• Journal of the Korea Institute of Information Security & Cryptology
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• v.24 no.2
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• pp.295-310
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• 2014

DCS (Distributed Control System), the main control system of power plants, is an automated system for enhancing operational efficiency by monitoring, tuning and real-time operation. DCS is becoming more intelligent and open systems as Information technology are evolving. In addition, there are a large amount of investment to enable proactive facility management, maintenance and risk management through the predictive diagnostics. However, new upcoming weaponized malware, such as Stuxnet designed for disrupting industrial control system(ICS), become new threat to the main control system of the power plant. Even though these systems are not connected with any other outside network. The main control systems used in the power plant usually have been used for more than 10 years. Also, this system requires the extremely high availability (rapid recovery and low failure frequency). Therefore, installing updates including security patches is not easy. Even more, in some cases, installing security updates can break the warranty by the vendor's policy. If DCS is exposed a potential vulnerability, serious concerns are to be expected. In this paper, we conduct the penetration test by using NESSUS, a general-purpose vulnerability scanner under the simulated environment configured with the Ovation version 1.5. From this result, we suggest a log analysis method to detect the security infringement and react the incident effectively.

• Korean Journal of Clinical Laboratory Science
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• v.54 no.4
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• pp.249-255
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• 2022

Alzheimer's disease (AD) represents a major public health concern and has been identified as a research priority. Clinical research evidence supports that the core cerebrospinal fluid (CSF) biomarkers for AD, including amyloid-β (Aβ42), total tau (T-tau), and phosphorylated tau (P-tau), reflect key elements of AD pathophysiology. Nevertheless, advances in the clinical identification of new indicators will be critical not only for the discovery of sensitive, specific, and reliable biomarkers of preclinical AD pathology, but also for the development of tests that facilitate the early detection and differential diagnosis of dementia and disease progression monitoring. The early detection of AD in its presymptomatic stages would represent a great opportunity for earlier therapeutic intervention. The chance of successful treatment would be increased since interventions would be performed before extensive synaptic damage and neuronal loss would have occurred. In this study, the importance of developing an early diagnostic method using cognitive decline biomarkers that can discriminate between normal, mild cognitive impairment (MCI), and AD preclinical stages has been emphasized.

• Transactions of the Korean Society of Automotive Engineers
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• v.13 no.4
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• pp.74-80
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• 2005

This paper presents a misfire monitoring method by using the weight factor. According to OBD II(On-Board Diagnostics) regulations of the CARB (California Air Resources Board), an ECU (Electronic Control Unit) should detect misfires which occur in the internal combustion engine. A misfire is 1311owe4 by post-oscillations for short duration. Sometimes, the amplitude of oscillations may be as high as misfire and can be falsely detected as another misfire. To prevent this, the software designers do not attempt to detect another misfire for this short duration, during which the post oscillations exist. Because of this, ECU does not detect all the misfires and hence, the unstable state of automobile cannot be detected. If this happens for a long time, automobile may get damaged. To solve these problems, this paper suggests a new algorithm to detect misfire by using weighting factor Weighting factor is a concept to distinguish the misfire with the post oscillation and to improve the detection rate. This value of weighting factor is used for counting the misfire. This paper also shows the result of experiment done on a automobile using this software. The software is implemented using ASCET-SD which is preferred in the design of engine control. This paper's result show the possibility of improving the misfire detection by implementing this algorithm.