• Journal of the Korea Society of Computer and Information
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• v.17 no.12
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• pp.71-82
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• 2012

In this paper, we propose a license plate detection method with improved Adaboost learning and MCT (Modified Census Transform). The MCT represents the local structure patterns as integer numbered feature values which has robustness to illumination change and memory efficiency. However, since these integer values are discrete, a lookup table is needed to design a weak classifier for Adaboost learning. Some previous research efforts have focused on minimization of exponential criterion for Adaboost optimization. In this paper, a method that uses MCT and improved Adaboost learning based on Newton's optimization to exponential criterion is proposed for license plate detection. Experimental results on license patch images and field images demonstrate that the proposed method yields higher performance of detection rates with low false positives than the conventional method using the original Adaboost learning.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.29 no.6
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• pp.1365-1373
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• 2019

Meltdown and Spectre are vulnerabilities that exploit out-of-order execution and speculative execution techniques to read memory regions that are not accessible with user privileges. OS patches were released to prevent this attack, but older systems without appropriate patches are still vulnerable. Currently, there are some research to detect Meltdown and Spectre attacks, but most of them proposed dynamic analysis methods. Therefore, this paper proposes a binary signature that can be used to detect Meltdown and Spectre malware without executing them. For this, we collected 13 malicious codes from GitHub and performed binary pattern analysis. Based on this, we proposed a static detection method for Meltdown and Spectre malware. Our results showed that the method identified all the 19 attack files with 0.94% false positive rate when applied to 2,317 normal files.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.3B
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• pp.311-317
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• 2009

The traditional network anomaly detection systems execute the threshold-based detection without considering dynamic network environments, which causes false positive and limits an effective resource utilization. To overcome the drawbacks, we present the adaptive network anomaly detection model based on artificial immune system (AIS) in centralized network. AIS is inspired from human immune system that has learning, adaptation and memory. In our proposed model, the interaction between dendritic cell and T-cell of human immune system is adopted. We design the main components, such as central node and router node, and define functions of them. The central node analyzes the anomaly information received from the related router nodes, decides response policy and sends the policy to corresponding nodes. The router node consists of detector module and responder module. The detector module perceives the anomaly depending on learning data and the responder module settles the anomaly according to the policy received from central node. Finally we evaluate the possibility of the proposed detection model through simulation.

• The Korean Journal of Applied Statistics
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• v.35 no.6
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• pp.685-701
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• 2022

FDR is widely used in high-dimensional data inference since it provides more liberal criterion contrary to FWER which is known to be very conservative by controlling Type-1 errors. This paper proposes a sparse VHAR model estimation method controlling FDR by adapting the knockoff introduced by Barber and Candès (2015). We also compare knockoff with conventional method using adaptive Lasso (AL) through extensive simulation study. We observe that AL shows sparsistency and decent forecasting performance, however, AL is not satisfactory in controlling FDR. To be more specific, AL tends to estimate zero coefficients as non-zero coefficients. On the other hand, knockoff controls FDR sufficiently well under desired level, but it finds too sparse model when the sample size is small. However, the knockoff is dramatically improved as sample size increases and the model is getting sparser.

• (The) Research of the performance art and culture
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• no.43
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• pp.145-172
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• 2021

Shin Myung-soon's is based on the taboo 'bombing of the Han River Bridge'. The reality of the bombing of the Han River Bridge in 1950 and the shooting of Colonel Choi Chang-sik was known only as a word of mouth. At that time, the ruling class did not want to reveal the painful mistakes of the unfavorable war situation in the early days of the war and the false broadcasting of the president. The truth of the case, which was kept completely secret even to the bereaved family, could only be revealed after the regime change. After that, the bereaved family of Colonel Choi Chang-sik confirmed the innocence of the deceased through a request for retrial, and then the was born. However, the fate of was not so smooth. At the time, the performance officials vividly remember the difficulties they had with the text. Despite passing the pre-screening of the script, the performance was canceled just before the performance. The fact that the National Theater, officials from the Ministry of Culture and Education, and even military generals visited the practice room to stop the performance, on the contrary, was a testimony to the dangers of . It can be summarized as a crack in official history and a move to stop it. was later adapted into a special TV drama in 1981 and was first released to the public. This was a very meaningful step in terms of dealing with politically sensitive subjects on television, but the inconsistency of in the first place has largely disappeared. After that, in 1988, only after democracy entered the phase of appeasement, could be performed in its full form. In short, can be said to be an example of a process in which the history of the Korean War recorded from the standpoint of an established order and the counter-memory that crack it up are transformed according to the changes of the times and media.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.44 no.1
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• pp.74-84
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• 2007

This paper presents a new dual-loop Delay Locked Loop(DLL) to expand the delay lock range of a conventional DLL. The proposed dual-loop DLL contains a Coarse_loop and a Fine_loop, and its operation utilizes one of the loops selected by comparing the initial time-difference among the reference clock and 2 internal clocks. The 2 internal clock signals are taken, respectively, at the midpoint and endpoint of a VCDL and thus are $180^{\circ}$ separated in phase. When the proposed DLL is out of the conventional lock range, the Coarse_loop is selected to push the DLL in the conventional lock range and then the Fine_loop is used to complete the locking process. Therefore, the proposed DLL is always stably locked in unless it is harmonically false-locked. Since the VCDL employed in the proposed DLL needs two control voltages to adjust the delay time, it uses TG-based inverters, instead of conventional, multi-stacked, current-starved inverters, to compose the delay line. The new VCDL provides a wider delay range than a conventional VCDL In overall, the proposed DLL demonstrates a more than 2 times wider lock range than a conventional DLL. The proposed DLL circuits have been designed, simulated and proved using 0.18um, 1.8V TSMC CMOS library and its operation frequency range is 100MHz${\sim}$1GHz. Finally, the maximum phase error of the DLL locked in at 1GHz is less than 11.2ps showing a high resolution and the simulated power consumption is 11.5mW.

• The Journal of the Convergence on Culture Technology
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• v.5 no.4
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• pp.329-337
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• 2019

It is true that many tales delivered in an 'Story-telling' auditorium or theater have not so much exquisite and refined forms as distorted and deteriorated ones. Furthermore, when false interpretations of tale-performers added into the category of the texts of tales, the problems can be made worse. In case of oral folk tales, there can be discordance between the standpoint of a tale-performer and the contents of a tale. This thesis is directly aimed at pointing out the 'Behavior Economics' problems concerned with the reading and interpretation of tales through investigating the missing parts of a text in reading tales. Man's rationality is meant to be confined to bounded rationality. Instead of making best choices, bounded rationality leads consumers to make a decision which they think suffices themselves to the point requiring no more consideration on the given item. It is the very Heuristic that does work in the process of this simplified decision making process. Heuristic utilizes established empirical notion and specific information, and that's why there can be cognitive 'Biases' sometimes leading to inaccurate judgment. As Oral Literature is basically based on heavy guesswork and perceptual biases of general public, it is imperative to contemplate oral literature in the framework of Heuristic of behavior economics. This thesis deals with thinking types and behavioral patterns of the general public in the perspective of heuristic by examining 'Story-tellings' on the basis of personal or public memory. In addition, heuristic involves how to deal with significant but intangible content such as the errors of oral story teller, the deviations of the story, and responses of the audience.

• The Korean Society of Law and Medicine
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• v.23 no.4
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• pp.103-131
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• 2022

2021, the Supreme Court recognized the foundation of the quasi-indecent act by force by the concept of 'alcohol blackout' although there were multiple situations that it was hard to judge insanity of the victims was evident in the cases with drunken victims. This means the consideration of insanity state due to temporary false memory rather than the total loss of mental capacity from the existing concept of insanity. However, the interpretation of insanity in the criminal law has to be strict and its application could be difficult. In particular, the comparison precedent which is very similar to the subject one was determined not to be the same with the state of the insanity or inability to resist during the sexual relation though the victim had the symptoms of alcohol blackout, denying the quasi-indecent act by force. This argument is determined to be logical remarkably, and insanity and quasi-indecent act by force should be discussed considering the medical review on the alcohol blackout of the victims sufficiently when determining the individual precedents. In addition, the most important point in the sexual crimes is the consent, and there may be possibility of negligence in case that uncertain consent is determined as the consent to continue the following act. Also, in case of uncertain consent or suspicious, universal determination not to follow the act should be able to realized. Therefore, strong evidence is required for criminality, determining that the victim is the state not to be able to do the normal judgment and the minimum willful negligence is existed that the accused uses this. In the subject ruling, the act of the accused has to be clearly punished, however, it is determined to be unreasonable for the punishment with the quasi-indecent act by force under the interpretation of the current regulations.

• KIPS Transactions on Software and Data Engineering
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• v.12 no.4
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• pp.179-188
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• 2023

Recently, fake news disguises the form of news content and appears whenever important events occur, causing social confusion. Accordingly, artificial intelligence technology is used as a research to detect fake news. Fake news detection approaches such as automatically recognizing and blocking fake news through natural language processing or detecting social media influencer accounts that spread false information by combining with network causal inference could be implemented through deep learning. However, fake news detection is classified as a difficult problem to solve among many natural language processing fields. Due to the variety of forms and expressions of fake news, the difficulty of feature extraction is high, and there are various limitations, such as that one feature may have different meanings depending on the category to which the news belongs. In this paper, emotional change patterns are presented as an additional identification criterion for detecting fake news. We propose a model with improved performance by applying a convolutional neural network to a fake news data set to perform analysis based on content characteristics and additionally analyze emotional change patterns. Sentimental polarity is calculated for the sentences constituting the news and the result value dependent on the sentence order can be obtained by applying long-term and short-term memory. This is defined as a pattern of emotional change and combined with the content characteristics of news to be used as an independent variable in the proposed model for fake news detection. We train the proposed model and comparison model by deep learning and conduct an experiment using a fake news data set to confirm that emotion change patterns can improve fake news detection performance.

• Journal of Software Assessment and Valuation
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• v.15 no.2
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• pp.111-119
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• 2019

The existing smart grid device authentication system is concentrated on DCU, meter reading FEP and MDMS, and the authentication system for smart meters is not established. Although some cryptographic chips have been developed at present, it is difficult to complete the PKI authentication scheme because it is at the low level of simple encryption. Unlike existing power grids, smart grids are based on open two-way communication, increasing the risk of accidents as information security vulnerabilities increase. However, PKI is difficult to apply to smart meters, and there is a possibility of accidents such as system shutdown by sending manipulated packets and sending false information to the operating system. Issuing an existing PKI certificate to smart meters with high hardware constraints makes authentication and certificate renewal difficult, so an ultra-lightweight password authentication protocol that can operate even on the poor performance of smart meters (such as non-IP networks, processors, memory, and storage space) was designed and implemented. As a result of the experiment, lightweight cryptographic authentication protocol was able to be executed quickly in the Cortex-M3 environment, and it is expected that it will help to prepare a more secure authentication system in the smart grid industry.