• Nuclear Engineering and Technology
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• v.53 no.10
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• pp.3327-3334
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• 2021

Present electric grids are advanced to integrate smart grids, distributed resources, high-speed sensing and control, and other advanced metering technologies. Cybersecurity is one of the challenges of the smart grid and nuclear plant digital system. It affects the advanced metering infrastructure (AMI), for grid data communication and controls the information in real-time. The research article is emphasized solving the nuclear and smart grid hardware security issues with the integration of field programmable gate array (FPGA), and implementing the latest Time Authenticated Cryptographic Identity Transmission (TACIT) cryptographic algorithm in the chip. The cryptographic-based encryption and decryption approach can be used for a smart grid distribution system embedding with FPGA hardware. The chip design is carried in Xilinx ISE 14.7 and synthesized on Virtex-5 FPGA hardware. The state of the art of work is that the algorithm is implemented on FPGA hardware that provides the scalable design with different key sizes, and its integration enhances the grid hardware security and switching. It has been reported by similar state-of-the-art approaches, that the algorithm was limited in software, not implemented in a hardware chip. The main finding of the research work is that the design predicts the utilization of hardware parameters such as slices, LUTs, flip-flops, memory, input/output blocks, and timing information for Virtex-5 FPGA synthesis before the chip fabrication. The information is extracted for 8-bit to 128-bit key and grid data with initial parameters. TACIT security chip supports 400 MHz frequency for 128-bit key. The research work is an effort to provide the solution for the industries working towards embedded hardware security for the smart grid, power plants, and nuclear applications.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.21 no.5
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• pp.19-26
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• 2021

This report proposes a waveguide spatial combiner with high power low loss. The proposed spatial combiner implements high power by combining from the center of each port through a waveguide. In particular, we implement low loss using TE01 mode, which has the lowest transmission track loss among modes of circular waveguide, and miniaturization is achieved by applying a new mode conversion method. IIn addition, it was confirmed that it was suitable for high output by calculating the insulation breakdown voltage of the new mode conversion structure through E-field analysis. The final 8-way waveguide spatial combiner was designed and manufactured, and the insertion loss was less than 0.4dB and the combining efficiency was 97% or more, confirming that the electrical performance was very good compared to the planar combining method.

• Journal of IKEEE
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• v.25 no.3
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• pp.571-577
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• 2021

This paper describes ISO/TR 4804, an international standard to describe how to design and verify autonomous cars to ensure safety and cybersecurity. Goals of ISO/TR 4804 are (1) positive risk balance and (2) avoidance of unreasonable risk. It also 12 principles of safety and cybersecurity to achieve these goals. In the design procedures, it describes (1) 13 capabilities to achieve these safety and cybersecurity principles, (2) hardware and software elements to achieve these capabilities, and (3) a generic logical architecture to combine these elements. In the verification procedures, it describes (1) 5 challenges to ensure safety and cybersecurity, (2) test goals, platforms, and solutions to achieve these challenges, (3) simulation and field operation methods, and (4) verification methods for hardware and software elements. Especially, it regards deep neural network as a software component and it describe design and verification methods of autonomous cars.

• Journal of IKEEE
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• v.25 no.3
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• pp.565-570
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• 2021

This paper describes UL 4600, a new international safety standard to ensure safety of autonomous cars. Conventional vehicular safety standards such as ISO 26262 and ISO/PAS 21448 suffer from large limitations to be applied to autonomous cars, but UL 4600 exploits new approaches to be applied to autonomous cars. Conventional standards define various technological aspects to ensure safety and require manufacturers to certify these aspects. On the contrary, UL 4600 requires manufacturer to explain and prove why autonomous cars are safe. In UL 4600, (1) under specific environments where the system is designed to operate with, (2) claims should be defined to guarantee given safety, and (3) arguments should be suggested to satisfy given goals, and (3) evidences should be presented to prove given arguments. UL 4600 is technology-neutral since it does not require specific designs nor technologies. So UL 4600 only requires manufacturers to prove given safety goals regardless of methods and technologies. Also UL 4600 admits various cases of autonomous car field operations into the standard via feedback loop. So UL 4600 effectively maneuvers various dangers unknown at the time of standard establishment.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.31 no.6
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• pp.1127-1136
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• 2021

In the field of power analysis attacks, electrical noise and misalignment of the power consumption trace are the major factors that determine the success of the attack. Therefore, several studies have been conducted to overcome this problem, and one of them is a signal processing method based on wavelet transform. Up to now, discrete wavelet transform, which can compress the trace, has been mostly used for power side-channel power analysis because continuous wavelet transform techniques increase data size and analysis time, and there is no efficient scale selection method. In this paper, we propose an efficient scale selection method optimized for power analysis attacks. Furthermore, we show that the analysis performance can be greatly improved when using the proposed method. As a result of the CPA(Correlation Power Analysis) and DDLA(Differential Deep Learning Analysis) experiments, which are non-profiling attacks, we confirmed that the proposed method is effective for noise reduction and trace alignment.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.4
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• pp.150-159
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• 2021

This study aimed to prevent inconvenience to electric vehicle users caused by an interruption of charging by the earth leakage breaker trip that occurs during charging. As a field case study, it was confirmed that during the battery charger failure type, leakage current measurement experiment by vehicle type, and leakage current breaker operation experiment, the internal temperature of the charger rose to more than 60 ℃ in summer, and the earth leakage circuit breaker stopped charging by tripping at 80% of the rated sensitivity current. Through Joule heating modeling, 32A is energized at the reference temperature of 30 ℃ at the initial time t=0 (s). After t=3000 (s), the heat generated around the charging part of the earth leakage breaker increased to 32.4 ℃. The temperature and time factors correlated with the amount of heat generated according to the statistical verification tool with a correlation coefficient of 0.97. Overall, it is possible to prevent the leakage breaker sensitivity current trip due to an increase in temperature inside the charger in summer by performing a Joule heating simulation according to the material of the charging case, the arrangement of the internal wiring, and the dielectric medium when developing the charger device.

• Journal of Convergence for Information Technology
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• v.11 no.7
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• pp.104-110
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• 2021

A novel selective oxidation process has been developed for low source/drain (S/D) series resistance of the fin channel metal oxide semiconductor field effect transistor (MOSFET). Using this technique, the selective oxidation fin-channel MOSFET (SoxFET) has the gate-all-around structure and gradually enhanced S/D extension regions. The SoxFET demonstrated over 70% reduction in S/D series resistance compared to the control device. Moreover, it was found that the SoxFET behaved better in performance, not only a higher drive current but also higher transconductances with suppressing subthreshold swing and drain induced barrier lowering (DIBL) characteristics, than the control device. The saturation current, threshold voltage, peak linear transconductance, peak saturation transconductance, subthreshold swing, and DIBL for the fabricated SoxFET are 305 ㎂/㎛, 0.33 V, 13.5 𝜇S, 76.4 𝜇S, 78 mV/dec, and 62 mV/V, respectively.

• Research in Vestibular Science
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• v.17 no.4
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• pp.142-151
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• 2018

Objectives: Excitability o medial vestibular nucleus (MVN) in the brainstem can be affected by changes in the arterial blood pressure. Several animal studies have demonstrated that acute hypotension results in the alteration of multiunit activities and expression of cFos protein in the MVN. In the field of extracellular electrophysiological recording, tetrode technology and spike sorting algorithms can easily identify single unit activity from multiunit activities in the brain. However, detailed properties of electrophysiological changes in single unit of the MVN during acute hypotension have been unknown. Methods: Therefore, we applied tetrode techniques and electrophysiological characterization methods to know the effect of acute hypotension on single unit activities of the MVN of rats. Results: Two or 3 types of unit could be classified according to the morphology of spikes and firing properties of neurons. Acute hypotension elicited 4 types of changes in spontaneous firing of single unit in the MVN. Most of these neurons showed excitatory responses for about within 1 minute after the induction of acute hypotension and then returned to the baseline activity 10 minutes after the injection of sodium nitroprusside. There was also gradual increase in spontaneous firing in some units. In contrast small proportion of units showed rapid reduction of firing rate just after acute hypotension. Conclusions: Therefore, application of tetrode technology and spike sorting algorithms is another method for the monitoring of electrical activity of vestibular nuclear during acute hypotension.

• BioChip Journal
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• v.12 no.4
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• pp.332-339
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• 2018

The future neuro-prosthetic devices would be required spikes data monitoring through sub-nanoscale transistors that enables to neuroscientists and clinicals for scalable, wireless and implantable applications. This research investigates the spikes monitoring through integrated CNT front-end amplifier for neuro-prosthetic diagnosis. The proposed carbon nanotube-based architecture consists of front-end amplifier (FEA), integrate fire neuron and pseudo resistor technique that observed high electrical performance through neural activity. A pseudo resistor technique ensures large input impedance for integrated FEA by compensating the input leakage current. While carbon nanotube based FEA provides low-voltage operation with directly impacts on the power consumption and also give detector size that demonstrates fidelity of the neural signals. The observed neural activity shows amplitude of spiking in terms of action potential up to $80{\mu}V$ while local field potentials up to 40 mV by using proposed architecture. This fully integrated architecture is implemented in Analog cadence virtuoso using design kit of CNT process. The fabricated chip consumes less power consumption of $2{\mu}W$ under the supply voltage of 0.7 V. The experimental and simulated results of the integrated FEA achieves $60G{\Omega}$ of input impedance and input referred noise of $8.5nv/{\sqrt{Hz}}$ over the wide bandwidth. Moreover, measured gain of the amplifier achieves 75 dB midband from range of 1 KHz to 35 KHz. The proposed research provides refreshing neural recording data through nanotube integrated circuit and which could be beneficial for the next generation neuroscientists.

• Journal of IKEEE
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• v.22 no.4
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• pp.1079-1087
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• 2018

Recently, computer vision field based deep learning artificial intelligence has become a hot topic among various image analysis boundaries. In this study, flames are detected in fire images using the Faster R-CNN algorithm, which is used to detect objects within the image, among various image recognition algorithms based on deep learning. In order to improve fire detection accuracy through a small amount of data sets in the learning process, we use image augmentation techniques, and learn image augmentation by dividing into 6 types and compare accuracy, precision and detection rate. As a result, the detection rate increases as the type of image augmentation increases. However, as with the general accuracy and detection rate of other object detection models, the false detection rate is also increased from 10% to 30%.