• Journal of the Korea Convergence Society
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• v.13 no.5
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• pp.219-228
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• 2022

In order to improve audit quality, it is essential to understand the occurrence of disagreement between auditors and managers, and this study aims to analyze the impact of Business Strategies on audit risk and accounting audit delay. To this end, we conducted an empirical analysis using sample 2,910 firm-year data from 2018 to 2020 of KOSPI-listed and KOSDAQ-listed companies. The results of the empirical analysis of this study are as follows. First, compared to the companies of defender type, prospectors can expand audit procedures for new products, R&D costs, and intangible assets, and increase audit delays due to disagreement between managers and auditors. Second, compared to KOSPI-listed companies, the prospectors in KOSDAQ are more likely to have lower financial reporting quality, which further increases audit delays. The results of this study analyzed whether a company's Business Strategy affects the possibility of disagreement between an auditor and a company, and verified whether there is a difference in the audit report lag by stock market. The results of this study show that auditors' strong duty of care is needed for the companies of prospector type with high audit risk, and it is meaningful to present reinforced audit systems and specific guidelines for the companies of prospector type through the definition of prospector type. It also enables the expansion of research to identify the relationship between non-financial factors and audit risks that make up the companies of prospector type.

• Proceedings of the Korea Contents Association Conference
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• 2005.11a
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• pp.529-532
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• 2005

In anomaly intrusion detection, how to model the normal behavior of activities performed by a user is an important issue. To extract the normal behavior as a profile, conventional data mining techniques are widely applied to a finite audit data set. However, these approaches can only model the static behavior of a user in the audit data set This drawback can be overcome by viewing the continuous activities of a user as an audit data stream. This paper proposes a new clustering algorithm which continuously models a data stream. A set of features is used to represent the characteristics of an activity. For each feature, the clusters of feature values corresponding to activities observed so far in an audit data stream are identified by the proposed clustering algorithm for data streams. As a result, without maintaining any historical activity of a user physically, new activities of the user can be continuously reflected to the on-going result of clustering.

• KIEAE Journal
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• v.15 no.5
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• pp.13-20
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• 2015

Purpose: In order to upgrade the energy performance of existing building, energy audit stage should be implemented first because it is useful method to find where the problems occur and know how much time and cost consumption for retrofit. In overseas researches, three levels of audit is proposed whereas there are no standards for audit in Korea. Besides, most studies use dynamic simulation in detail like audit level 3 even though the level 2 can save time and cost than level 3. Thus, this paper focused on audit level 2 and proposed the audit method with the simple linear regression analysis model. Method: Two parameters were considered for the simple regression analysis, which were the monthly electric use and the mean outdoor temperature data. The former is a dependent variable and the latter is a independent variable, and the building's energy performance profile was estimated from the regression analysis method. In this analysis, we found the abnormal point in cooling season and the more detailed analysis were conducted about the three heat source equipments. Result: Comparing with real and predicted models, the total consumption of predicted model was higher than real value as 23,608 kWh but it was the results that was reflected the compulsory control in 2013. Consequently, it was analyzed that the revised model could save the cooling energy as well as reduce peak electric use than before.

• Journal of Korea Spatial Information System Society
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• v.7 no.2 s.14
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• pp.15-27
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• 2005

The purpose of this study is to present a methodology of GIS audit system which fully reflects standardization regarding GIS. With the recognition of the problems stemming from data exchange, building costs, and budget waste, this study utilized the standardization for evaluation factors of GIS audit. After analyzing the advantages and disadvantages of current audit methodology, this study pointed out the importance of audit, then presenting main audit factors followed by analyzing national standardization and extracting contents of audit to be added into the existing auditing items. Through the analysis of different types and characteristics, and both advantages and disadvantages of GASP, this study identifies and introduces a highly improved and practical methodology called Modified-GASP (M-GASP) that is basically set to be complementary and supplementary to GASP. Ultimately, the result of this study will support the higher degree of efficiency, stability, and extendability of GIS system, not to mention of strengthening the competitiveness of organizations involved.

• Journal of Internet Computing and Services
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• v.17 no.6
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• pp.123-131
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• 2016

Process mining in big data environment utilize a number of data were generated from the business process. It generates lots of knowledge and insights regarding implementation and improvement of the process through the event log of the company's enterprise resource planning (ERP) system. In recent years, various research activities engaged with the audit work of company organizations are trying actively by using the maximum strength of the mining process. However, domestic studies on applicable sales auditing system for the process mining are insufficient under big data environment. Therefore, we propose process-mining methods that can be optimally applied to online and traditional auditing system. In advance, we propose continuous monitoring information system that can early detect and prevent the risk under the big data environment by monitoring risk factors in the organizations of enterprise. The scope of the research of this paper is to design a pre-verification system for risk factor via practical examples in sales auditing. Furthermore, realizations of preventive audit, continuous monitoring for high risk, reduction of fraud, and timely action for violation of rules are enhanced by proposed sales auditing system. According to the simulation results, avoidance of financial risks, reduction of audit period, and improvement of audit quality are represented.

• Journal of the Institute of Electronics Engineers of Korea TE
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• v.39 no.1
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• pp.77-82
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• 2002

IDS has been studied mainly in the field of the detection decision and collecting of audit data. The detection decision should decide whether successive behaviors are intrusions or not , the collecting of audit data needs ability that collects precisely data for intrusion decision. Artificial methods such as rule based system and neural network are recently introduced in order to solve this problem. However, these methods have simple host structures and defects that can't detect changed new intrusion patterns. So, we propose the method using data mining that can retrieve and estimate the patterns and retrieval of user's behavior in the distributed different hosts.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.7 no.5
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• pp.978-985
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• 2003

The implementation of abnormal behavior detection IDS is more difficult than the implementation of misuse behavior detection IDS because usage patterns are various. Therefore, most of commercial IDS is misuse behavior detection IDS. However, misuse behavior detection IDS cannot detect system intrusion in case of modified intrusion patterns occurs. In this paper, we apply data mining so as to detect intrusion with only audit data related in intrusion among many audit data. The agent in the distributed IDS can collect log data as well as monitoring target system. False positive should be minimized in order to make detection accuracy high, that is, core of intrusion detection system. So We apply data mining algorithm for prediction of modified intrusion pattern in the level of audit data learning.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2001.10a
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• pp.479-482
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• 2001

IDS has been studied mainly in the field of the detection decision and collecting of audit data. The detection decision should decide whether successive behaviors are intrusions or not, the collecting of audit data needs ability that collects precisely data for intrusion decision. Artificial methods such as rule based system and neural network are recently introduced in order to solve this problem. However, these methods have simple host structures and defects that can't detect transformed intrusion patterns. So, we propose the method using data mining that can retrieve and estimate the patterns and retrieval of user's behavior in the distributed different hosts.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2002.05a
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• pp.619-622
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• 2002

IDS has been studied mainly in the field of the detection derision and collecting of audit data. The detection decision should decide whether successive behaviors are intrusions or not , the collecting of audit data needs ability that collects precisely data for intrusion decision. Artificial methods such as rule based system and neural network are recently introduced in order to solve this problem. However, these methods have simple host structures and defects that can't detect transformed intrusion patterns. So, we propose the method using data mining agent that can retrieve and estimate the patterns and retrieval of user's behavior in the distributed different hosts.

• Journal of Korean Society for Quality Management
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• v.21 no.2
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• pp.71-84
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• 1993

Currently the problem of air pollution caused by the motor vehicle emission is one of the most serious problems to be solved. Thus we needed the vehicle emissions audit procedure and technical innovation constraining the motor vehicle emission. The Korean Environmental Protection Agency currently audits automobiles for emissions compliance at assembly plants with multiple attribute multiple staged sampling plans. In order to establish the more reasonable audit procedure, the multiple staged sampling plan designed in this paper has been applied to the domestic vehicles by analyzing the statistic characteristics of the emission distribution. This paper summarizes the auditing procedure and develops methods for determining its statistical characteristics. Specifically, we consider how to evaluate a multiple staged sampling plan, give a procedure that efficiently estimates attribute-type probabilities from multivariate variables-type data, and quantify the effect of tightening the acceptable quality level of the sampling plan. As a result it can be proved that this audit procedure is the reasonable plan minimizing the AQL (Acceptable Quality Level) and is to be used effectively for the auditing procedure constraining the injurious gasses of the motor vehicles.