• 문화기술의 융합
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• 제9권5호
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• pp.721-727
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• 2023

국가 운영에서 부정, 낭비, 남용을 방지하기 위해 감사 및 감찰기구를 운영하고, 이들에게 업무의 독립성 보장을 포함한 많은 권한과 책임을 부여하고 있다. 하지만 이들 기관에서 발생하는 문제나 비위에 대해서는 누가 어떻게 감독하는지에 대한 문제가 제기된다. 이러한 감독을 위해 미국에서는 감찰관 법을 통해 감사기구 간 협의체인 감사공동체를 구성하여 업무 수행의 기준 준수 여부와 감사기구 직원의 비위에 대한 조사를 수행하고, 의회, 대통령, 회계감사원, 소속 기관 지도부 등 다양한 이해관계자가 상호작용을 하면서 독립성 보장과 협업 문화를 조성하고 있다. 정부 운영의 효율성과 효과성을 제고한다는 측면에서 감독기구와 의회의 관계를 발전시킬 필요가 있는 것이다. 이에 본 논문에서는 이러한 미국 사례를 연구하여 우리나라 감사기구에 적용할 감독제도의 효율적인 정책방안을 제시한다.

• 미국학
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• 제43권1호
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• pp.115-143
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• 2020

The U.S. Congress has been known to effectively control the bureaucracy. On one hand, Congress adjusts the degree of discretion provided to the bureaucracy when making agencies or legislation: ex ante control. On the other hand, it also performs the oversight activities to punish or correct undesirable behaviors of bureaucrats: ex post control. While the dynamics of each control mechanism is widely examined theoretically, few have attempted to empirically investigate this with a special attention to partisan politics in Congress. I attempt to fill this gap by measuring the two types of control mechanisms, testing theoretical assertions, and analyzing the dynamics under the two control mechanisms.

• International Journal of Computer Science & Network Security
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• 제21권7호
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• pp.56-62
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• 2021

The surge in generic attacks execution against cipher text on the computer network has led to the continuous advancement of the mechanisms to protect information integrity and confidentiality. The implementation of explicit decision tree machine learning algorithm is reported to accurately classifier generic attacks better than some multi-classification algorithms as the multi-classification method suffers from detection oversight. However, there is a need to improve the accuracy and reduce the false alarm rate. Therefore, this study aims to improve generic attack classification by implementing two hybridized decision tree algorithms namely Naïve Bayes Decision tree (NBTree) and Logistic Model tree (LMT). The proposed hybridized methods were developed using the 10-fold cross-validation technique to avoid overfitting. The generic attack detector produced a 99.8% accuracy, an FPR score of 0.002 and an MCC score of 0.995. The performances of the proposed methods were better than the existing decision tree method. Similarly, the proposed method outperformed multi-classification methods for detecting generic attacks. Hence, it is recommended to implement hybridized decision tree method for detecting generic attacks on a computer network.