• Journal of Multimedia Information System
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• v.9 no.2
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• pp.103-112
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• 2022

Background: A presentation attack places the printed image or displayed video at the front of the sensor to deceive the biometric recognition system. Usually, presentation attackers steal a genuine user's biometric image and use it for presentation attack. In recent years, reconstruction attack and adversarial attack can generate high-quality fake images, and have high attack success rates. However, their attack rates degrade remarkably after image shooting. Methods: In order to comprehensively analyze the threat of presentation attack to palmprint recognition system, this paper makes six palmprint presentation attack datasets. The datasets were tested on texture coding-based recognition methods and deep learning-based recognition methods. Results and conclusion: The experimental results show that the presentation attack caused by the leakage of the original image has a high success rate and a great threat; while the success rates of reconstruction attack and adversarial attack decrease significantly.

• Journal of the Korea Institute of Military Science and Technology
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• v.19 no.2
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• pp.236-243
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• 2016

This paper presents a threat list acquisition method in an engagement area using the support vector machines (SVM). The proposed method consists of track creation, track estimation, track feature extraction, and threat list classification. To classify the threat track robustly, dynamic track estimation and pattern recognition algorithms are used. Dynamic tracks are estimated accurately by approximating a track movement using position, velocity and time. After track estimation, track features are extracted from the track information, and used to classify threat list. Experimental results showed that the threat list acquisition method in the engagement area achieved about 95 % accuracy rate for whole test tracks when using the SVM classifier. In case of improving the real-time process through further studies, it can be expected to apply the fire control systems.

• Strategy21
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• s.44
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• pp.142-176
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• 2018

So far, the main threat to South Korea was North Korea. That is why South Korea established a strategy based on the threat of North Korea and most of the budget on defense was used to deter North Korea. Even though the neighboring countries(China, Japan, and Russia) are growing as a real threat with abilities and intentions based on their powerful naval forces, South Korea has not yet been able to establish a strategy that regards neighboring countries as a threat. But the decades-old structural mechanism of the Korean security environment is undergoing a radical change on April 27, 2018, through the South-North summit and the Panmunjom Declaration. Under the changing security environment, South Korea was placed in a complicated dilemma that had to deal with threats of two axes(China), three axes(China, Japan), and four axes(Japan, Russia). If the one axis threat(North Korea) is dominated by land threats, the second, third and fourth axis threats are threats from the sea. This paper analyzed the maritime strategy of Korea within the framework of maritime-geopolitics, in other words recognition and expansion of the sphere of maritime. I have designed that the maritime defense space that we can deny from threats is divided into three lines of defense: 1 line (radius 3,000km), 2 lines (2,000km), and 3 lines (1,000km). The three defense zones of the three lines were defined as an active defense(1 line), defensive offense(2 line), active offense(3 line). The three defense zones of the three lines were defined as the sphere of core maritime, As a power to deny the sphere of core maritime, it was analyzed as a maneuvering unit, a nuclear-powered submarine, the establishment of missile strategy, and the fortification of islands station. The marine strategy of South Korea with these concepts and means was defined as 'Offensive Maritime Denial Strategy'.

• Journal of IKEEE
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• v.23 no.4
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• pp.1134-1139
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• 2019

One of the most important applications of computer vision algorithms is the detection of threat objects in x-ray security images. However, in the practical setting, this task is complicated by two properties inherent to the dataset, namely, the problem of class imbalance and visual complexity. In our previous work, we resolved the class imbalance problem by using a GAN-based anomaly detection to balance out the bias induced by training a classification model on a non-practical dataset. In this paper, we propose a new method to alleviate the visual complexity problem by using a KNN-based automatic cropping algorithm to remove distracting and irrelevant information from the x-ray images. We use the cropped images as inputs to our current model. Empirical results show substantial improvement to our model, e.g. about 3% in the practical dataset, thus further outperforming previous approaches, which is very critical for security-based applications.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.34 no.4
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• pp.577-586
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• 2024

As new technologies are developed, new security threats such as the emergence of AI technologies that create ransomware are also increasing. New security equipment such as XDR has been developed to cope with these security threats, but when using various security equipment together rather than a single security equipment environment, there is a difficulty in creating numerous regular expressions for identifying and classifying essential data. To solve this problem, this paper proposes a method of identifying essential information for identifying threat information by introducing artificial intelligence-based entity name recognition technology in various security equipment usage environments. After analyzing the security equipment log data to select essential information, the storage format of information and the tag list for utilizing artificial intelligence were defined, and the method of identifying and extracting essential data is proposed through entity name recognition technology using artificial intelligence. As a result of various security equipment log data and 23 tag-based entity name recognition tests, the weight average of f1-score for each tag is 0.44 for Bi-LSTM-CRF and 0.99 for BERT-CRF. In the future, we plan to study the process of integrating the regular expression-based threat information identification and extraction method and artificial intelligence-based threat information and apply the process based on new data.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.21 no.4
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• pp.15-23
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• 2021

In most hacking attacks, hackers intrudes inside for a long period of time and attempts to communicate with the outside using a circumvent connection to achieve purpose. research in response to advanced and intelligent cyber threats has been mainly conducted with signature-based detection and blocking methods, but recently it has been extended to threat hunting methods. attacks from organized hacking groups are advanced persistent attacks over a long period of time, and bypass remote attacks account for the majority. however, even in the intrusion detection system using intelligent recognition technology, it only shows detection performance of the existing intrusion status. therefore, countermeasures against targeted bypass rwjqthrwkemote attacks still have limitations with existing detection methods and threat hunting methods. in this paper, to overcome theses limitations, we propose a model that can detect the targeted circumvent connection remote attack threat of an organized hacking group. this model designed a threat hunting process model that applied the method of verifying the origin IP of the remote circumvent connection, and verified the effectiveness by implementing the proposed method in actual defense information system environment.

• Journal of Aerospace System Engineering
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• v.15 no.2
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• pp.36-44
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• 2021

Unmanned aerial vehicles (UAVs) are increasingly needed as they can replace manned aircrafts in dangerous military missions. However, because of their low autonomy, current UAVs can execute missions only under continuous operator control. To overcome this limitation, higher autonomy levels of UAVs based on autonomous situational awareness is required. In this paper, we propose an autonomous situational awareness software consisting of situation awareness management, threat recognition, threat identification, and threat space analysis to detect dynamic situational change by external threats. We implemented the proposed software in real mission computer hardware and evaluated the performance of situational awareness toward dynamic radar threats in flight simulations.

• 한국노년학
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• v.36 no.4
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• pp.1109-1124
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• 2016

We examined the effect of stereotype threat (STT) on spatial working memory and facial emotion recognition in Korean elderly. In addition, we investigated the role of expected moderator such as self-perception of aging. Seventeen seniors (male=7) received basic cognitive tests including K-WMS-IV, MMSE and answered self-report questionnaires including self-perception of aging, anxiety of aging, attitude toward aging and age identity on the first visit. On the second visit, they were exposed to negative stereotype by reading a script detailing cognitive decline related to aging while a control group was exposed to a neutral content. Following the exposure, they were tested on a spatial-working memory task (Corsi-block tapping task) and emotion recognition task (facial expression identification task). The results showed that the seniors exposed to STT showed significantly lower performance on emotion recognition task (p < .05) (i.e., especially on the more difficult facial stimuli). In addition, there was a significant interaction between STT and self-perception of aging (p< .05), indicating that those who have positive self-perception of aging did not show impairment in emotion recognition task and difficult spatial working memory task under STT. On the other hand, those with negative self-perception of aging showed impaired performance under STT. Taken together, the current study suggests that being exposed to STT could negatively influence cognitive and emotional functioning of elderly. Interestingly, having a positive self-perception of aging could protect the underperformance caused by STT.

• Journal of Convergence for Information Technology
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• v.11 no.10
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• pp.322-331
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• 2021

This study attempted to identify the multi-cultural acceptance level of freshmen in nursing colleges and to analyze the factors influencing it. For the research method, data were collected from 410 first-year nursing students at K University in W City through a questionnaire from March 1 to 28, 2021, and frequency, reliability analysis, t-test, ANOVA, correlation, and multiple regression were conducted using the open-source statistical package R. As a result of the study, the multi-cultural acceptance level of freshman in nursing colleges averaged 77.36 points, indicating that they have a slightly higher multi-cultural acceptance capacity, and as a result of analyzing the influence of multi-cultural acceptance related factors, Korean recognition requirements(𝛽=0.34, p<.001), perceived threat recognition for migrants (𝛽=0.29, p<.001), Experience in multi-cultural education(𝛽=0.14, p<.001), Recognition of the appropriate age for multi-cultural education (𝛽=0.20, p<.001) was statistically significant. According to results, it is necessary to develop and actively utilize regular curriculum and programs related to multi-culturalism for nursing students.

• The Journal of Society for e-Business Studies
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• v.26 no.2
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• pp.83-94
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• 2021

The need for recognition of partially occluded objects is increasing in the area of computer vision applications. Occlusion causes significant problems in identifying and locating an object. In this paper, an annealed Hopfield network (AHN) is proposed for detecting threat objects in passengers' check-in baggage. AHN is a deterministic approximation that is based on the hybrid Hopfield network (HHN) and annealing theory. AHN uses boundary features composed of boundary points and corner points which are extracted from input images of threat objects. The critical temperature also is examined to reduce the run time of AHN. Extensive computational experiments have been conducted to compare the performance of the AHNwith that of the HHN.