KR101775658B1 - Trust based smart-work system and method using the same - Google Patents

Abstract

The present invention discloses a trust-based smart work system and a method thereof. The present invention collects trust data using various sensing devices and user trust data agents, generates trust information which defines a trust relationship between trust objects, and provides trust information to a smart work service portal, thereby setting the information access right of each object according to a trust level between objects performing the smart work, and performing the service and device use control.

Description

[0001] The present invention relates to a trust-based smart work system and method,

The present invention relates to a smart work system and method, and more particularly to a trust based smart work system and method.

With the recent development of Internet technology and ICT technology, especially with the development of mobile technology, development and service provision and utilization of smart work system that can work freely and flexibly anytime and anywhere are increasing. As a result, access to and sharing of data for business, various company resources and services can be made anytime and anywhere through various ICT technologies, and such smart work services can be provided or provided according to changes in social population, work patterns and productivity awareness. The importance of utilization is increasing.

Existing SmartWall services can be divided into business mail, post and electronic payment service through groupware, unified communication through video conferencing, messenger and SNS, mobile work service through mobile devices, and sharing of data and resources And so on.

In particular, it is important to utilize smart work center with well-equipped smart work center besides the company, but it is important to provide smooth service without worrying about places such as home, vehicles, and other places.

However, in terms of users who provide or utilize such a smart work service, there are problems such as non-face-to-face remote work, unreliability and unreliability of work performance, personnel evaluation and access to secure data and services As a result, the proliferation of smart work services is hampered.

Until now, there has been no confirmation or provision of the trust level for each object, which can be evaluated and acknowledged through the system between smartwalk service providers and users. Therefore, by transparently providing the trust level with respect to the attitude, the location and the device used, the performance of the user using the smart work, and the level of collaboration between the users, it is possible to improve the trust level for the user, A smart work system and a method capable of differentiating based on a clear standard of the smart work system and method are required.
Examples of the prior art related to the present invention are disclosed in Korean Patent Publication No. 10-2015-0062637 (published on June 20, 2018), Korean Patent Laid-Open Publication No. 10-2014-0125488 (published on October 29, 2014) Publication No. 10-2015-0074151 (published on Jul. 01, 2015).

A problem to be solved by the present invention is to collect trust data through a variety of IoT sensing devices and trust data agents around a smart work space and a service user, and to collect the trust data through a smart work service using data / resources / services Based smart work service capable of analyzing trust information about the user's attitude, location, and device, work performance and user-level of collaboration, and providing the mash-up function to the smart work service function.

According to another aspect of the present invention, there is provided a trust-based smart work system including: a sensing device installed around a user and transmitting sensed data as trust data; A trust data agent installed in at least one of a user's PC, a mobile device, and a business system to transmit trust data; And a trust information system for receiving the trust data and using the trust data to generate trust information indicating a trust relationship between the trust objects.

In addition, the trust information may include an object (Trustor_Object) as a trust subject, a trustee_Object as an object of trust (Trustee_Object), a Metric as a trust context, a scope as a reliability application scope, and a value as a reliability evaluation value.

In addition, the metric indicates a type of trust represented by the trust information.

The trust information system may further include: a trust data manager for providing, to the trust model manager, trust data required for a trust analysis model driven by the trust model manager among the collected trust data; A trust model manager for driving a trust analysis module to be driven by the trust information evaluator, managing the performance of the embedded trust analysis module, and providing trust data to the trust analysis module; And a trust information evaluator for generating trust information using the trust data according to a predefined trust analysis module.

The trust data manager may generate a plurality of collection queues for collecting the trust data, generate a plurality of subscription queues requested by the trust model manager, and distribute the trust data between the collection queue and the subscription queue .

Also, the trust model manager loads the profile information of the trust analysis module, requests the trust data manager for the trust data manager necessary for generating the trust information, requests the trust data manager for the analysis module file on the Module- The trust information evaluator can be executed.

In addition, the trust information evaluator may output the reliability of the specific type for the trustee to a predetermined range of values in accordance with a predefined trust analysis model.

The trust information system may further include a trust information converter for generating the trust information output from the trust information evaluator into RDF data converted into a semantic structure.

Further, the trust information system generates new trust information using trust information according to a predefined reasoning algorithm at regular time intervals or whenever newly generated trust information exceeds a predefined reasoning threshold And may further include a trust information reasoner.

The trust information system may further include: IoTP receiving trust data sensed by the IoT sensing devices; A Trust Data Collector (TDC) for receiving trust data from the user trust data agent; And a TIAPI module for registering the trust object at the request of the smart work service portal, requesting the IoTP and the TDC to collect the trust data, and providing the trust information service to the SmartWall Services Portal.

The present invention collects trust data using various sensing devices and user trust data agents, generates trust information that defines a trust relationship between each trust object, and provides trust information to a smart work service portal , The information access right of each object can be set according to the trust level between each object performing the smart work, and the service and device use control can be performed.

1 is a block diagram showing a configuration of a trust-based smart work system according to a preferred embodiment of the present invention.
FIG. 2 is a detailed block diagram showing a detailed configuration of the trust information system shown in FIG. 1. FIG.
3 is a diagram showing the structure of the trust information generated in the present invention.
FIG. 4 is a flowchart illustrating a detailed process of registering a unique ID and registering a relationship between objects in the trust information system before the actual trust object and the smart work service object in FIG. 3 perform the trust information analysis.
5 is a flowchart illustrating a detailed process of collecting trust data in the trust information system of FIG.
FIG. 6 is a detailed block diagram of a trust data manager for reliably distributing trust data received in the trust information system of FIG. 2 to a trust model.
FIG. 7 is a flowchart illustrating a detailed process of processing trust data received in the trust information system of FIG. 2 as trust information through the trust analysis module.
FIG. 8 is a flowchart for explaining a detailed process of processing trust information processed in the trust information system of FIG. 2 into a semantic structure and performing trust inference.
FIG. 9 is a diagram showing a detailed structure of a TIAPI module for providing trust information processed in the trust information system of FIG. 2 to a Smart Work Service Portal (SWP).

Hereinafter, preferred embodiments of the present invention will be described with reference to the accompanying drawings.

FIG. 1 is a block diagram showing a configuration of a trust-based smart work system according to a preferred embodiment of the present invention, FIG. 2 is a detailed block diagram showing a detailed configuration of the trust information system shown in FIG. 1, Is a diagram showing the structure of the trust information generated in the present invention.

4 is a diagram showing an example of a relationship between an actual trust object corresponding to the Trustor_Object (Trusted Object) and Trustee_Object (Trusted Object) in FIG. 3 and a SmartWallService object such as various sensing devices, FIG. 5 is a flowchart illustrating a detailed process of collecting trust data in the trust information system of FIG. 2; FIG. 5 is a flowchart illustrating a detailed process of registering a unique ID and issuing a relationship between objects registered in the system 500; FIG.

FIG. 6 is a detailed block diagram of a trust data manager for reliably distributing trust data received in the trust information system of FIG. 2 to a trust model.

FIG. 7 is a flowchart for explaining a detailed process of processing trust data received in the trust information system of FIG. 2 as trust information through the trust analysis module, FIG. 8 is a flowchart illustrating the process of processing trust information processed in the trust information system of FIG. A semantic structure, and a detailed process of performing trust inference.

9 is a diagram showing a detailed structure of the TIAPI module 590 for providing the trust information processed in the trust information system 500 of FIG. 2 to the smart work service portal (SWP) 600. In FIG.

1, a smart work user accesses a smart work space 300 such as an office 310, a smart work center 320, and a home 330 via a user PC 100 or a user mobile device 200 The smart work space 300 and the business system LS are connected to the smart work portal SWP 600 to generate various trust information. (Trust Agent) such as a user trust data agent 110 and a trust data agent 410 installed in a legacy system 400 or an authentication sensing device 350 and an environment sensing device 360 in a smart work space, And the time attendance sensing device 370, and analyzes and provides the trust data through a trust information system (TIS). Thus, the smart work portal service And in order to provide the trustee with mashup information on the functions and services.

In order to generate various trust information related to the user, the trust agent 110 or 210 located in the user equipment and the work space or the trust agent 410 located in the in-house business system periodically or interlocks with the trust information system 500 Continuously communicates user's business-related trust data.

Also, the IoT sensing devices 350, 360, and 370 located in the smart work space for analyzing the user business situation continuously provide trust data to the trust information system depending on the situation.

The trust information system 500 performs real-time and continuous filtering and processing of such heterogeneous trust data, calculation of the trust information, expression of trust information through association, and provision of an application interface service (API) according to the user's request .

Therefore, in the present invention, it is possible to move beyond the level of providing all data, resources, and smart work service functions to a user without considering the degree of trust over the Internet simply by the prior art, In order to provide trust-based services by collecting and analyzing various trust data for users and meshing them up to the smart work service function, there are provided a collector for collecting trust data in association with an external IoT sensing device or a trust data agent, (IoT Platform) 501 and a Trust Data Collector (TDC) 502. The collected data is transmitted to a trust information evaluator (TE) 501 through a trust model manager (TMM) Trust Data Manager (TDM) 520, which passes the information to the Information Evaluator 540, A trust information transformer (TT) 550 for transforming the information into a semantic structure in the trust knowledge repository, and a trust information reasoner (TR) 560 for inferring new trust information from the trust information A trust information system (TIAPI) 590 including a trust information API module for providing a trust information service to an external smart work service, and (2) a trust information system (TIAPI) 4, a method for generating a trust object, a method for generating a plurality of smart work service objects such as an IoT sensing device and a trust agent, and a method for generating a plurality of smart work service objects from an IoT sensing device or a trust data agent A method for collecting trust data, A method of providing reliable delivery of data in order to distribute the trust data to the trust model, and (6) a method of performing various trust analysis models, connecting trust data, providing performance management and performing trust analysis, As shown in FIG. 8, and a method for generating and storing data of an RDF format, which is a semantic standard for storing and retrieving trust information based on relationships, as shown in FIG. 8, and periodically deducing new trust information.

Hereinafter, a trust-based smart work system and method according to a preferred embodiment of the present invention will be described with reference to the accompanying drawings.

1, the trust-based smart work system of the present invention includes various sensing devices (e.g., authentication sensing device 350, environment sensing device 360, and tangible sensing device 370), trust data agents (110, 210, 410), and a trust information system (500).

The various sensing devices (e.g., the authentication sensing device 350, the environmental sensing device 360 and the tangible sensing device 370) may be located within the office 310, smart work center 320, And transmits the collected trust data to the trust information system 500. The trust information system 500 stores the trust data related to the work of the user.

The trust data agents 110, 210, and 410 are installed in the user PC 100, the user mobile device 200, and the company business system 400, which are devices that access the smart work service portal 600 and use the service functions, And transmits the trust data to the trust information system 500.

The trust information system 500 continuously generates trust information using the trust data received from the various sensing devices and trust data agents and provides the trust information at the request of the smart work service portal 600, Work services are provided.

FIG. 2 is a detailed block diagram showing a detailed configuration of the trust information system shown in FIG. 1. FIG. The trust information system 500 includes an IoT (IoT Platform) 501, a Trust Data Collector (TDC) 502, a trust data manager (TDM) 502, (Trust Data Manager) 520, a Trust Model Manager (TMM) 530, a Trust Information Evaluator (TE) 540, a Trust Information Translator (TT) 550 A Trust Information Reasoner (TR) 560, a Trust Data Base (TDB) 570, a Trust Knowledge Base (TKB) 580, and a TIAPI module 590. [ .

First, IoTP (IoT Platform) 501 collects sensed trust data from external sensing devices 350, 360, and 370. Each of the sensing devices stores an originator of each sensor and trust object identification information (TrustObject_ID) that the corresponding sensor senses in advance in the TDB 570, and the information collected by the sensing device is as shown in Table 1 below Structure.

Originator TrustObject_ID SensorType Value Timestamp

The sensor type indicates the type of the sensing device (state of the art, environment, authentication, and the like), and Value indicates the sensing result value of the sensing device (the time when the user is seated for the task, the illuminance / temperature / humidity, Whether or not the ID / password is authenticated), and the Timestamp represents the sensing time.

The TDC (Trust Data Collector) 502 collects trust data from the external user PC 100, the user's mobile device 200, and the trust data agent 110, 210, 410 installed in the business system 400. The trust data agents 110, 210 and 410 also store the identifiers and trust object identification information (TrustObject_ID) of each trust data agent 110, 210 and 410 in the TDB 570 in advance and information collected from the trust data agents 110, And has the structure shown in Table 2 below.

Originator TrustObject_ID DataType Value Timestamp

Here, the DataType indicates information (information such as whether an OS is patched, whether a firewall is used, whether a vaccine is installed, whether a vaccine is upgraded, whether a password data security function or a screen saver is operated, etc.) , value represents the value for the collected information, and Timestamp represents the measured time.

The trust data manager (TDM) 520 performs a function of providing trust data required for the trust analysis model driven by the trust model manager (TMM) 530 among the collected trust data. 6, the trust data manager (TDM) 520 includes a plurality of collection queues 523 for receiving trust data from the IoTP 501 and the TDC 502, a trust model manager TMM A queue manager 522 for generating a plurality of subscription queues 525 at the request of the subscriber manager 530, a subscription manager subscription manager 526, an inter-queue trust data dispatcher module 526 for distributing the trust data between the collection queue and the subscription queue A QoS manager 521 for managing a stable queue transmission, and the like.

A trust model manager (TMM) 530 drives a trust analysis module to be driven by a trust information evaluator (TE) 540, manages the execution of an embedded trust analysis module, Data.

The trust information evaluator (TE) 540 generates trust information using the trust data according to the previously defined trust analysis module, and outputs the generated trust information to the trust information converter.

An example of the trust information generated by the trust information evaluator 540 is shown in FIG. Referring to FIG. 3, the trust information expresses a trust relationship between a trust object Trustor_Object and a trustee object Trustee_Object. The trust relationship is defined in detail as Trustor_Object, Trustee_Object, Metric as a trust context, Scope , And the reliability evaluation value value as elements.

Organizations and users, which are the subjects of trust, are subordinate concepts of agents. Trusted objects are objects of Agent, Data, Resource, Service, and Device type. The trustee is an object of type Agent. Thus, a company or a user expresses a trust relationship with another trustee object.

Metric, which is a trust context, is used for expressing various concepts (types) of trust. In the present invention, for the smart work service, an authentication, a reliability, a performance, a collaboration, ) And other trust information. The reliability value is treated as a real value in the range [0,1].

As an example, when a specific user performs authentication using a user ID and password, not a biosensor, in a user PC for telecommuting, the trust information evaluator 540 calculates trust scores Can be evaluated as 0.3 to generate trust information such as {company, user ID, authentication, smart work, 0.3}. In this example, although the user can perform authentication using biometric information, since the authentication is performed using the ID and the password, the company gives the user a low reliability score of 0.3 for the current authentication Accordingly, it is possible to limit the access of the user's e-mail for business use and the business bulletin board.

If the user wishes to access the restricted e-mail or access the business bulletin board, he or she can perform the re-authentication through the authentication sensing device 350 using his / her biometric information (e.g., fingerprint recognition, In this case, the trust information evaluator 540 generates trust information such as {company, user ID, authentication, smart work, 0.9} by generating a high trust score for the authentication and accesses the e-mail reading and business bulletin board can do.

The trust information converter (TT) 550 processes the trust information output from the trust information evaluator 540 into a semantic structure for expressing and inferring the trust information related to various trust objects. To this end, the trust information converter 550 converts the trust information into six pieces of RDF data, stores the RDF data in the trust knowledge storage TKB 580, as shown in reference numeral 551 in FIG. 8, And outputs it to the information inference unit 560.

The Trust Information Reasoner (TR) 560 deduces new trust information periodically or whenever new trust information exceeds the threshold value, using the stored trust information. Algorithms for generating new trust information using trust information are defined in advance and can be applied in various ways, so a detailed description thereof will be omitted.

 A trust data base (TDB) 570 manages trust object and smart work service object information, and stores and manages information collected from environment sensing devices and trust data agents.

The Trust Knowledge Base (TKB) (580) manages the analyzed trust information in an RDF structure based on relationships based on trust objects.

The TIAPI module 590 provides the trust information service to the smart work service portal 600, which is an external service, so that the smart work service portal 600 can restrict the access authority of the user according to the trust information, So that they can take action.

Referring to FIG. 4, details of an actual trust object corresponding to a Trustor_Object and a smart work service object corresponding to a Trustee_Object are registered in a trust information system before performing a trust information analysis, and a unique ID is issued and an inter- To explain the process,

First, the trust object registration process is processed by the TIAPI module 590 at the request of the smart work service portal 600, and the trust object information is inputted (S5901), the step S5902 of confirming whether the trust object is already registered , S5903), and an ID is issued to the untrusted trust object and stored in the TDB 570 (S5904).

The smart work service object registration process is processed in the TIAPI module 590 at the request of the smart work service portal 600 and the smart work service object information is inputted (S5911), whether or not the smart work service object is already registered A step S5915 of storing the smart work service object information, a step S5915 of inquiring the related trust object, and a step S5916 of forming a relationship between the trust object and the smart work service object do. For example, in step S5916, the fingerprint authentication sensing device installed in the smart work space of the user to perform biometric authentication of a user and a user, which are trust objects, may be stored in the TDB 570 in association with each other. These objects are created in the system "URI # uuid" format to ensure uniqueness as well as externality in the system.

Referring to FIG. 5, a detailed process of collecting trust data in the trust information system will be described. The IoTP 501 of the trust information system 500 receives the trust data collection request through the TIAPI module 590 in operation S5011 and transmits the trust data collection request to the authentication sensing device 350, the environment sensing device 360, and the tangible state sensing device 370, or receives sensor information from the sensing devices according to the set period for each sensing device (S5012).

Thereafter, the IoTP 501 checks the originator in the received trust data 503 (S5013), inquires of the TDB 570 to confirm whether it is registered (S5014), and registers the registered TrustObject_ID (S5015, S5016, S5017).

When the TrustObject_ID is confirmed, the sensing information is transmitted to the TDM 520 (S5018). If the TrustObject_ID is not registered in the sensing device, the confirmed TrustObject_ID is returned to the sensing device so that the corresponding sensing device can transmit the trust data including the TrustObject_ID (S5019).

When the TDC 502 receives a trust data collection request (S5021) via the TIAPI module 590 (S5021), the trust data collection flow of the user PC / mobile device / business system In step S5022, the agent TDA 110, 210, 410 receives and receives the trust data, or receives the trust data by reporting the trust data when each agent satisfies the reporting condition.

The TDC 502 confirms the Originator from the received trust data 504 (S5023), inquires the TDB 570 (S5024), and confirms the existence of the TrustObject_ID (S5025, S5026, S5027).

When the existence of TrustObject_ID is confirmed, the TDC 502 transfers the trust data to the TDM 520 (S5028). If the trust data does not include the TrustObject_ID, the Trust Data_ID is registered to the trust data agent, And causes the trust data agent to output the trust data including the TrustObject_ID (S5029).

Referring to FIG. 7, in the trust information system, the detailed process of processing received trust data as trust information through the trust analysis module will be described. First, the trust model manager (TMM) Information 531 is loaded (S531), and a subscription is requested to the TDM 520 according to Topic for the necessary trust data subscription (S532). In the profile 531, the metric indicates the type of trust information about the corresponding trust information, and the Topic indicates the trust data required to generate the corresponding trust information.

The trust model manager 530 loads the corresponding analysis module file into the memory on the Module-Path of the profile information to execute the trust information evaluator (TE) 540 (S533) , And hears the subscription message from the TDM 520 (S535). Thereafter, it is checked whether the analysis module is being executed (S536), the trust data is transmitted to the trust information evaluator TE 540 (S537), and the analysis module end process is performed at the analysis end (S538).

The trust information evaluator (TE) 540 initializes analysis-related variables and data structures through analysis initialization (S541), receives trust data from the TMM 530 (S542), and performs filtering, Preprocessing such as mappings of values is performed (S543).

Thereafter, the trust information evaluator (TE) 540 evaluates the trust according to a predefined evaluation algorithm (S544), outputs the trust information (S545), and requests the TMM 530 Processing such as finishing the residual process of the analysis process is performed (S546).

The trust information transformer (TR) 550 loads the trust transformation rule 551 (S551), and the trust information transformer (TR) 550 loads the trust transformation rule The trust information is received from the information evaluator (TE) 540 (S552).

Thereafter, the trust information converter (TR) 550 converts the inputted trust information into six pieces of RDF data (S553), as shown in the example of the trust transformation rule 551, and adds the RDF data (S554), and transmits the converted RDF data to the trust reasoner 560 (S555).

The trust information inference unit 560 loads the predefined trust information reasoning rule in step S561 and receives the RDF data from the trust information transformer TE 550 in step S562. (S563). Here, the reasoning threshold condition means an accumulated value of received RDF data or a predetermined reasoning period, and when the accumulated value of the received RDF data exceeds a predefined reasoning threshold or exceeds a period set by the reasoning threshold , Trust information inference is performed according to a predefined algorithm (S564). The result of the inference is stored in the TKB 580 (S565).

Referring to FIG. 9, a detailed structure of a TIAPI module 580 for providing trust information processed in a trust information system to a SmartWare Service Portal (SWP) will be described. The TIAPI module 580 includes a smart work service portal 590 A RESTful API Processor 581 for processing a REST API call of the REST API, an Authentication Manager 582 for performing an authentication process in a REST API call, an IoTP 501 for a trust data collection request in the smart work service portal 590, A trust data requestor 583 for processing the trust data request in cooperation with the trust information processor 502, a KDB Query Processor 584 for effectively retrieving the trust information of the RDF structure by interfacing with the TKB 580 for the trust information retrieval request, A KDB Manager 586 for detecting an event such as addition and change of new trust information in the Internet 580, and a Notifier 585 for providing notification to the smart work service portal 590 It consists of a module.

The process of each component according to the preferred embodiment of the present invention has been described.

Hereinafter, an example in which the operation flow between the modules constituting Fig. 2 is applied to the smart work service scenario using real trust using the logical model of Fig. 3 will be described as follows. It should be noted, however, that the following description corresponds to only one example of the embodiments of the present invention, and the technical idea of the present invention is not limited to the embodiments described below.

(S0) The smart work portal service generates trust object information for organization, person, data, resource, service, and device of the trust information analysis subject. . In general, smart work portal service records the meta information about the employees, the data provided by the company, the resources they have, the service they provide, and the devices available to employees, The issuance of an important trust object ID should be preceded.

(S1) In order to collect and analyze the trust data, the smart work portal service must install sensing devices that detect authentication / environment / attendance around the trust object or trust data agents in each device and company system, The devices or trust data agents are recorded with meta information in the form of a Smart Work Service object, and each ID issuance must be preceded. Since such a smart service object provides information related to the trust object, in order to record which trust object the smart service object relates to, which user, user device, service, and the like, the ID of the trust object is referred to as a reference key reference key.

(S2) The user accesses the smart work service portal 600 through the user PC 100 or the mobile device 200. At this time, if the ID (e.g., Email ID) / Password information of the lowest level for the system login is delivered to the smart work service portal, the service requests the TIAPI module 590 to collect the authentication information And the TIAPI module 590 delivers the authentication information collection request to the IoTP 501. [

(S3) The authentication sensing device 350 is generally located around the user's environment and performs user authentication at the request of the IoTP 501. The authentication sensing device can perform functions such as identification through employee ID card tagging or biometric authentication through photo / fingerprinting. Through this, the authentication sensing device outputs the information such as the service object ID for the authentication sensing device, the trust object ID of the user, the authentication, the authentication value, and the time, as in the structure 503 of FIG. 6 to the IoTP 501.

(S4) The environment sensing device 360 is for collecting work environment information about the worker. A value corresponding to the sensor type such as temperature, humidity, illuminance and position is referred to as "service object ID for the environment sensing device, Trust object ID, sensing device type, sensing value, time ", and the like. The locations correspond to the types of "company", "smart work center", "house", "other place" during initial installation. The environmental sensing device periodically outputs these values according to internally set reporting periods.

(S5) The time attendance sensing device 370 analyzes the work concentration of the worker, collects the proximity sensor values installed in the vicinity of the worker, processes the value of the proximity sensor as the service duration of the user, The trust object ID of the user, the sensing device type, the sensing value, the time "and the like. The sensing value may mean the number of minutes that the user has been in front of the sensor and continuously worked.

(S6) The TIAPI module 580 also provides the trust data agent (TDA) 110 installed in the user PC 100 or the TDA 210 of the mobile device 200 for trust analysis of the equipment used by the user And transmits the data collection request through the TDC 502.

(S7) The TDA 110 on the user PC receiving the trust data request from the TDC 502 analyzes the reliability of the user's PC by checking whether the OS is patched, whether the firewall is used, whether the vaccine is installed, The trust data in the form of "service object ID for the TDA, trust object ID for the device, trust data type, value, time" is collected by the TDC 110, .

(S8) The TDA 410 on the business system receiving the trust data request from the TDC 502 is used for determining the work achievement level or the collaboration level among the users for the company business, collecting and analyzing the log information of the existing business system , And outputs it to the TDC 502 as trust data having a format of "service object ID for TDA, trust object ID of employee, trust data type, value, time". The trust data type can be defined as a task classified in the business system such as "task assignment", "task progress", "task completion". At this time, the value is an identification ID for tasks such as work.

(S9) While the trust information system 500 is running, the trust model manager TMM 530 loads the predefined profile specifications as shown in 531 of FIG. 7, loads the analysis module defined in each specification, ). First, each loaded analysis module corresponds to an instance of a trust evaluator (TE) 540, and each instance proceeds with an analysis initialization operation at the request of the TMM 530. Each trust evaluation externally has an interface related to performance management such as initialization, execution, suspension, and termination, and internal algorithms can be implemented in various ways. At this time, the TMM 530 receives a subscription for a defined topic to receive the trust data required for analysis by the corresponding trust evaluator (TE) 540 in the profile specification from the TDM 520, Make a request.

(S10) The trust data manager (TDM) 520 generates a plurality of input queues for each trust data type defined to receive from the IoTP 501 and the TDC 502 and transmits the IoTP 501 and TDC 502 receives the trust data through each input queue. In addition, the TMM 530 generates an output queue for each subscription topic requested, and forms a mapping relationship between the input queue and the output queue. This is to manage Quality of Service (QoS) as well as efficient delivery in order for multiple trust information evaluators (TEs) 540 to operate and consume the same type of trust data from the TDM 520. The quality of delivery is maintained according to the QoS level defined when the TDM is executed. This level is 0: allow delivery failure, 1: allow duplicate delivery, 2: guarantee unconditional delivery.

(S11) If the process of S10 is illustrated for a "user access trust" analysis, the user access trust can be used to evaluate the trustworthiness of the user connected via the user's identity and user status and thereby limit service access. The "User Access Trust Analysis" module includes the trust information evaluator (TE) interface (initialization, execution, suspension, termination), etc. The required trust data topics are "authentication" Metric) is the user "Reliability ". The "user access trust" analysis module is an execution module implemented, for example, through a decision tree algorithm. The authentication or environment information collected through the IoTP 501 is output through the TDM 520. The TMM 530 receives the authentication or environment information and transfers it to the trust evaluator according to whether the trust analysis module is executed. The trust data is a kind of stream data. From the collection of trust data to the evaluation of transmission, each process has a pipeline structure between each module in the trust information system (TIS) 500.

(S12) The trust data input by the trust information evaluator (TE) 540 through the process of S11 is processed by the value of the metric required internally through the filtering and decision tree input and output. If the authentication level is "biometric" and the location is "Smart Work Center", it can be output with a reliability level of 0.8.

(S13) The trust knowledge repository (TKB) 580 is a repository for representing and storing semantic-based relationships between objects, not a table-type information store like a DB, and supporting search and inference . The RDF (Resource Description Framework) is a W3C-defined standard structure that expresses these semantic-based relationships. The trust objects that are generated at the stage of the scenario S0 in advance of the initial configuration of the TKB 580 are also stored in the TKB 580 in RDF format.

(S14) The trust information output from the trust information evaluator (TE) 540 is transmitted to the trust information evaluator (TE) 540 through "http://handysoft.co.kr "," http: //handysoft.co.kr#0512&quot ;, " "trustwork" such as "smartwork", "0.8">.

(S15) The trust information converter (TT) 550 converts the input value into six pieces of RDF data, stores it in the TKB 580, and outputs it to the trust information inference unit (TR) Each RDF data is related to each RDF tuple based on the six relations "hasTrustor", "hasTrustee", "hasMetric", "hasValue", "hasScope", and "hasTime" around "TrustRelationshipID"

(S16) The trust information inference unit 560 performs the function of discovering and generating meaningful new trust information from the existing trust information. The trust inference rule is defined as "the frequency of change of the user's daily trust is > , And "statility" is 0.5 ", and RDF tuples and the like received from the trust information converter 550 are stored in the queue and are inferred as batch processing expressions for each reasoning threshold value. The inference threshold is defined as the number of RDF tuples or time values arriving in the queue. That is, it can be set to perform inference every 10 minutes or every 100 RDF tuple inputs.

(S17) When the user accesses the smart work service portal 600, the processes from (S2) to (S16) are performed simultaneously, and the function of the smart work service portal 600 searches for such trust information , And mashing up the functions to limit the functions according to the trust of the user. For example, in the e-mail function provided by the smart work service portal 600, the "reliability" of the recipient is evaluated at the time of mail delivery and the mail delivery function can be disallowed if the & If the "reliability" of the device used by the user is less than 0.8, mashups will not be allowed to store the attachments of the received mail locally.

The present invention can also be embodied as computer-readable codes on a computer-readable recording medium. A computer-readable recording medium includes all kinds of recording apparatuses in which data that can be read by a computer system is stored. Examples of the computer-readable recording medium include a ROM, a RAM, a CD-ROM, a magnetic tape, a floppy disk, an optical data storage device, and the like, and may be implemented in the form of a carrier wave (for example, transmission via the Internet) . The computer readable recording medium may also be distributed over a networked computer system so that computer readable code can be stored and executed in a distributed manner.

The present invention has been described with reference to the preferred embodiments. It will be understood by those skilled in the art that various changes in form and details may be made therein without departing from the spirit and scope of the invention as defined by the appended claims. Therefore, the disclosed embodiments should be considered in an illustrative rather than a restrictive sense. The scope of the present invention is defined by the appended claims rather than by the foregoing description, and all differences within the scope of equivalents thereof should be construed as being included in the present invention.

100: user PC 200: user mobile device
300: smart work space 350: authentication sensing device
360: Environment sensing device 370: Time & attendance sensing device
400: Business system 500: Trust Information System
501: IoT Platform (IoT Platform) 502: Trust Data Collector (TDC)
520: Trust Data Manager (TDM)
530: Trust Model Manager (TMM)
540: Trust Information Evaluator (TE)
550: Trust Information Translator (TT)
560: Trust Information Reasoner (TR)
570: Trust Database (TDB)
580: Trust Knowledge Store (TKB)
590: TIAPI module
600: Smart Work Service Portal
110, 210, 410: User Trust Data Agent (TDA)

Claims (10)

A sensing device installed around the user and transmitting sensed data as trust data;
A trust data agent installed in at least one of a user's PC, a mobile device, and a business system to transmit trust data; And
And a trust information system for receiving the trust data and using the trust data to generate trust information indicating a trust relationship between trust objects,
The trust information includes an object (Trustor_Object) as a trust subject, a trustee_object (Trustee_Object), a metric as a trust context, a scope as a reliability application scope, and a value as a reliability evaluation value,
Wherein the metric indicates a type of trust represented by the trust information,
The trust information system
A trust data manager for providing the trust model manager with trust data necessary for a trust analysis model driven by the trust model manager among the collected trust data;
A trust model manager for driving a trust analysis module to be driven by the trust information evaluator, managing the performance of the embedded trust analysis module, and providing trust data to the trust analysis module;
A trust information evaluator for generating trust information using trust data according to a predefined trust analysis module; And
And a trust information inference unit that generates new trust information using trust information according to a predefined reasoning algorithm whenever the newly generated trust information exceeds a predefined reasoning threshold at regular time intervals,
The trust information evaluator
Wherein the trusted subject outputs a certain type of trustworthiness to a trustee in a predetermined range of values according to a predefined trust analysis model. delete delete delete The system according to claim 1, wherein the trust data manager
A plurality of collection queues for collecting the trust data, generating a plurality of subscription queues requested by the trust model manager, and distributing the trust data between the collection queue and the subscription queue. . The system of claim 1, wherein the trust model manager
Loading the profile information on the trust analysis module, requesting the trust data manager for the trust data manager necessary for generating the trust information, loading the analysis module file on the module-path of the profile information in the memory, and executing the trust information evaluator Based smart work system. delete The method according to claim 1,
And a trust information converter for generating the trust information output from the trust information evaluator into RDF data converted into a semantic structure. delete The method according to claim 1,
IoTP for receiving the trust data sensed at the sensing devices;
A Trust Data Collector (TDC) for receiving trust data from the trust data agent; And
Further comprising a TIAPI module for registering the trust object at the request of the SmartWare service portal, requesting the IoTP and the TDC to collect the trust data, and providing the trust information service to the SmartWall service portal Trust-based smart work system.

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