• Proceedings of the Korea Information Processing Society Conference
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• 2016.04a
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• pp.186-188
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• 2016

본 논문에서는 모바일 환경에서 동적서명인식에 관해 원본서명과 숙련된 위조서명의 구분을 검증하는 방법을 제안한다. 속도/거리 정보 실험(Data1)과 속도/거리정보와 가속도계를 추가 실험(Data2)을 원본 서명과 위조서명에 대한 테이블을 만들고, 비교하여 원본 서명의 인식률 확인한다. 제시한 방법은 각각 모바일 환경에서 10명이 20 번삑 손가락으로 테스트 하였다. 원본서명에서 딥 러닝중의 하나인 MLP를 실험한 결과 원본 서명에서 Data1은 92%, Data2는 95%의 정확도를 보였으며, 위조서명에서 Data1은 82%, Data2는 85%를 보였다. 그리고 AE에서 실험한 결과 Data1은 원본 서명에서 Data1은 95%, Data2는 97%의 정확도를 보였으며, 위조서명에서 Data1은 91.5%, Data2는 93%의 정확도가 보였다. 실험결과 위조서명에 대해서는 MLP로 위조서명을 분류하는 것보다 OAE에서 분류하는 것이 더 좋은 정확도를 보여준다.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.54 no.9
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• pp.531-538
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• 2005

This paper proposes an expert system which is able to enhance the accuracy and productivity by determining the test strategy based on heuristic rules for test of the hybrid electronic circuit board producted massively in production line. The test heuristic rules are obtained from test system designer, test experts and experimental results. The guarding method separating the tested device with circumference circuit of the device is adopted to enhance the accuracy of measurements in the test of analog devices. This guarding method can reduce the error occurring due to the voltage drop in both the signal input line and the measuring line by utilizing heuristic rules considering the device impedance and the parallel impedance. Also, PSA(Parallel Signature Analysis) technique Is applied for test of the digital devices and circuits. In the PSA technique, the real-time test of the high integrated device is possible by minimizing the test time forcing n bit output stream from the tested device to LFSR continuously. It is implemented in Visual C++ computer language for the purpose of the implementation of the inference engine using the dynamic memory allocation technique, the interface with the electronic circuit database and the hardware direct control. Finally, the effectiveness of the builded expert system is proved by simulating the several faults occurring in the mounting process the electronic devices to the surface of PCB for a typical hybrid electronic board and by identifying the results.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.2
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• pp.617-636
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• 2021

This paper presents a privacy-preserving data aggregation scheme deals with the multidimensional data. It is essential that the multidimensional data is rarely mentioned in all researches on smart grid. We use the Paillier Cryptosystem and blinding factor technique to encrypt the multidimensional data as a whole and take advantage of the homomorphic property of the Paillier Cryptosystem to achieve data aggregation. Signature and efficient batch verification have also been applied into our scheme for data integrity and quick verification. And the efficient batch verification only requires 2 pairing operations. Our scheme also supports fault tolerance which means that even some smart meters don't work, our scheme can still work well. In addition, we give two extensions of our scheme. One is that our scheme can be used to compute a fixed user's time-of-use electricity bill. The other is that our scheme is able to effectively and quickly deal with the dynamic user situation. In security analysis, we prove the detailed unforgeability and security of batch verification, and briefly introduce other security features. Performance analysis shows that our scheme has lower computational complexity and communication overhead than existing schemes.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.9
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• pp.3258-3273
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• 2021

Malware is a severe threat to the computing system and there's a long history of the battle between malware detection and anti-detection. Most traditional detection methods are based on static analysis with signature matching and dynamic analysis methods that are focused on sensitive behaviors. However, the usual detections have only limited effect when meeting the development of malware, so that the manual update for feature sets is essential. Besides, most of these methods match target samples with the usual feature database, which ignored the characteristics of the sample itself. In this paper, we propose a new malware detection method that could combine the features of a single sample and the general features of malware. Firstly, a structure of Directed Cyclic Graph (DCG) is adopted to extract features from samples. Then the sensitivity of each API call is computed with Markov Chain. Afterward, the graph is merged with the chain to get the final features. Finally, the detectors based on machine learning or deep learning are devised for identification. To evaluate the effect and robustness of our approach, several experiments were adopted. The results showed that the proposed method had a good performance in most tests, and the approach also had stability with the development and growth of malware.

• KIPS Transactions on Computer and Communication Systems
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• v.11 no.10
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• pp.363-372
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• 2022

Since the recent COVID-19 Pandemic, the ransomware fandom has intensified along with the expansion of remote work. Currently, anti-virus vaccine companies are trying to respond to ransomware, but traditional file signature-based static analysis can be neutralized in the face of diversification, obfuscation, variants, or the emergence of new ransomware. Various studies are being conducted for such ransomware detection, and detection studies using signature-based static analysis and behavior-based dynamic analysis can be seen as the main research type at present. In this paper, the frequency of ".text Section" Opcode and the Native API used in practice was extracted, and the association between feature information selected using K-means Clustering algorithm, Cosine Similarity, and Pearson correlation coefficient was analyzed. In addition, Through experiments to classify and detect worms among other malware types and Cerber-type ransomware, it was verified that the selected feature information was specialized in detecting specific ransomware (Cerber). As a result of combining the finally selected feature information through the above verification and applying it to machine learning and performing hyper parameter optimization, the detection rate was up to 93.3%.

• The Bulletin of The Korean Astronomical Society
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• v.38 no.2
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• pp.89.1-89.1
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• 2013

We present a multiwavelength study of the X-class flare, which occurred in active region (AR) NOAA 11339 on 3 November 2011. The EUV images recorded by SDO/AIA show the activation of a remote filament (located north of the AR) with footpoint brightenings about 50 min prior to the flare occurrence. The kinked filament rises-up slowly and after reaching a projected height of ~49 Mm, it bends and falls freely near the AR, where the X-class flare was triggered. Dynamic radio spectrum from the Green Bank Solar Radio Burst Spectrometer (GBSRBS) shows simultaneous detection of both positive and negative drifting pulsating structures (DPSs) in the decimetric radio frequencies (500-1200 MHz) during the impulsive phase of the flare. The global negative DPSs in solar flares are generally interpreted as a signature of electron acceleration related to the upward moving plasmoids in the solar corona. The EUV images from AIA $94{\AA}$ reveal the ejection of multiple plasmoids, which move simultaneously upward and downward in the corona during the magnetic reconnection. The estimated speeds of the upward and downward moving plasmoids are ~152-362 and ~83-254 km/s, respectively. These observations strongly support the recent numerical simulations of the formation and interaction of multiple plasmoids due to tearing of the current-sheet structure. On the basis of our analysis, we suggest that the simultaneous detection of both the negative and positive DPSs is most likely generated by the interaction/coalescence of the multiple plasmoids moving upward and downward along the current-sheet structure during the magnetic reconnection process. Moreover, the differential emission measure (DEM) analysis of the active region reveals presence of a hot flux-rope structure (visible in AIA 131 and $94{\AA}$) prior to the flare initiation and ejection of the multi-temperature plasmoids during the flare impulsive phase.

• Asian-Australasian Journal of Animal Sciences
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• v.31 no.7
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• pp.1062-1071
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• 2018

The misuse of anabolic hormones or illegal drugs is a ubiquitous problem in animal husbandry and in food safety. The ban on growth promotants in food producing animals in the European Union is well controlled. However, application regimens that are difficult to detect persist, including newly designed anabolic drugs and complex hormone cocktails. Therefore identification of molecular endogenous biomarkers which are based on the physiological response after the illicit treatment has become a focus of detection methods. The analysis of the 'transcriptome' has been shown to have promise to discover the misuse of anabolic drugs, by indirect detection of their pharmacological action in organs or selected tissues. Various studies have measured gene expression changes after illegal drug or hormone application. So-called transcriptomic biomarkers were quantified at the mRNA and/or microRNA level by reverse transcription-quantitative polymerase chain reaction (RT-qPCR) technology or by more modern 'omics' and high throughput technologies including RNA-sequencing (RNA-Seq). With the addition of advanced bioinformatical approaches such as hierarchical clustering analysis or dynamic principal components analysis, a valid 'biomarker signature' can be established to discriminate between treated and untreated individuals. It has been shown in numerous animal and cell culture studies, that identification of treated animals is possible via our transcriptional biomarker approach. The high throughput sequencing approach is also capable of discovering new biomarker candidates and, in combination with quantitative RT-qPCR, validation and confirmation of biomarkers has been possible. These results from animal production and food safety studies demonstrate that analysis of the transcriptome has high potential as a new screening method using transcriptional 'biomarker signatures' based on the physiological response triggered by illegal substances.

• Smart Structures and Systems
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• v.1 no.1
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• pp.83-101
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• 2005

This paper summarizes the application of a rational methodology for the structural assessment of older reinforced concrete Tunisian bridges. This methodology is based on ambient vibration measurement of the bridge, identification of the structure's modal signature and finite element model updating. The selected case study is the Boujnah bridge of the Tunis-Msaken Highway. This bridge is made of a continuous four-span simply supported reinforced concrete slab without girders resting on elastomeric bearings at each support. Ambient vibration tests were conducted on the bridge using a data acquisition system with nine force-balance accelerometers placed at selected locations of the bridge. The Enhanced Frequency Domain Decomposition technique was applied to extract the dynamic characteristics of the bridge. The finite element model was updated in order to obtain a reasonable correlation between experimental and numerical modal properties. For the model updating part of the study, the parameters selected for the updating process include the concrete modulus of elasticity, the elastic bearing stiffness and the foundation spring stiffnesses. The primary objective of the paper is to demonstrate the use of the Enhanced Frequency Domain Decomposition technique combined with model updating to provide data that could be used to assess the structural condition of the selected bridge. The application of the proposed methodology led to a relatively faithful linear elastic model of the bridge in its present condition.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.5C
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• pp.726-736
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• 2004

In this paper, we proposed a new scalar multiplier structure needed for an elliptic curve cryptosystem(ECC) over the standard basis in GF(2$^{163}$ ). It consists of a bit-serial multiplier and a divider with control logics, and the divider consumes most of the processing time. To speed up the division processing, we developed a new division algorithm based on the extended Euclid algorithm. Dynamic data dependency of the Euclid algorithm has been transformed to static and fixed data flow by a localization technique, to make it independent of the input and field polynomial. Compared to other existing scalar multipliers, the new scalar multiplier requires smaller gate counts with improved processor performance. It has been synthesized using Samsung 0.18 um CMOS technology, and the maximum operating frequency is estimated 250 MHz. The resulting performance is 148 kbps, that is, it takes 1.1 msec to process a 163-bit data frame. We assure that this performance is enough to be used for digital signature, encryption/decryption, and key exchanges in real time environments.

• Atmosphere
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• v.23 no.3
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• pp.331-346
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• 2013

A case study of mesoscale snowfall with polar low signature during 25~26 December 2010 in South Korea is presented. The data used for analysis include surface and upper level weather charts, rain gauge, sea surface temperature, satellite imagery, sounding, and global $1^{\circ}{\times}1^{\circ}$ reanalysis data. The system initiated with a surface trough near the bay of Bohai but quickly intensified to become a polar low within 12 hours. The polar low moved southeastward bringing snowfall to southwestern Korea. There was strong instability layer beneath 800 hPa but baroclinicty was weak and disappeared as the low progressed onto land. Shortwave at 500 hPa and the surface trough became in-phase which hindered the development of the polar low while it approached Korea. However, there were strong tropopause folding (~500 hPa) and high potential vorticity (PV), which allowed the system to maintain its structure and dump 20.3 cm of snow in Jeonju. Synoptic, thermodynamic, dynamic, and moisture analyses reveal that polar low developed in an area of baroclinicity with strong conditional instability and warm air advection at the lower levels. Further, the development of a surface trough to polar low was aided by tropopause folding with PV advection in the upper level, shortwave trough at 500 hPa, and moisture advection with low-level jet (LLJ) of 15 m $s^{-1}$ or more at 850 hPa. Maximum snowfall was concentrated in this region with convection being sustained by latent heat release.