 1, wherein: before processing the download log data, the method also comprises the step of carrying out deduplication filtration on invalid download data in the download log data.
5. The method for analyzing file downloading behavior according to claim 4, wherein: the invalid download data comprises a plurality of times of download data of the same attribute file within a second threshold time.
6. The method for analyzing file downloading behavior according to claim 5, wherein: the second threshold time is 1 minute.
7. The method for analyzing file downloading behavior according to claim 1, wherein: the statistical analysis includes calculating one or more of a mathematical sample variance, and expected value of the download log data corresponding to the download behavior of the user over a first threshold time range.
8. A system for analyzing file downloading behavior, comprising:
the monitoring module is used for monitoring the downloading behavior within a first threshold time range;
the log acquisition module is used for acquiring downloaded log data;
the data processing module is used for processing the downloaded log data;
the data statistics module is used for carrying out statistics analysis on the processed download log data;
and the analysis and judgment module is used for judging whether the downloading behavior of the user is illegal.
9. The system for analyzing file downloading behavior according to claim 8, wherein: and the log acquisition module stores the acquired download log data to the HDFS.
10. The system for analyzing file downloading behavior according to claim 8, wherein: the data processing module processes data by using a spark streaming technology.
11. The system for analyzing file downloading behavior according to claim 8, wherein: the data processing module comprises a filtering unit, and the filtering unit is used for filtering the downloaded log data acquired by the log acquisition module, extracting effective data information, finally generating a Hive table and storing the Hive table to the HDFS.
12. The system for analyzing file downloading behavior according to claim 11, wherein: and the data processing module reads data from Hive based on a Spark data analysis engine and converts the data into a DataFrame.
13. The system for analyzing file downloading behavior according to claim 12, wherein: the data processing module comprises a deduplication unit and is used for performing deduplication processing on the generated data frame.
14. The system for analyzing file downloading behavior according to claim 8, wherein: the data statistics module adopts a spark sql module to calculate one or more of mathematical sample variance, variance and expectation value of each user downloading behavior within a first threshold time range.
15. An intelligent terminal, characterized in that, the intelligent terminal is provided with the file downloading behavior analysis system of any one of claims 8-14.
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111683102A (en) * | 2020-06-17 | 2020-09-18 | 绿盟科技集团股份有限公司 | FTP behavior data processing method, and method and device for identifying abnormal FTP behavior |
Citations (12)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102622443A (en) * | 2012-03-13 | 2012-08-01 | 北京邮电大学 | Customized screening system and method for microblog |
| CN102946319A (en) * | 2012-09-29 | 2013-02-27 | 焦点科技股份有限公司 | System and method for analyzing network user behavior information |
| CN105162614A (en) * | 2015-06-19 | 2015-12-16 | 成都艾尔普科技有限责任公司 | Network user behavior auditing and responsibility management method |
| CN105528535A (en) * | 2015-12-25 | 2016-04-27 | 北京奇虎科技有限公司 | Log information based user behavior analysis method and apparatus |
| CN105868256A (en) * | 2015-12-28 | 2016-08-17 | 乐视网信息技术（北京）股份有限公司 | Method and system for processing user behavior data |
| CN106097043A (en) * | 2016-06-01 | 2016-11-09 | 腾讯科技（深圳）有限公司 | The processing method of a kind of credit data and server |
| CN106789885A (en) * | 2016-11-17 | 2017-05-31 | 国家电网公司 | User's unusual checking analysis method under a kind of big data environment |
| CN106982150A (en) * | 2017-03-27 | 2017-07-25 | 重庆邮电大学 | A kind of mobile Internet user behavior analysis method based on Hadoop |
| CN107124330A (en) * | 2017-05-11 | 2017-09-01 | 北京古盘创世科技发展有限公司 | Data download control method and system |
| CN107341033A (en) * | 2017-06-30 | 2017-11-10 | 百度在线网络技术（北京）有限公司 | A kind of data statistical approach, device, electronic equipment and storage medium |
| CN108304723A (en) * | 2018-01-17 | 2018-07-20 | 链家网（北京）科技有限公司 | A kind of anomaly detection method and device |
| CN108376158A (en) * | 2018-02-09 | 2018-08-07 | 北京航智信息技术有限公司 | The analysis method of student's mobile terminal user behaviors log, apparatus and system |
-
2018
- 2018-09-29 CN CN201811147518.2A patent/CN110971476A/en active Pending
Patent Citations (12)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102622443A (en) * | 2012-03-13 | 2012-08-01 | 北京邮电大学 | Customized screening system and method for microblog |
| CN102946319A (en) * | 2012-09-29 | 2013-02-27 | 焦点科技股份有限公司 | System and method for analyzing network user behavior information |
| CN105162614A (en) * | 2015-06-19 | 2015-12-16 | 成都艾尔普科技有限责任公司 | Network user behavior auditing and responsibility management method |
| CN105528535A (en) * | 2015-12-25 | 2016-04-27 | 北京奇虎科技有限公司 | Log information based user behavior analysis method and apparatus |
| CN105868256A (en) * | 2015-12-28 | 2016-08-17 | 乐视网信息技术（北京）股份有限公司 | Method and system for processing user behavior data |
| CN106097043A (en) * | 2016-06-01 | 2016-11-09 | 腾讯科技（深圳）有限公司 | The processing method of a kind of credit data and server |
| CN106789885A (en) * | 2016-11-17 | 2017-05-31 | 国家电网公司 | User's unusual checking analysis method under a kind of big data environment |
| CN106982150A (en) * | 2017-03-27 | 2017-07-25 | 重庆邮电大学 | A kind of mobile Internet user behavior analysis method based on Hadoop |
| CN107124330A (en) * | 2017-05-11 | 2017-09-01 | 北京古盘创世科技发展有限公司 | Data download control method and system |
| CN107341033A (en) * | 2017-06-30 | 2017-11-10 | 百度在线网络技术（北京）有限公司 | A kind of data statistical approach, device, electronic equipment and storage medium |
| CN108304723A (en) * | 2018-01-17 | 2018-07-20 | 链家网（北京）科技有限公司 | A kind of anomaly detection method and device |
| CN108376158A (en) * | 2018-02-09 | 2018-08-07 | 北京航智信息技术有限公司 | The analysis method of student's mobile terminal user behaviors log, apparatus and system |
Non-Patent Citations (2)
| Title |
|---|
| 唐振贵: "针对分布式批量下载的电子资源防控系统的研究", 《图书馆学研究》 * |
| 李伟伟: "专网应用系统用户行为监控系统设计与实现", 《中国优秀硕士学位论文全文数据库》 * |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111683102A (en) * | 2020-06-17 | 2020-09-18 | 绿盟科技集团股份有限公司 | FTP behavior data processing method, and method and device for identifying abnormal FTP behavior |
| CN111683102B (en) * | 2020-06-17 | 2022-12-06 | 绿盟科技集团股份有限公司 | FTP behavior data processing method, and method and device for identifying abnormal FTP behavior |
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