• Journal of the Korea Institute of Information Security & Cryptology
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• v.22 no.3
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• pp.427-438
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• 2012

The SCADA(Supervisory Control and Data Acquisition) systems are used to control some critical national infrastructures such as electricity, gas, and water distribution systems. Recently, there are many researches on key management scheme for secure communication due to change to the open network environment. We propose a new key management method which is established on ID-based cryptosystem using pairing on MTU(Master Terminal Unit), Sub-MTU, and RTU(Remote Terminal Unit). Furthermore, we present a redistribution protocol of private key of each device and a system recovery protocol as a countermeasure of exposure of KMS(Key Management System) master key which is occurred by some unexpected accidents or malicious attacks.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.52 no.3
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• pp.95-99
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• 2003

In this paper, the power system automation based on CAN communication protocol is introduced. Along with digitalization of electrical device, the various on-line services such as remote control, remote monitoring, remote parameter setting, fault data recording and remote diagnostic have been realized and become available. Therefore, it is necessary for those electrical devices to have real-time and reliable communication protocols. Author proposes DNPC(Distributed Network Protocol with CAN) which is proper to the power system SCADA (Supervisory Control And Data Acquisition) and DCS (Distributed Control System). The physical and datalink layer of DNPC protocol consists of the CAN2.0B which has the real-time characteristics and powerful error control scheme. As the transport and application layer, DNP3.0 is adopted because of its flexibility and compatible feature. Using the DNPC protocol, the power system automation is realized.

• Proceedings of the KIEE Conference
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• 2006.07a
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• pp.139-140
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• 2006

In this paper, autonomous information exchange methodology is studied between IEDS using SOAP protocol based on XML and PtP communication. Inference-based solution of the IED identifies the faulted zone autonomously from free information exchange among IEDs, transmits the operation information to the above SCADA system, also determines whether it executes or not for commands from the above SCADA. Finally, Inference-based solution is implemented using MS Visual C++ MFC, MS SOAP and MS XML. Availability and accuracy of the design is verified from simulation reviews for typical distribution substation.

• The KIPS Transactions:PartD
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• v.12D no.7 s.103
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• pp.1031-1038
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• 2005

In this paper, the maximum traffic quantity and actual traffic quantify of the data which are needed to grasp the statement of a system will be measured more accurately. A concrete quality measurement will be conducted by analysing a change of traffic quantity according to a protocol change and traffic under an overload condition when there is an accident. As a result can make an opportunity to maximize safety of power SCADA. Furthermore, future traffic quantity can be prospected by knowing current traffic quantity and grasping the rate of increase by the analysis and the information can be used as data to secure the band width in advance. It can make stable operation of power SCADA by arranging the limited network resources efficiently by information analysis of a network and expects more confidence.

• International Journal of Computer Science & Network Security
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• v.23 no.3
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• pp.10-16
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• 2023

The ever-increasing amount of data generated by various industries and systems has led to the development of data mining techniques as a means to extract valuable insights and knowledge from such data. The electrical energy industry is no exception, with the large amounts of data generated by SCADA systems. This study focuses on the analysis of historical data recorded in the SCADA database of the Libyan Electricity Company. The database, spanned from January 1st, 2013, to December 31st, 2022, contains records of daily date and hour, energy production, temperature, humidity, wind speed, and energy consumption levels. The data was pre-processed and analyzed using the WEKA tool and the Apriori algorithm, a supervised machine learning technique. The aim of the study was to extract association rules that would assist decision-makers in making informed decisions with greater efficiency and reduced costs. The results obtained from the study were evaluated in terms of accuracy and production time, and the conclusion of the study shows that the results are promising and encouraging for future use in the Libyan Electricity Company. The study highlights the importance of data mining and the benefits of utilizing machine learning technology in decision-making processes.

• Journal of information and communication convergence engineering
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• v.7 no.2
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• pp.98-106
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• 2009

Process Control Systems (PCSs) or Supervisory Control and Data Acquisition (SCADA) systems have recently been added to the already wide collection of wireless sensor networks applications. The PCS/SCADA environment is somewhat more amenable to the use of heavy cryptographic mechanisms such as public key cryptography than other sensor application environments. The sensor nodes in the environment, however, are still open to devastating attacks such as node capture, which makes designing a secure key management challenging. In this paper, a key management scheme is proposed to defeat node capture attack by offering both forward and backward secrecies. Our scheme overcomes the pitfalls which Nilsson et al.'s scheme suffers from, and is not more expensive than their scheme.

• Proceedings of the KIEE Conference
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• 2015.07a
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• pp.288-289
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• 2015

EMS(Energy Management System: 에너지 관리 시스템)에서 SCADA(Supervisory Control and Data Acquisition: 집중원격감시 시스템)은 RTU(Remote Terminal Unit), RCC(Remote Control Centre) 등을 통해 데이터를 취득한다. 이렇게 취득된 데이터는 토폴로지(Topology)를 구성하고, 계통을 감시하고 해석하는데 사용된다. EMS에서 계통해석 기술은 발전, 송전, 변전, 배전 계통이 유기적으로 결합되어 원활한 전력의 공급과 높은 신뢰도를 제공할 수 있어야 하는데 이를 위해서는 항상 신뢰할 수 있는 데이터를 사용해야 한다. 하지만 SCADA 취득 데이터는 통신 선로 상의 지연 등 통신 오류를 포함하고 있기 때문에 항상 신뢰할 수는 없으며, 오차를 포함한 측정 데이터를 사용하여 계통 해석을 할 경우 계통 해석 결과 전체를 신뢰할 수 없게 된다는 문제점이 있다. 본 논문에서는 원격 장치 신호 품질 불량 시 계통해석 데이터를 보다 신뢰할 수 있도록 취득, 사용하는 방안에 대해 제안한다.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.5
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• pp.815-825
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• 2015

DNP3(Distributed Network Protocol) is one of the most representative protocols which is used in SCADA(Supervisory Control and Data Acquisition) system. IEC 62351 is listing the integrity, confidentiality, availability and non-repudiation or accountability as the security requirement. However, IEEE Std. 1815 that is DNP3 standards does not define a mechanism for non-repudiation or accountability. In this paper, we propose a non-repudiation of origin technique about the sender of critical ASDU and implement the proposed scheme using software such as OpenSSL and SCADA source code library.

• Journal of Electrical Engineering and Technology
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• v.12 no.2
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• pp.689-700
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• 2017

This paper presents an effective approach for wind turbine (WT) condition assessment based on the data collected from wind farm supervisory control and data acquisition (SCADA) system. Three types of assessment indices are determined based on the monitoring parameters obtained from the SCADA system. Neural Networks (NNs) are used to establish prediction models for the assessment indices that are dependent on environmental conditions such as ambient temperature and wind speed. An abnormal level index (ALI) is defined to quantify the abnormal level of the proposed indices. Prediction errors of the prediction models follow a normal distribution. Thus, the ALIs can be calculated based on the probability density function of normal distribution. For other assessment indices, the ALIs are calculated by the nonparametric estimation based cumulative probability density function. A Back-Propagation NN (BPNN) algorithm is used for the overall WT condition assessment. The inputs to the BPNN are the ALIs of the proposed indices. The network structure and the number of nodes in the hidden layer are carefully chosen when the BPNN model is being trained. The condition assessment method has been used for real 1.5 MW WTs with doubly fed induction generators. Results show that the proposed assessment method could effectively predict the change of operating conditions prior to fault occurrences and provide early alarming of the developing faults of WTs.

• International Journal of Computer Science & Network Security
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• v.22 no.3
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• pp.220-228
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• 2022

The directed tests produce an expectation model to assist the organization's heads and professionals with settling on the right and speedy choice. A directed deep learning strategy has been embraced and applied for SCADA information. In this paper, for the load shedding expectation overall power organization of Libya, a convolutional neural network with multi neurons is utilized. For contributions of the neural organization, eight convolutional layers are utilized. These boundaries are power age, temperature, stickiness and wind speed. The gathered information from the SCADA data set were pre-handled to be ready in a reasonable arrangement to be taken care of to the deep learning. A bunch of analyses has been directed on this information to get a forecast model. The created model was assessed as far as precision and decrease of misfortune. It tends to be presumed that the acquired outcomes are promising and empowering. For assessment of the outcomes four boundary, MSE, RMSE, MAPE and R2 are determined. The best R2 esteem is gotten for 1-overlap and it was 0.98.34 for train information and for test information is acquired 0.96. Additionally for train information the RMSE esteem in 1-overlap is superior to different Folds and this worth was 0.018.