• 한국정보통신학회:학술대회논문집
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• 한국해양정보통신학회 2011년도 추계학술대회
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• pp.563-566
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• 2011

스마트그리드는 전력 에너지망에 구축되는 추가적인 네트워크 개념으로 볼 수 있으며 전력과 IT가 결합된 형태이므로 통신망 관점에서 요구사항을 명확히 도출하고 이를 통신망에 구현하기 위한 구조가 구체적으로 정의되어야 한다. 본 논문에서는 ITU-T를 중심으로 스마트그리드에 대한 기술을 소개하고 통신망 관점의 표준 요구사항에 대해서도같이 논하기로 한다.

• 디지털산업정보학회논문지
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• 제12권4호
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• pp.41-49
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• 2016

Smart Grid is a next generation of new power growth electrical grid which provide high quality of electrical service by using Information Technologies to increase intelligence and performance. By using Smart Grid system, it can support energy management such as increase quality of electrical power, decrease energy and decrease emissions. However, Smart Grid uses information of energy consumption and when Smart Grid collects information, it will create private information. In this thesis, it will address issues of security private information which caused by Smart Grid for administrative measure and efficiency of Smart Grid in domestic. Also, cryptographic module algorithm, latest security solutions and strong wireless security policy for network environment such as wireless communication Iinternet are require for Smart Grid perform successfully and protect national power network equipment from cyber-attack and can stop leakage of user's personal information. Finally, it is urgent to prepare protection measures of National industrial facilities and power grid which can prepare for a cyber terrorism and penetration attacks and build emergency countermeasure management team for Smart Grid are require for safe Smart Grid environment.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제11권3호
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• pp.1510-1532
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• 2017

In smart grid, privacy implications to individuals and their families are an important issue because of the fine-grained usage data collection. Wireless communications are utilized by many utility companies to obtain information. Network coding is exploited in smart grids, to enhance network performance in terms of throughput, delay, robustness, and energy consumption. However, random linear network coding introduces a new challenge for privacy preserving due to the encoding of data and updating of coefficients in forwarder nodes. We propose a distributed privacy preserving scheme for random linear network coding in smart grid that considers the converged flows character of the smart grid and exploits a homomorphic encryption function to decrease the complexities in the forwarder node. It offers a data confidentiality privacy preserving feature, which can efficiently thwart traffic analysis. The data of the packet is encrypted and the tag of the packet is encrypted by a homomorphic encryption function. The forwarder node random linearly codes the encrypted data and directly processes the cryptotext tags based on the homomorphism feature. Extensive security analysis and performance evaluations demonstrate the validity and efficiency of the proposed scheme.

• 한국정보과학회논문지:컴퓨팅의 실제 및 레터
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• 제15권12호
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• pp.948-952
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• 2009

최근 공간 네트워크에서 대용량 이동객체의 위치정보를 관리하기 위한 DS-GRID(distributed S-GRID)가 제안되었다[1]. 그러나 DS-GRID는 균일 크기의 그리드 셀을 이용하기 때문에, 실제 응용에서 빈번히 발생하는 이동 객체의 쏠림 현상을 효율적으로 관리하지 못하는 단점을 지닌다. 이를 해결하기 위해, 본 논문에서는 이동객체의 밀도에 따라 그리드 셀을 동적으로 분할하는 동적 분산 그리드 기법을 제안한다. 아울러 이를 위한 k-최근접 질의처리 알고리즘을 제안한다. 마지막으로 성능 평가를 통해 이동객체의 쏠림 현상이 발생하였을 경우, 제안하는 동적 분산 그리드 기법이 검색 및 업데이트 성능 측면에서 DS-GRID 보다 우수함을 입증한다.

• 대한전자공학회논문지SD
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• 제44권12호
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• pp.37-42
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• 2007

클락 그리드 네트워크(Clock Grid Network)는 대부분의 고속 마이크로 프로세서에서 클락 스큐를 줄이기 위한 일반적인 방법이다. 본 논문은 클락 그리드의 모델링과 분석을 위해서 S-파라미터(Scattering Parameter)를 사용한 새로운 효과적인 방법을 제안한다. 또한, 그리드 사이즈와 와이어(wire) 폭이 그리드의 클락 스큐에 미치는 영향을 제시한다. 본 논문에서 클락 그리드의 상호 연결은 RC 수동소자에 의해서 모델화 되고, 제안된 방법의 결과는 Hspice의 시뮬레이션 결과와 비교해서 10 % 내의 오차를 보여준다.

• International Journal of Computer Science & Network Security
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• 제22권12호
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• pp.29-36
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• 2022

Smart grid (SG) software platforms and communication networks that run and manage the entire grid are increasingly concerned about cyber security. Characteristics of the smart grid networks, including heterogeneity, time restrictions, bandwidth, scalability, and other factors make it difficult to secure. The age-old strategy of "building bigger walls" is no longer sufficient given the rise in the quantity and size of cyberattacks as well as the sophisticated methods threat actor uses to hide their actions. Cyber security experts utilize technologies and procedures to defend IT systems and data from intruders. The primary objective of every organization's cybersecurity team is to safeguard data and information technology (IT) infrastructure. Consequently, further research is required to create guidelines and methods that are compatible with smart grid security. In this study, we have discussed objectives of of smart grid security, challenges of smart grid security, defensive cybersecurity techniques, offensive cybersecurity techniques and open research challenges of cybersecurity.

• 한국시뮬레이션학회논문지
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• 제15권3호
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• pp.1-9
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• 2006

현재 그리드 컴퓨팅은 네트워크 컴퓨팅 환경에서 대용량의 데이터와 엄청난 컴퓨팅의 문제를 해결하는데 매우 효과적인 해결책으로 각광받고 있다. 그리드는 애플리케이션을 여러 부분으로 나누어, 각 부분을 수많은 컴퓨터에서 동시에 수행함으로써 대규모 시뮬레이션 및 대용량 컴퓨팅을 실현할 수 있다. 그러나, 이를 위해서는 효과적인 자원 관리와 스케줄링 기법이 필요하다. 이 논문에서 우리는 분산된 그리드 컴퓨팅 환경에서의 자원관리와 스케줄링에 적용 가능한 그리드 거래망 모델을 제안하고 자율적인 자원 거래를 위한 가격 입찰 알고리즘을 소개한다. 우리는 모델의 효율성과 능력을 입증하기 위해 DEVSJAVA 모델링 & 시뮬레이션 환경 하에서 프로토타입 모델을 설계하고 실험하였다.

• Journal of Electrical Engineering and Technology
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• 제12권3호
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• pp.989-995
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• 2017

As is known to all that the output of wind power generation has a character of randomness and volatility because of the influence of natural environment conditions. At present, the research of wind power prediction mainly focuses on point forecasting, which can hardly describe its uncertainty, leading to the fact that its application in practice is low. In this paper, a wind power range prediction model based on the multiple output property of BP neural network is built, and the optimization criterion considering the information of predicted intervals is proposed. Then, improved Particle Swarm Optimization (PSO) algorithm is used to optimize the model. The simulation results of a practical example show that the proposed wind power range prediction model can effectively forecast the output power interval, and provide power grid dispatcher with decision.

• 통합자연과학논문집
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• 제9권3호
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• pp.199-205
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• 2016

In this paper, we established ZIGBEE home network and combined smart-grid and u-Healthcare system. We assisted for amount of electricity management of household by interlocking home devices of wireless sensor, PLC modem, DCU and realized smart grid and u-Healthcare at the same time by verifying body heat, pulse, blood pressure change and proceeded living body signal by using SVM algorithm and variety of ZIGBEE network channel and enabled it to check real-time through IHD which is developed by user interface. In addition, we minimized the rate of energy consumption of each sensor node when living body signal is processed and realized Query Processor which is able to optimize accuracy and speed of query. We were able to check the result that is accuracy of classification 0.848 which is less accounting for average 17.9% of storage more than the real input data by using Mjoin, multiple query process and SVM algorithm.

• International Journal of Computer Science & Network Security
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• 제21권6호
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• pp.89-100
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• 2021

Smart Grid Network (SGN) is a next generation electrical power network which digitizes the power distribution grid and achieves smart, efficient, safe and secure operations of the electricity. The backbone of the SGN is information communication technology that enables the SGN to get full control of network station monitoring and analysis. In any network where communication is involved security is essential. It has been observed from several recent incidents that an adversary causes an interruption to the operation of the networks which lead to the electricity theft. In order to reduce the number of electricity theft cases, companies need to develop preventive and protective methods to minimize the losses from this issue. In this paper, we have introduced a machine learning based SVM method that detects malicious nodes in a smart grid network. The algorithm collects data (electricity consumption/electric bill) from the nodes and compares it with previously obtained data. Support Vector Machine (SVM) classifies nodes into Normal or malicious nodes giving the statues of 1 for normal nodes and status of -1 for malicious -abnormal-nodes. Once the malicious nodes have been detected, we have done a trust evaluation based on the nodes history and recorded data. In the simulation, we have observed that our detection rate is almost 98% where the false alarm rate is only 2%. Moreover, a Trust value of 50 was achieved. As a future work, countermeasures based on the trust value will be developed to solve the problem remotely.