• International Journal of Computer Science & Network Security
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• v.23 no.2
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• pp.126-132
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• 2023

Web technology is evolving with the passage of time, from a single node server to high availability and then in the form of Kubernetes. In recent years, the research community have been trying to provide high availability in the form of multi master cluster with a solid election algorithm. This is helpful in increasing the resources in the form of pods inside the worker node. There are new impact of known DDoS attack, which is utilizing the resources at its peak, known as Yoyo attack. It is kind of burst attack that can utilize CPU and memory to its limit and provide legit visitors with a bad experience. In this research, we tried to mitigate the Yoyo attack by introducing a firewall at load-balancer level to prevent the attack from going to the cluster network.

• Journal of Korea Multimedia Society
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• v.9 no.3
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• pp.333-341
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• 2006

Recently, Random Constant worm is increasing The worm retards the availability of the overall network by exhausting resources such as CPU resource and network bandwidth, and damages to an uninfected system as well as an infected system. This paper analyzes the Power-Law network which possesses the preferential characteristics to restrain the worm from spreading. Moreover, this paper suggests the model which dynamically controls the spread of the worm using information about depth distribution of the delivery node which can be seen commonly in such network. It has also verified that the load for each node was minimized at the optimal depth to effectively restrain the spread of the worm by a simulation.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 1999.05a
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• pp.375-381
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• 1999

In this study, turbine speed control algorithm is studied for Buk-Jeju steam turbine power plant and also digital governor system is designed for speed control of steam turbine in power plant. By using duplex I/O module, triplex CPU module, 2 out of 3 voting algorithm and adding self diagnostic ability, the reliability of the designed digital governor system can be acquired satisfactorily. Designed and manufactured digital governor system is implemented in a pilot steam turbine plant of 0.3kw output power Installed in Korea Maritime University. After a series of experiment the reliability and availability is confirmed and also stable operation is achieved.

• Proceedings of the Korea Information Processing Society Conference
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• 2003.11a
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• pp.149-152
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• 2003

최근 VOD 서버 모델로 제안되는 클러스터형 VOD 서버는 확장성과 가용성을 높일 수 있다는 장점이 있지만 서버에 노드수가 증가하면서 서버에 장애가 발생할 가능성이 높아지는 문제점을 가지고 있다. 본 논문에서는 클러스터형 VOD 서버에서 노드 장애 발생시 이를 복구하기 위한 방안으로서 RAID-3, 4의 특성을 취합하고, 이에 파이프라인 개념을 더한 복구 시스템을 제시하고자 한다. 본 복구 시스템은 RAID-4 개념을 도입하여 디스크로의 접근을 큰 사이즈의 블록단위로 함으로써 디스크의 효율성을 증가시키며, 네트웍에는 RAID-3 개념을 적용하여 작은 사이즈의 블록으로 나누어 전송함으로써 네트웍을 효율적으로 사용하고 메모리 부하를 줄일 수 있도록 한다. 또한 파이프라인 개념을 도입하여 복구과정을 여러 노드에서 분담하여 동시에 처리함으로써 CPU, 네트웍, 메모리 등과 같은 자원에 대한 부하가 모든 노드로 분산되도록 한다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.1
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• pp.86-109
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• 2019

Cloud computing systems' performance is still a central focus of research for determining optimal resource utilization. Running several existing benchmarks simultaneously serves to acquire performance information from specific cloud system resources. However, the complexity of monitoring the existing performance of computing systems is a challenge requiring an efficient and interactive user directing performance-monitoring system. In this paper, we propose an effective multivariate control framework for monitoring cloud systems performance. The proposed framework utilizes the hardware cloud systems performance metrics, collects and displays the performance measurements in terms of meaningful graphics, stores the graphical information in a database, and provides the data on-demand without requiring a third party software. We present performance metrics in terms of CPU usage, RAM availability, number of cloud active machines, and number of running processes on the selected machines that can be monitored at a high control level by either using a cloud service customer or a cloud service provider. The experimental results show that the proposed framework is reliable, scalable, precise, and thus outperforming its counterparts in the field of monitoring cloud performance.

• Journal of the Semiconductor & Display Technology
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• v.21 no.3
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• pp.45-49
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• 2022

The fourth industrial revolution, internet of things, and the expansion of online web services have increased an exponential growth and deployment in the number of cloud data centers (CDC). The cloud is emerging as new paradigm for delivering the Internet-based computing services. Due to the dynamic and non-linear workload and availability of the resources is a critical problem for efficient workload and resource management. In this paper, we propose the particle swarm optimization (PSO) based gated recurrent unit (GRU) neural network for efficient prediction the future value of the CPU and memory usage in the cloud data centers. We investigate the hyper-parameters of the GRU for better model to effectively predict the cloud resources. We use the Google Cluster traces to evaluate the aforementioned PSO-GRU prediction. The experimental shows the effectiveness of the proposed algorithm.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.11
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• pp.3163-3181
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• 2023

Eavesdropping attacks have seriously threatened network security. Attackers could eavesdrop on target nodes and link to steal confidential data. In the traditional network architecture, the static routing path and the important nodes determined by the nature of network topology provide a great convenience for eavesdropping attacks. To resist monitoring attacks, this paper proposes a random routing mutation defense method based on dynamic path weight (DPW-RRM). It utilizes network centrality indicators to determine important nodes in the network topology and reduces the probability of important nodes in path selection, thereby distributing traffic to multiple communication paths, achieving the purpose of increasing the difficulty and cost of eavesdropping attacks. In addition, it dynamically adjusts the weight of the routing path through network state constraints to avoid link congestion and improve the availability of routing mutation. Experimental data shows that DPW-RRM could not only guarantee the normal algorithmic overhead, communication delay, and CPU load of the network, but also effectively resist eavesdropping attacks.

• Journal of Information Processing Systems
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• v.5 no.1
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• pp.33-40
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• 2009

Ever since the network-based malicious code commonly known as a 'worm' surfaced in the early part of the 1980's, its prevalence has grown more and more. The RCS (Random Constant Spreading) worm has become a dominant, malicious virus in recent computer networking circles. The worm retards the availability of an overall network by exhausting resources such as CPU capacity, network peripherals and transfer bandwidth, causing damage to an uninfected system as well as an infected system. The generation and spreading cycle of these worms progress rapidly. The existing studies to counter malicious code have studied the Microscopic Model for detecting worm generation based on some specific pattern or sign of attack, thus preventing its spread by countering the worm directly on detection. However, due to zero-day threat actualization, rapid spreading of the RCS worm and reduction of survival time, securing a security model to ensure the survivability of the network became an urgent problem that the existing solution-oriented security measures did not address. This paper analyzes the recently studied efficient dynamic network. Essentially, this paper suggests a model that dynamically controls the RCS worm using the characteristics of Power-Law and depth distribution of the delivery node, which is commonly seen in preferential growth networks. Moreover, we suggest a model that dynamically controls the spread of the worm using information about the depth distribution of delivery. We also verified via simulation that the load for each node was minimized at an optimal depth to effectively restrain the spread of the worm.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.5
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• pp.1726-1743
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• 2014

DDoS (Distributed Denial of Service) has been a continuous threat to the cyber world with the growth in cyber technology. This technical evolution has given rise to a number of ultra-sophisticated ways for the attackers to perform their DDoS attack. In general, the attackers who generate the denial of service, use the vulnerabilities of the TCP. Some of the vulnerabilities like SYN (synchronization) flooding, and IP spoofing are used by the attacker to create these Distributed Reflected Denial of Service (DrDoS) attacks. An attacker, with the assistance of IP spoofing creates a number of attack packets, which reflects the flooded packets to an attacker's intended victim system, known as the primary target. The proposed scheme, Efficient Spoofed Flooding Defense (ESFD) provides two level checks which, consist of probing and non-repudiation, before allocating a service to the clients. The probing is used to determine the availability of the requested client. Non-repudiation is taken care of by the timestamp enabled in the packet, which is our major contribution. The real time experimental results showed the efficiency of our proposed ESFD scheme, by increasing the performance of the CPU up to 40%, the memory up to 52% and the network bandwidth up to 67%. This proves the fact that the proposed ESFD scheme is fast and efficient, negating the impact on the network, victim and primary target.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• v.1
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• pp.171-174
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• 2006

A large number of service providers in countries all over the world have established GNSS reference station networks in the last years and are using network software today to provide a correction stream to the user as a routine service. In current GNSS network processing, all the geometric related information such as ionospheric free carrier phase ambiguities from all stations and satellites, tropospheric effects, orbit errors, receiver and satellite clock errors are estimated in one centralized Kalman filter. Although this approach provides an optimal solution to the estimation problem, however, the processing time increases cubically with the number of reference stations in the network. Until now one single Personal Computer with Pentium 3.06 GHz CPU can only process data from a network consisting of no more than 50 stations in real time. In order to process data for larger networks in real time and to lower the computational load, a federated filter approach can be considered. The main benefit of this approach is that each local filter runs with reduced number of states and the computation time for the whole system increases only linearly with the number of local sensors, thus significantly reduces the computational load compared to the centralized filter approach. This paper presents the technical aspect and performance analysis of the federated filter approach. Test results show that for a network of 100 reference stations, with the centralized approach, the network processing including ionospheric modeling and network ambiguity fixing needs approximately 60 hours to process 24 hours network data in a 3.06 GHz computer, which means it is impossible to run this network in real time. With the federated filter approach, only less than 1 hour is needed, 66 times faster than the centralized filter approach. The availability and reliability of network processing remain at the same high level.