Request model of information assurance for IoT Services

Abstract

Background/Objectives: The service market using measurement information has expanded, but the effectiveness of the service is insufficient and unreliable because there is no procedure for verifying data in smart metering services.

Methods/Statistical analysis: Method for verifying the accuracy of the measurement data is provided through the analysis of the international standards (such as OIML D 31).

This method is demonstrated in electronic electricity meter and smart metering service to confirm the effectiveness of data reliability verification and to establish an environment to test data reliability.

Findings: The standard OIML D 31 is a general requirement for software controlled instrumentation.There are several requirements for this D 31, which can be broken down into five broad categories. We want to develop a meter that meets OIML D 31. The meter can then be used to prepare the meter's data management general requirements and to update test procedures. Using the developed meter as a reference, we develop a data verifier for the smart metering service, and develop test specifications and procedures for this service. This will be used as a data validation test for smart metering services that utilize weighing information based on OIML D 31.

Improvements/Applications: By developing the data management guidelines of the smart metering services, new services market with data stability and interoperability with various meters can be expected.

Keywords: Fraud prevention, Instrument Software, Measuring Instruments, Software protection, Software Requirement, Software Vulnerability