• Journal of KIISE:Databases
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• v.31 no.1
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• pp.1-12
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• 2004

As network systems are developed rapidly and network architectures are more complex than before, it needs to use PBNM(Policy-Based Network Management) in network system. Generally, architecture of the PBNM consists of two hierarchical layers: management layer and enforcement layer. A security policy server in the management layer should be able to generate new policy, delete, update the existing policy and decide the policy when security policy is requested. And the security policy server should be able to analyze and manage the alert messages received from Policy enforcement system in the enforcement layer for the available information. In this paper, we propose an alert analyzer using data mining. First, in the framework of the policy-based network security management, we design and implement an alert analyzes that analyzes alert data stored in DBMS. The alert analyzer is a helpful system to manage the fault users or hosts. Second, we implement a data mining system for analyzing alert data. The implemented mining system can support alert analyzer and the high level analyzer efficiently for the security policy management. Finally, the proposed system is evaluated with performance parameter, and is able to find out new alert sequences and similar alert patterns.

• Journal of the Korea Society of Computer and Information
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• v.7 no.4
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• pp.141-149
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• 2002

Recently, a number of network systems are developed rapidly and network architectures are more complex than before, and a policy-based network management should be used in network system. Especially, a new paradigm that policy-based network management can be applied for the network security is raised. A security policy server in the management layer can generate new policy, delete. update the existing policy and decide the policy when security policy is requested. The security server needs to analyze and manage the alert message received from server Policy enforcement system in the enforcement layer for the available information. In this paper, we implement an alert analyzer that analyze the stored alert data for making of security policy efficiently in framework of the policy-based network security management. We also propose a data mining system for the analysis of alert data The implemented mining system supports alert analyzer and the high level analyzer efficiently for the security.

• Proceedings of the Korea Information Processing Society Conference
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• 2003.05b
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• pp.1453-1456
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• 2003

인터넷의 발달로 인하여 기존 전화망을 인터넷 망으로 적은 비용으로 사용하고자 VoIP 가 연구되기 시작하였다. VoIP 의 기존전화망과의 품질의 차이에도 불구하고 대폭적인 통화비용의 절감과 다양한 이점으로 많은 연구가 되고 있다. 이에 통화품질의 향상을 위하여 QoS에 대한 연구가 활발히 진행되고 있다. 여기서는 QoS를 지원하는 Q-SIP 서버와 Policy Based 의 COPS 를 이용하여 Pre-COPS update message 와 Reservation COPS cache로 정책결정과 QoS를 지원하고자 한다.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.26 no.5
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• pp.1105-1119
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• 2016

Android includes SEAndroid as a core security feature. SELinux is applied to Android OS as a SEAndroid, because there exists structural differences between Linux and Android. Since the security of SEAndroid depends on the reliable policy if the policy is tampered by the attacker, the serious security problems can be occurred. So we must protect policies which are the most important thing in SEAndoroid. In this paper, we analyze the process of SEAndroid policy updating to find out vulnerabilities and study the attack points on policy tampering. And we propose the SPPA to detect whether the policy is modified by an attacker. Moreover, we prove the performance and the effect of our proposed method on mobile device.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.6
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• pp.1877-1891
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• 2022

As a part of cloud computing technology, algorithms for cloud task scheduling place an important influence on the area of cloud computing in data centers. In our earlier work, we proposed DeepEnergyJS, which was designed based on the original version of the policy gradient and reinforcement learning algorithm. We verified its effectiveness through simulation experiments. In this study, we used the Proximal Policy Optimization (PPO) algorithm to update DeepEnergyJS to DeepEnergyJSV2.0. First, we verify the convergence of the PPO algorithm on the dataset of Alibaba Cluster Data V2018. Then we contrast it with reinforcement learning algorithm in terms of convergence rate, converged value, and stability. The results indicate that PPO performed better in training and test data sets compared with reinforcement learning algorithm, as well as other general heuristic algorithms, such as First Fit, Random, and Tetris. DeepEnergyJSV2.0 achieves better energy efficiency than DeepEnergyJS by about 7.814%.

• Korean Journal of Construction Engineering and Management
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• v.7 no.3 s.31
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• pp.122-129
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• 2006

The Ministry of Construction and Transportation(MOCT) announced the General Policy for Effective Implementation of Public Construction Projects(the Policy) in 1999. Fifty two regulations were amended to embody the Policy between 1999 to 2001 Then MOCT performed the analysis to show the quantitative performance of the Policy. However, there has been no effort to evaluate the degree of implementation and effectiveness of the Policy so far. Therefore, this paper was initiated to perform the survey on industry's perceptions, implementation degree, effectiveness, and satisfaction of the Policy. The result shows that most policies were implemented in the construction industry but some policies were little adopted. Therefore, this paper proposes to update the Policy based on the survey results to effectively implement public sector projects.

• Korean Management Science Review
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• v.11 no.1
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• pp.145-163
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• 1994

For an Information System to be successful the continual control of the database system(DBS) is very important. In general, such control operations are performed periodically in batches, even in real time systems. We explain DBS related such control operations and describe the decision problem in each of them. Specifically, backup, checkpointing, reorganization, and batch update operations are considered. Then we develop a general model of the batch backup situation to determine the optimal backup timing. Other operations are considered as special cases of the general batch backup operation are derived and compared. We show that, in general, the control limit policy is superior to the fixed time interval policy in terms of the long-run average cost per unit time. Some practical considerations about the implementation of optimal policies are also mentioned.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.45 no.3
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• pp.46-52
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• 2008

BGP is an exterior routing protocol which exchanges routing information between ASs in ISP or large networks. It is necessary for the BGP to provide traffic enforcement among ASs, for an End-to-End traffic engineering capability in the Internet. However, traditional BGP-4 is lack of end-to-end traffic engineering capability because the policy-based routing affects the traffic only between directly-connected neighbor ASs. This paper proposes an extended BGP routing algorithm to achieve an End-to-End traffic engineering capability. This new method does not require an additional BGP message type, nor change a structure of existing routing table. It only extended the operation of UPDATE message with AS_PATH attribute, which is well-known mandatory. Simulation shows that the new BGP algorithm improves the packet delay and packet loss without the problem of backward compatibility.

• Journal of Digital Convergence
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• v.13 no.10
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• pp.147-155
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• 2015

The objective of this research is to empirically analyze the impact of contents update or patch service in online game, being provided after delivery to correct faults and to improve performance of the game. Regression analysis is applied to the data set, where the weekly increase rate of playing times is dependant variable, and the time(week) and two types of contents updates are introduced as independent variables. Statistical results show that the time(week) negatively influences the weekly increase rate of playing times. But the impact of new contents generation and contents adjustment on the weekly increase rate of playing times is not statistically significant, implying that once online game is published, contents update has no significant impact on the playing times. Implications for game designs are provided as a conclusion.

• Journal of KIISE:Computer Systems and Theory
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• v.33 no.3
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• pp.193-204
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• 2006

In most existing distributed Web systems, incoming requests are distributed to servers via Domain Name System (DNS). Although such systems are simple to implement, the address caching mechanism easily results in load unbalancing among servers. Moreover, modification of the DNS is necessary to load considering the server's state. In this paper, we propose a new dynamic load balancing method using dynamic DNS update and round-robin mechanism. The proposed method performs effective load balancing without modification of the DNS. In this method, a server can dynamically be added to or removed from the DNS list according to the server's load. By removing the overloaded server from the DNS list, the response time becomes faster. For dynamic scheduling, we propose a scheduling algorithm that considers the CPU, memory, and network usage. We can select a scheduling policy based on resources usage. The proposed system can easily be managed by a GUI-based management tool. Experiments show that modules implemented in this paper have low impact on the proposed system. Furthermore, experiments show that both the response time and the file transfer rate of the proposed system are faster than those of a pure Round-Robin DNS.