CN104392297A - Method and system for realizing non-business process irregularity detection in large data environment - Google Patents
Method and system for realizing non-business process irregularity detection in large data environment Download PDFInfo
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Abstract
The invention relates to a method for realizing non-business process irregularity detection in a large data environment. The method comprises steps: a system introduces a standardization process model and builds a business object type; the system associates the business object type and the standardization process model; the system acquires standard data of a non-business process; the system carries out process recovery on the data of the standard data; and the system carries out irregularity analysis on the standard data after recovery. The invention also relates to a system for realizing non-business process irregularity detection in a large data environment, which comprises a standardization process definition module, a process association module, a process recovery and irregularity definition module, a data extraction module and a process recovery and irregularity analysis module. by adopting the method and the system of the invention, irregularities in the non-business handling process by an enterprise can be detected in real time, the business activity monitoring field is further expanded, the structure is simple, expansibility is good, the detection efficiency is high, portability is strong, and a wider application range is provided.
Description
Technical field
The present invention relates to business process monitoring field, particularly relate to flow process unlawful practice detection field, under specifically referring to a kind of large data environment, realize the method and system that the unlawful practice of non-traffic flow process detects.
Background technology
Along with the informationalized continuous propelling of every profession and trade, the automaticity of industry and enterprise is deepened, and most business all achieves information system management, and miscellaneous service flowsheet platform is just for the day to day operation of enterprise provides support.Because the business of the such as industry such as bank, telecommunications is very huge and complicated, in enterprise existing a large amount of separately independently in operation systems and same business mutually isolated various numerous and diverse application program bring problems to daily operation and IT department:
(1) input and output amount across the operation flow of the different link in the even same center of branch hub is not inconsistent, but is difficult to the abnormal operation that these data differences are caused in location, cannot continue to follow the tracks of storage operation yet;
(2) analysis of manufacturing capability forms need the work expending several hours, and from multiple system, extract business datum, during this, service condition there occurs change;
(3) find to cause the reason of the system failure to be that disk space causes daily record to write not after earnestly having investigated two or three hours;
(4) system pressure increases suddenly, but does not know that the application in which link consumes resource.
Face these insoluble IT problems, enterprise deals with by building BAM (BAM, Business ActivityMonitoring) platform.BAM is a kind of software engineering for monitoring enterprise operation situation based on Enterprise information integration.BAM provides the real time access to Professional performance index, to improve speed and the efficiency of business running.This term of BAM was proposed by Gartner Group in 2002, and for describing some emerging abilities, some gordian techniquies are put together the situation fundamentally changing operation system by these abilities.
BAM develops the quickest, the most effective means of the senior optimization of business in application integratedtechnology, its aim is the state obtaining operation flow operation in real time, automatically provide objective analysis to report, to improve, to optimize operation flow, it improves high-tech technological layer, also comprises personnel, management layer.The target of BAM is to provide the ability can understanding business event when the service environment of enterprise changes in time, so just can make decision-making timely.By providing real-time information, BAM scheme can reduce cost and accelerate to perform affairs.BAM is by the real-time information of capturing service process flow operation, call BPM to manage operation flow, quality enterprise being possessed required by Agile enterprise, turn of the market can be responded rapidly, adjust business game rapidly, implement operation flow rapidly, according to feedack, operation flow is optimized and revised rapidly simultaneously.
BAM enables business service in service management personnel monitoring enterprise and flow process, make KPI (KPI Key Performance Indicator, KeyPerformance Indicator) associate with actual operation flow itself, and the most important thing is, revise operation flow when service environment changes rapidly or take correct measure.BAM is the complete set solution building true-time operation information board and monitored and warn application program by Web.This technology can make service-user build the warning of real-time interactive information plate and predictability to monitor business service and flow process.Event and warning (non-primary data) are the active forces of a BAM system.Data Collection, lower brill, stop-loss signals, operator's interference and automatic shutdown all belong to the built-in opereating specification of BAM system.BAM system is responsible for following the tracks of, integrating and report main business event, and they all use the integrated of bottom to visit and service data.Usually business intelligence and analytical applications preference use Fat Client browser as user interface in real time.
The general treatment scheme of BAM technology can be described as: first obtain and record data; Next has been important pre-service or the works for the treatment of such as the extraction of data, the integration of clean and mark and data, gathering and expression; Again need the data analysis step that complete, generally include the preprocessing process such as data filtering, data summarization, Data classification or cluster; Finally enter the analysis phase, in this stage, various algorithm and computational tool can be applied in data, want result that is that see or that can make an explanation in the hope of obtaining analyst.But traditional BAM technology generally only supports the gather and analysis to operation flow application data, the monitoring of flow process correlated activation cannot be carried out to the legacy application of a large amount of non-traffic flow process application type, and the critical asset of legacy application often in Course of Enterprise Informationalization, if the process action in legacy application can not be carried out effective monitoring, the meaning of traditional business activity monitoring technology is also very limited.
By strengthening traditional BAM technology to the support of legacy application, BAM technology can realize enterprises, it is integrated that outside is widely applied, monitor and managment, this just must cause needing large data technique to support the mass data to widely applying system monitoring to bring to teach, the problem of Storage and Processing, the treatment and analyses demand of mass data is had higher requirement to traditional BAM technology, therefore require that the data supporting platform of bottom possesses powerful communication (data flowing and exchange) ability, (data are possessed) ability of storage and calculating (data processing) ability, thus ensure user's access of magnanimity, efficient data acquisition and processing (DAP), the accurate Real-Time Sharing of multimode data and the quick response in the face of changes in demand.
Summary of the invention
The object of the invention is the shortcoming overcoming above-mentioned prior art, provide and a kind of to detect in enterprise's non-traffic treatment scheme unlawful practice in real time to further expand BAM field, favorable expandability, detection efficiency is high, realizes the method and system that the unlawful practice of non-traffic flow process detects under improving the large data environment of business Detection job.
To achieve these goals, the method and system realizing non-traffic flow process unlawful practice detection under large data environment of the present invention have following formation:
Realize the method that the unlawful practice of non-traffic flow process detects under this large data environment, its principal feature is, described method comprises the following steps:
(1) system introducing standardization procedural model, and create business object type;
(2) described business object type associates with described standardization procedural model by the system described in;
(3) normal data of the system acquisition non-traffic flow process described in;
(4) system described in carries out process reduction to the data of described normal data;
(5) system described in carries out violation situation analysis to the normal data after reduction.
Further, described system carries out process reduction to the data of described normal data, is specially:
Described system finds corresponding standardization flow process and the normal data of correspondence according to process code.
Further, between described step (4) and step (5), further comprising the steps of:
(4.1) node set that the system described in finds corresponding monitored node set according to corresponding standardization flow process, step lacks inspection node set and wrong order is made unwarranted inspections;
(4.2) system described in judges that whether each normal data is the data of monitor node;
(4.3) if this normal data is the data of monitor node, then continue step (5), otherwise delete this normal data and return step (4.2), until all normal datas judge complete.
Further, described system judges that whether each normal data is the data of monitor node, comprises the following steps:
(4.2.1) whether there is the flow nodes number of each normal data in the monitored node set described in the system described in judges;
If (4.2.2) there is the flow nodes number of each normal data in described monitored node set, then this normal data is the data of monitor node, otherwise this normal data is not the data of monitor node.
Further, after described step (4.4), further comprising the steps of:
(4.5) system described in judges the type that the unlawful practice of each normal data is analyzed.
Further, described system judges to comprise the following steps the type that the unlawful practice of each normal data is analyzed:
(4.5.1) whether the wrong order described in system described in judges is made unwarranted inspections exists the flow nodes number of each normal data in node set, if, then judge that this normal data is as the order entanglement normal data needing to carry out wrong order and make unwarranted inspections, otherwise judge that this normal data is made unwarranted inspections without the need to carrying out wrong order;
(4.5.2) the step disappearance described in the system described in judges checks the flow nodes number that whether there is each normal data in node set, if, then judge that this normal data is as the step disappearance normal data needing to carry out the inspection of step disappearance, otherwise judge that this normal data checks without the need to carrying out step disappearance.
Further, described carries out violation situation analysis to the normal data after reduction, is specially:
Described system is carried out wrong order according to result of determination to described normal data and is made unwarranted inspections or the inspection of step disappearance, and shows check result.
Further, described system is carried out wrong order according to result of determination to described normal data and is made unwarranted inspections or the inspection of step disappearance, comprises the following steps:
(4.6a) the step disappearance flow nodes number related in the system identification step disappearance rule described in;
(4.7a) whether exist in the order entanglement normal data described in the system described in judges and lack flow nodes number identical flow nodes number with step, if so, then continue step (4.7a), otherwise continue step (4.8a);
(4.8a) system described in judges that check result lacks as step.
Further, described system is carried out wrong order according to result of determination to described normal data and is made unwarranted inspections or the inspection of step disappearance, comprises the following steps:
(4.6b) the wrong order sinuous flow journey node number related in the system identification order entanglement rule described in;
(4.7b) whether the order of the operation end time that the order of the operation end time that the order entanglement normal data described in system described in judges is corresponding is corresponding with described wrong order sinuous flow journey node number is consistent, if, then continue step (4.7b), otherwise continue step (4.8b);
(4.8b) system described in judges that check result is as order entanglement.
Further, described system introducing standardization procedural model, is specially:
The procedural model file transform of multiple format is the standardization procedural model of unified standard form and the standardization procedural model described in display by described system.
Further, the standardization procedural model described in described display, is specially:
The standardization procedural model of described system according to two-stage classification system and organizational structure two dimension displays.
Further, between described step (2) and (3), further comprising the steps of:
(2.1) the business object type described in is set to singleton pattern or many cases pattern.
Further, the normal data of described system acquisition non-traffic flow process, is specially:
The data of described system acquisition non-traffic flow process, and the data collected are converted to normal data.
In addition, the present invention realizes the system that the unlawful practice of non-traffic flow process detects under also providing a kind of large data environment, its principal feature is, described system comprises:
Standardization flow process definition module, in order to import standardization procedural model;
Flow process relating module, in order to create business object type, and associates described business object type with described standardization procedural model;
Process reduction and violation definition module, in order to store the also meta-rule for process reduction and the violation rule for violation situation analysis;
The data collected in order to gather the data of non-traffic flow process, and are converted to normal data by data extraction module;
Process reduction and violation analysis module, in order to carry out process reduction to the data of described normal data, and carry out violation situation analysis to the normal data after reduction.
The method and system that the unlawful practice of non-traffic flow process detects are realized under have employed large data environment of the present invention, to employ from Legacy System and directly extract non-traffic data to carry out process reduction and to carry out the method for unlawful practice detection, achieve the monitoring to the operation flow in the application of non-traffic flow process, overcome the defect that traditional BAM technology can only be applied to operation flow application; Simultaneously, system is by using configuration mode to provide good extendability to system component, integrated, the several data source of multiple application under meeting large data environment, several data processing mode, several data analytical model and multiple monitoring represent the integrated requirement of result, rule definition and Function Extension very flexible.The data analysis that system provides has very high real-time, can Fast Monitoring to the data that there is unlawful practice, represent warning in time, substantially increase unlawful practice from response time reaction being detected, the further in-depth of administering for enterprise IT provides solid foundation, has range of application widely.
Accompanying drawing explanation
Fig. 1 is the process flow diagram realizing the method that the unlawful practice of non-traffic flow process detects under large data environment of the present invention.
Embodiment
In order to more clearly describe technology contents of the present invention, conduct further description below in conjunction with specific embodiment.
Refer to Fig. 1, in one embodiment, the method realizing non-traffic flow process unlawful practice detection under large data environment of the present invention comprises the following steps:
(1) system introducing standardization procedural model, and create business object type;
(2) described business object type associates with described standardization procedural model by the system described in;
(3) normal data of the system acquisition non-traffic flow process described in;
(4) system described in carries out process reduction to the data of described normal data;
(5) system described in carries out violation situation analysis to the normal data after reduction.
In a preferred embodiment, described system carries out process reduction to the data of described normal data, is specially:
Described system finds corresponding standardization flow process and the normal data of correspondence according to process code.
In the preferred embodiment of one, between described step (4) and step (5), further comprising the steps of:
(4.1) node set that the system described in finds corresponding monitored node set according to corresponding standardization flow process, step lacks inspection node set and wrong order is made unwarranted inspections;
(4.2) system described in judges that whether each normal data is the data of monitor node;
(4.3) if this normal data is the data of monitor node, then continue step (5), otherwise delete this normal data and return step (4.2), until all normal datas judge complete.
In the preferred embodiment of one, described system judges that whether each normal data is the data of monitor node, comprises the following steps:
(4.2.1) whether there is the flow nodes number of each normal data in the monitored node set described in the system described in judges;
If (4.2.2) there is the flow nodes number of each normal data in described monitored node set, then this normal data is the data of monitor node, otherwise this normal data is not the data of monitor node.
In the preferred embodiment of one, after described step (4.4), further comprising the steps of:
(4.5) system described in judges the type that the unlawful practice of each normal data is analyzed.
In the preferred embodiment of one, described system judges to comprise the following steps the type that the unlawful practice of each normal data is analyzed:
(4.5.1) whether the wrong order described in system described in judges is made unwarranted inspections exists the flow nodes number of each normal data in node set, if, then judge that this normal data is as the order entanglement normal data needing to carry out wrong order and make unwarranted inspections, otherwise judge that this normal data is made unwarranted inspections without the need to carrying out wrong order;
(4.5.2) the step disappearance described in the system described in judges checks the flow nodes number that whether there is each normal data in node set, if, then judge that this normal data is as the step disappearance normal data needing to carry out the inspection of step disappearance, otherwise judge that this normal data checks without the need to carrying out step disappearance.
In the preferred embodiment of one, described carries out violation situation analysis to the normal data after reduction, is specially:
Described system is carried out wrong order according to result of determination to described normal data and is made unwarranted inspections or the inspection of step disappearance, and shows check result.
In the preferred embodiment of one, described system is carried out wrong order according to result of determination to described normal data and is made unwarranted inspections or the inspection of step disappearance, comprises the following steps:
(4.6a) the step disappearance flow nodes number related in the system identification step disappearance rule described in;
(4.7a) whether exist in the order entanglement normal data described in the system described in judges and lack flow nodes number identical flow nodes number with step, if so, then continue step (4.7a), otherwise continue step (4.8a);
(4.8a) system described in judges that check result lacks as step.
In the preferred embodiment of one, described system is carried out wrong order according to result of determination to described normal data and is made unwarranted inspections or the inspection of step disappearance, comprises the following steps:
(4.6b) the wrong order sinuous flow journey node number related in the system identification order entanglement rule described in;
(4.7b) whether the order of the operation end time that the order of the operation end time that the order entanglement normal data described in system described in judges is corresponding is corresponding with described wrong order sinuous flow journey node number is consistent, if, then continue step (4.7b), otherwise continue step (4.8b);
(4.8b) system described in judges that check result is as order entanglement.
In a preferred embodiment, described system introducing standardization procedural model, is specially:
The procedural model file transform of multiple format is the standardization procedural model of unified standard form and the standardization procedural model described in display by described system.
In the preferred embodiment of one, the standardization procedural model described in described display, is specially:
The standardization procedural model of described system according to two-stage classification system and organizational structure two dimension displays.
In a preferred embodiment, between described step (2) and (3), further comprising the steps of:
(2.1) the business object type described in is set to singleton pattern or many cases pattern.
In a preferred embodiment, the normal data of described system acquisition non-traffic flow process, is specially:
The data of described system acquisition non-traffic flow process, and the data collected are converted to normal data.
In addition, the present invention realizes the system that the unlawful practice of non-traffic flow process detects under also providing a kind of large data environment, its principal feature is, described system comprises:
Standardization flow process definition module, in order to import standardization procedural model;
Flow process relating module, in order to create business object type, and associates described business object type with described standardization procedural model;
Process reduction and violation definition module, in order to store the also meta-rule for process reduction and the violation rule for violation situation analysis;
The data collected in order to gather the data of non-traffic flow process, and are converted to normal data by data extraction module;
Process reduction and violation analysis module, in order to carry out process reduction to the data of described normal data, and carry out violation situation analysis to the normal data after reduction.
In actual applications, the treatment scheme that the unlawful practice realizing non-traffic flow process detects comprises the steps:
1, import standardization flow process and manage, comprising following steps:
1) the two-stage classification system (flow process large class/flow process group) of system initialization flow process and the organizational structure belonging to monitored flow process;
2) the procedural model files passe of multiple format is converted to the standardization procedural model of BPMN 2.0 form to monitor supervision platform, wherein the procedural model files passe of multiple format is comprised the following steps to monitor supervision platform:
(1) classification (flow process group) belonging to flow process is selected;
(2) indicated release whether covering existing normal process is selected;
(3) select whether create redaction;
(4) the logical correctness verification whether carrying out procedural model file is selected;
(5) the procedural model file that will upload is selected;
3) after standardization procedural model imports, finely tune procedural model, wherein, the operation of finely tuning procedural model comprises and arranges branch/content such as aggregation scheme, branch condition;
4) system is the personalized version that each organization design is different, comprising following steps:
(1) from procedural model storehouse, copy property version one by one;
(2) different personalized version is assigned to corresponding organizational structure;
5) the standardization procedural model used organizational structure carries out the adjustment of personalized version;
6) all standardization procedural models are shown from " two-stage classification system " and " organizational structure " two dimensions.
2, define data model and associate with flow process, comprising following steps:
1) system creation business object type is (if the establishment employing of business object type is the pattern imported from database table, Operation system setting business is to the persistence map information of the attribute of newtype, but the association that can not automatically create between business object type), wherein, the mode of operation creating business object type comprises following three kinds:
A () selects one or more to show from database, import the business object type that will create;
B (), from outside URL (Uniform Resoure Locator, uniform resource locator) or upload file mode, imports create business object type from XSD (XML Schemas Definition, XML structure defines) file;
C () creates a business object type by graphic interface, and add attribute one by one, arrange persistence map information etc.;
2) form of the business object type described in is: the unique ID of attribute 1 attribute 2 attribute 3 organization mechanism code normal process code;
Wherein, the ID that described unique ID refers to the different business object instance of same business needs identical.
3) system is based on the standardization procedural model of specifying (comprising public version and personalized version), is the business object type that the organization design of specifying associates, wherein, comprises the following steps:
(1) user specifies the standardization procedural model that will carry out operation flow association;
(2) user selects the organizational structure that will associate from organizational model, and the organizational structure that system is selected according to user finds out business object list of types and shows from database table;
(3) user selects the business object type that will associate from the list of business object type, and different flow process can use same business object type;
(4) the business object type created associates with standardization procedural model by system;
(5) each business object type that user is chosen as association arranges singleton pattern or many cases pattern, and wherein, the singleton pattern of described business object type refers to each business object type only corresponding business object example in standardization procedural model; The many cases pattern of described business object type to refer in standardization procedural model that each business object type can corresponding multiple business object example;
3, definitim flow also meta-rule and violation rule, comprising following steps:
1) user by process reduction with interface be set in violation of rules and regulations open certain version that standardization flow process model defines;
2) system reads standardization flow process model and defines to obtain file, with patterned way, standardization flow process is shown to user;
3) user needs those monitored nodes in process action node listing in setting procedure;
4) system joins in monitored node set by needing the node ID of monitor node (sequence number);
5) user determines whether the inspection to wanting monitored node to carry out " step disappearance " or " order entanglement ";
6) by needing the node carrying out " step disappearance " or " order entanglement " to join step disappearance respectively, system checks that node set and wrong order are made unwarranted inspections in node set, namely step disappearance checks that node set and wrong order node set of making unwarranted inspections is the set of flow nodes, comprises multiple nodes that will carry out step disappearance and wrong order and make unwarranted inspections;
7) user is by checking that rule arranges the also meta-rule of interface setting procedure in violation of rules and regulations, namely by business object that data acquisition obtains, the attribute such as " whether performing ", " execution time ", " executor " of identification activity (namely monitored in operation flow business activity node) is set, wherein, described " whether performing " attribute is a Boolean attribute, only have meet user arrange regular time this attribute value be just true;
8) user arranges " disappearance of having ready conditions/unnecessary " rule in violation of rules and regulations, and rule is arranged by the mode of regular expression in violation of rules and regulations;
4, from monitored system extracted data, comprising following steps:
1) system sends data acquisition notice, comprising following steps to monitored system:
(1) system is by configurable scheduling mechanism, and the notice periodically calling collected system monitors interface;
(2), when call notification monitors interface, import start time and end time two attributes into and carry out the scope that restricting data gathers;
Wherein, it is the standard Web Service format interface provided by collected system that described notice monitors interface, and described configurable scheduling mechanism refers to the timing and manual scheduling mechanism that are realized by configurable mode;
2), after monitored system acceptance to data acquisition notice, according to the data-interface specification of specifying, WS (website, network address) data receiver interface, in batches propelling data that supervisory system provides is called;
3) monitored system completes the service of to call supervisory system after the relevant all data-pushings of this notice complete and providing, and informs that this data acquisition notifier processes completes;
4) data collected are converted to the data layout of standard by supervisory system, conveniently carry out next step process reduction;
The form of the normal data after described data conversion is: the operation of flow process type flow numbering flow nodes mode of operation to operate the operation Close Date start time Start Date and operates end time operator and operate department's spare fields;
5) normal data after conversion is stored in process reduction database;
5, process reduction and situation analysis is in violation of rules and regulations carried out;
Wherein, the step of process reduction carried out to the data after conversion as follows:
1) from process reduction database, take out data, use process code in normal process database, search corresponding standardization procedural model:
2) in process reduction database, the identical standard data records of all process codes is found out according to the process code of this record;
3) the data record these with identical process code is transferred in a temporary file from process reduction database, arranges with the flow nodes ascending order of data;
4) find out the monitored node set needing in corresponding standardization flow process to carry out monitoring, step disappearance checks that node set and wrong order are made unwarranted inspections node set;
5) in monitored node set, search whether there is identical node number according to the flow nodes number of bar data every in temporary file, if there is no, illustrate that these data are non-monitor node data, delete these data and check next, until the end of temporary file;
6) if there is identical node number in monitored node set, continue in step disappearance inspection node set and wrong order make unwarranted inspections node set, to search respective nodes according to flow nodes number, determine the judgement carrying out which kind of unlawful practice;
The step of carrying out flow process violation situation analysis is as follows:
1) system checks regular unlawful practice inspection flow data in temporary file being carried out to step disappearance according to fixed step disappearance, specifically comprises the following steps:
(1) in step disappearance rule base, corresponding step disappearance rule is read according to the process code of standardization flow process;
(2) involved in identification step disappearance rule flow nodes number;
(3) in temporary file, search the flow nodes number whether existing and comprise in step disappearance rule;
(4) if all existed, illustrate that flow process does not have step to lack in violation of rules and regulations;
(5) one or morely not exist if had, illustrate that flow process exists step disappearance in violation of rules and regulations, the step of disappearance is exactly the flow nodes do not comprised in temporary file.
2) system to carry out the unlawful practice inspection of order entanglement according to fixed wrong order rule of making unwarranted inspections to the flow data in temporary file, specifically comprises the following steps:
(1) in order entanglement rule base, corresponding order entanglement rule is read according to the process code of standardization flow process;
(2) flow nodes number involved in order entanglement rule is identified;
(3) whether the priority reading the operation end time of corresponding flow process node data in temporary file is consistent with order entanglement rule interior joint sequence of operation;
(4) if be consistent, illustrate that flow process does not walk order entanglement in violation of rules and regulations;
(5) if having one or more inconsistent, illustrate that flow process exists order entanglement in violation of rules and regulations, the step of order entanglement is exactly define contrary flow nodes with order entanglement rule;
Wherein, step disappearance and order entanglement are basis rules in violation of rules and regulations, which constraint condition is used to judge examined node for being defined in inspection, determine whether these examined nodes exist the violation problem of step disappearance and order entanglement, as long as select node and the automatically setting of requirements of process monitoring during definition.
3) if flow data exists unlawful practice, violation data write unlawful practice database is submitted to and is reported to supervisor console in violation of rules and regulations and carries out violation and represent, specifically comprises the following steps:
(1) read the configuration file of the Centralized Monitoring platform of unlawful practice, represented by the monitored results of predefined theme form to unlawful practice;
(2) from normal process model bank, read standardization procedural model, represent interface with patterned way;
(3) from unlawful practice database, read the flow nodes data that there is unlawful practice, represent business practical implementation with patterned way and show in violation of rules and regulations;
(4) the various aggregate query of violation flow process and the graphic exhibition of statistics is carried out;
(5) graphic exhibition of the self-defining violation content analysis of all types of user and form is carried out according to predefine template.
The method and system that the unlawful practice of non-traffic flow process detects are realized under have employed large data environment of the present invention, to employ from Legacy System and directly extract non-traffic data to carry out process reduction and to carry out the method for unlawful practice detection, achieve the monitoring to the operation flow in the application of non-traffic flow process, overcome the defect that traditional BAM technology can only be applied to operation flow application; Simultaneously, system is by using configuration mode to provide good extendability to system component, integrated, the several data source of multiple application under meeting large data environment, several data processing mode, several data analytical model and multiple monitoring represent the integrated requirement of result, rule definition and Function Extension very flexible.The data analysis that system provides has very high real-time, can Fast Monitoring to the data that there is unlawful practice, represent warning in time, substantially increase unlawful practice from response time reaction being detected, the further in-depth of administering for enterprise IT provides solid foundation, has range of application widely.
In this description, the present invention is described with reference to its specific embodiment.But, still can make various amendment and conversion obviously and not deviate from the spirit and scope of the present invention.Therefore, instructions and accompanying drawing are regarded in an illustrative, rather than a restrictive.
Claims (14)
1. realize the method that the unlawful practice of non-traffic flow process detects under large data environment, it is characterized in that, described method comprises the following steps:
(1) system introducing standardization procedural model, and create business object type;
(2) described business object type associates with described standardization procedural model by the system described in;
(3) normal data of the system acquisition non-traffic flow process described in;
(4) system described in carries out process reduction to the data of described normal data;
(5) system described in carries out violation situation analysis to the normal data after reduction.
2. realize the method that the unlawful practice of non-traffic flow process detects under large data environment according to claim 1, it is characterized in that, described system carries out process reduction to the data of described normal data, is specially:
Described system finds corresponding standardization flow process and the normal data of correspondence according to process code.
3. realize the method that the unlawful practice of non-traffic flow process detects under large data environment according to claim 2, it is characterized in that, between described step (4) and step (5), further comprising the steps of:
(4.1) node set that the system described in finds corresponding monitored node set according to corresponding standardization flow process, step lacks inspection node set and wrong order is made unwarranted inspections;
(4.2) system described in judges that whether each normal data is the data of monitor node;
(4.3) if this normal data is the data of monitor node, then continue step (5), otherwise delete this normal data and return step (4.2), until all normal datas judge complete.
4. realize the method that the unlawful practice of non-traffic flow process detects under large data environment according to claim 3, it is characterized in that, described system judges that whether each normal data is the data of monitor node, comprises the following steps:
(4.2.1) whether there is the flow nodes number of each normal data in the monitored node set described in the system described in judges;
If (4.2.2) there is the flow nodes number of each normal data in described monitored node set, then this normal data is the data of monitor node, otherwise this normal data is not the data of monitor node.
5. realize the method that the unlawful practice of non-traffic flow process detects under large data environment according to claim 3, it is characterized in that, after described step (4.4), further comprising the steps of:
(4.5) system described in judges the type that the unlawful practice of each normal data is analyzed.
6. realize the method that the unlawful practice of non-traffic flow process detects under large data environment according to claim 5, it is characterized in that, described system judges to comprise the following steps the type that the unlawful practice of each normal data is analyzed:
(4.5.1) whether the wrong order described in system described in judges is made unwarranted inspections exists the flow nodes number of each normal data in node set, if, then judge that this normal data is as the order entanglement normal data needing to carry out wrong order and make unwarranted inspections, otherwise judge that this normal data is made unwarranted inspections without the need to carrying out wrong order;
(4.5.2) the step disappearance described in the system described in judges checks the flow nodes number that whether there is each normal data in node set, if, then judge that this normal data is as the step disappearance normal data needing to carry out the inspection of step disappearance, otherwise judge that this normal data checks without the need to carrying out step disappearance.
7. realize the method that the unlawful practice of non-traffic flow process detects under large data environment according to claim 6, it is characterized in that, described carries out violation situation analysis to the normal data after reduction, is specially:
Described system is carried out wrong order according to result of determination to described normal data and is made unwarranted inspections or the inspection of step disappearance, and shows check result.
8. under large data environment according to claim 7, realize the method that the unlawful practice of non-traffic flow process detects, it is characterized in that, described system is carried out wrong order according to result of determination to described normal data and is made unwarranted inspections or the inspection of step disappearance, comprises the following steps:
(4.6a) the step disappearance flow nodes number related in the system identification step disappearance rule described in;
(4.7a) whether exist in the order entanglement normal data described in the system described in judges and lack flow nodes number identical flow nodes number with step, if so, then continue step (4.7a), otherwise continue step (4.8a);
(4.8a) system described in judges that check result lacks as step.
9. under large data environment according to claim 7, realize the method that the unlawful practice of non-traffic flow process detects, it is characterized in that, described system is carried out wrong order according to result of determination to described normal data and is made unwarranted inspections or the inspection of step disappearance, comprises the following steps:
(4.6b) the wrong order sinuous flow journey node number related in the system identification order entanglement rule described in;
(4.7b) whether the order of the operation end time that the order of the operation end time that the order entanglement normal data described in system described in judges is corresponding is corresponding with described wrong order sinuous flow journey node number is consistent, if, then continue step (4.7b), otherwise continue step (4.8b);
(4.8b) system described in judges that check result is as order entanglement.
10. realize the method that the unlawful practice of non-traffic flow process detects under large data environment according to claim 1, it is characterized in that, described system introducing standardization procedural model, is specially:
The procedural model file transform of multiple format is the standardization procedural model of unified standard form and the standardization procedural model described in display by described system.
Realize the method that the unlawful practice of non-traffic flow process detects under 11. large data environments according to claim 10, it is characterized in that, the standardization procedural model described in described display, is specially:
The standardization procedural model of described system according to two-stage classification system and organizational structure two dimension displays.
Realize the method that the unlawful practice of non-traffic flow process detects under 12. large data environments according to claim 1, it is characterized in that, between described step (2) and (3), further comprising the steps of:
(2.1) the business object type described in is set to singleton pattern or many cases pattern.
Realize the method that the unlawful practice of non-traffic flow process detects under 13. large data environments according to claim 1, it is characterized in that, the normal data of described system acquisition non-traffic flow process, is specially:
The data of described system acquisition non-traffic flow process, and the data collected are converted to normal data.
14. 1 kinds realize the system of non-traffic flow process unlawful practice detection based on the method according to any one of claim 1 to 13 under large data environment, and it is characterized in that, described system comprises:
Standardization flow process definition module, in order to import standardization procedural model;
Flow process relating module, in order to create business object type, and associates described business object type with described standardization procedural model;
Process reduction and violation definition module, in order to store the also meta-rule for process reduction and the violation rule for violation situation analysis;
The data collected in order to gather the data of non-traffic flow process, and are converted to normal data by data extraction module;
Process reduction and violation analysis module, in order to carry out process reduction to the data of described normal data, and carry out violation situation analysis to the normal data after reduction.
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Cited By (11)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104899674A (en) * | 2015-04-24 | 2015-09-09 | 公安部交通管理科学研究所 | Public traffic management service pre-warning method and pre-warning system |
| CN107277005A (en) * | 2017-06-13 | 2017-10-20 | 深圳市永达电子信息股份有限公司 | A kind of distributed operation flow detection method |
| CN109697456A (en) * | 2018-11-21 | 2019-04-30 | 华为技术有限公司 | Business diagnosis method, apparatus, equipment and storage medium |
| CN109741035A (en) * | 2019-01-03 | 2019-05-10 | 深圳壹账通智能科技有限公司 | Data processing method, device, computer equipment and storage medium |
| CN109918152A (en) * | 2019-03-18 | 2019-06-21 | 中科麦迪人工智能研究院(苏州)有限公司 | Task executing method, device, server and storage medium based on policy flow |
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| CN110383323A (en) * | 2017-02-15 | 2019-10-25 | 索尼公司 | Information processing system and information processing method |
| CN110968604A (en) * | 2019-12-05 | 2020-04-07 | 长春嘉诚信息技术股份有限公司 | Method for automatically retrieving illegal operation of internet operation enterprise |
| CN111383150A (en) * | 2020-03-04 | 2020-07-07 | 青岛海信网络科技股份有限公司 | Method and device for identifying and supervising traffic police violation |
| CN115514548A (en) * | 2022-09-16 | 2022-12-23 | 北京易诚互动网络技术股份有限公司 | Method and device for guaranteeing Internet application security |
Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20020156601A1 (en) * | 2001-04-19 | 2002-10-24 | Tu Kevin Hsiaohsu | Event monitoring and detection system |
| CN1417690A (en) * | 2002-12-03 | 2003-05-14 | 南京金鹰国际集团软件系统有限公司 | Application process audit platform system based on members |
| CN101097619A (en) * | 2006-06-27 | 2008-01-02 | 国际商业机器公司 | System and method for monitoring business flowpath |
| US20080140468A1 (en) * | 2006-12-06 | 2008-06-12 | International Business Machines Corporation | Complex exponential smoothing for identifying patterns in business data |
| CN101902366A (en) * | 2009-05-27 | 2010-12-01 | 北京启明星辰信息技术股份有限公司 | Method and system for detecting abnormal service behaviors |
| CN102034357A (en) * | 2010-12-01 | 2011-04-27 | 北京握奇数据系统有限公司 | Vehicle monitoring device as well as device, system and method for detecting regulation-violating vehicles |
| CN103116825A (en) * | 2013-01-29 | 2013-05-22 | 江苏省邮电规划设计院有限责任公司 | Intelligent city management system |
| CN103778511A (en) * | 2014-01-27 | 2014-05-07 | 北京荣之联科技股份有限公司 | Cross-system procedure monitoring method and device |
-
2014
- 2014-10-27 CN CN201410581872.1A patent/CN104392297A/en active Pending
Patent Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20020156601A1 (en) * | 2001-04-19 | 2002-10-24 | Tu Kevin Hsiaohsu | Event monitoring and detection system |
| CN1417690A (en) * | 2002-12-03 | 2003-05-14 | 南京金鹰国际集团软件系统有限公司 | Application process audit platform system based on members |
| CN101097619A (en) * | 2006-06-27 | 2008-01-02 | 国际商业机器公司 | System and method for monitoring business flowpath |
| US20080140468A1 (en) * | 2006-12-06 | 2008-06-12 | International Business Machines Corporation | Complex exponential smoothing for identifying patterns in business data |
| CN101902366A (en) * | 2009-05-27 | 2010-12-01 | 北京启明星辰信息技术股份有限公司 | Method and system for detecting abnormal service behaviors |
| CN102034357A (en) * | 2010-12-01 | 2011-04-27 | 北京握奇数据系统有限公司 | Vehicle monitoring device as well as device, system and method for detecting regulation-violating vehicles |
| CN103116825A (en) * | 2013-01-29 | 2013-05-22 | 江苏省邮电规划设计院有限责任公司 | Intelligent city management system |
| CN103778511A (en) * | 2014-01-27 | 2014-05-07 | 北京荣之联科技股份有限公司 | Cross-system procedure monitoring method and device |
Cited By (15)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104899674A (en) * | 2015-04-24 | 2015-09-09 | 公安部交通管理科学研究所 | Public traffic management service pre-warning method and pre-warning system |
| CN110383323A (en) * | 2017-02-15 | 2019-10-25 | 索尼公司 | Information processing system and information processing method |
| CN110383323B (en) * | 2017-02-15 | 2023-08-15 | 索尼公司 | Information processing system and information processing method |
| CN107277005A (en) * | 2017-06-13 | 2017-10-20 | 深圳市永达电子信息股份有限公司 | A kind of distributed operation flow detection method |
| CN109697456B (en) * | 2018-11-21 | 2021-02-09 | 华为技术有限公司 | Service analysis method, device, equipment and storage medium |
| CN109697456A (en) * | 2018-11-21 | 2019-04-30 | 华为技术有限公司 | Business diagnosis method, apparatus, equipment and storage medium |
| CN109741035A (en) * | 2019-01-03 | 2019-05-10 | 深圳壹账通智能科技有限公司 | Data processing method, device, computer equipment and storage medium |
| CN109918152A (en) * | 2019-03-18 | 2019-06-21 | 中科麦迪人工智能研究院(苏州)有限公司 | Task executing method, device, server and storage medium based on policy flow |
| CN109993235A (en) * | 2019-04-10 | 2019-07-09 | 苏州浪潮智能科技有限公司 | A kind of multivariate data classification method and device |
| CN110275697A (en) * | 2019-06-28 | 2019-09-24 | 普元信息技术股份有限公司 | Platform process contrast difference analysis system and method in business under distributed environment based on topological structure |
| CN110275697B (en) * | 2019-06-28 | 2022-11-22 | 普元信息技术股份有限公司 | System and method for contrastively analyzing differences of service middlebox processes based on topological structure in distributed environment |
| CN110968604A (en) * | 2019-12-05 | 2020-04-07 | 长春嘉诚信息技术股份有限公司 | Method for automatically retrieving illegal operation of internet operation enterprise |
| CN111383150A (en) * | 2020-03-04 | 2020-07-07 | 青岛海信网络科技股份有限公司 | Method and device for identifying and supervising traffic police violation |
| CN115514548A (en) * | 2022-09-16 | 2022-12-23 | 北京易诚互动网络技术股份有限公司 | Method and device for guaranteeing Internet application security |
| CN115514548B (en) * | 2022-09-16 | 2023-06-09 | 北京易诚互动网络技术股份有限公司 | Method and device for guaranteeing Internet application safety |
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