• 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 Information Security & Cryptology
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• v.32 no.3
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• pp.527-545
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• 2022

In order to effectively detect APT attacks performed by well-organized adversaries, we implemented a system to detect attacks by reconstructing attack chains of APT attacks. Our attack chain-based APT attack detection system consists of 'events collection and indexing' part which collects various events generated from hosts and network monitoring tools, 'unit attack detection' part which detects unit-level attacks defined in MITRE ATT&CK^® techniques, and 'attack chain reconstruction' part which reconstructs attack chains by performing causality analysis based on provenance graphs. To evaluate our system, we implemented a test-bed and conducted several simulated attack scenarios provided by MITRE ATT&CK Evaluation program. As a result of the experiment, we were able to confirm that our system effectively reconstructed the attack chains for the simulated attack scenarios. Using the system implemented in this study, rather than to understand attacks as fragmentary parts, it will be possible to understand and respond to attacks from the perspective of progress of attacks.

• IEMEK Journal of Embedded Systems and Applications
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• v.18 no.6
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• pp.311-317
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• 2023

This paper presents a sliding mode observer (SMO) for reconstructing cyber attacks affecting a system. The system is first re-expressed such that its design freedom is easier to manipulate. The SMO is then used to reconstruct the cyber attack affecting the system. A simulation example is used to verify the performance of the SMO under two types of cyber attacks, and its results demonstrate the effectiveness of our proposed scheme.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.31 no.5
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• pp.987-999
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• 2021

Recently, Federated learning has become an issue due to privacy invasion caused by data. Federated learning is safe from privacy violations because it does not need to be collected into a server and does not require learning data. As a result, studies on application methods for utilizing distributed devices and data are underway. However, Federated learning is no longer safe as research on the reconstruction attack to restore learning data from gradients transmitted in the Federated learning process progresses. This paper is to verify numerically and visually how well data reconstruction attacks work in various data situations. Considering that the attacker does not know how the data is constructed, divide the data with the class from when only one data exists to when multiple data are distributed within the class, and use MNIST data as an evaluation index that is MSE, LOSS, PSNR, and SSIM. The fact is that the more classes and data, the higher MSE, LOSS, and PSNR and SSIM are, the lower the reconstruction performance, but sufficient privacy invasion is possible with several reconstructed images.

• Wind and Structures
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• v.38 no.1
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• pp.75-91
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• 2024

Reliable wind signal reconstruction can be beneficial to the operational safety of long-span bridges. Non-Gaussian characteristics of wind signals make the reconstruction process challenging. In this paper, non-Gaussian wind signals are converted into a combined prediction of two kinds of features, actual wind speeds and wind angles of attack. First, two decomposition techniques, empirical mode decomposition (EMD) and variational mode decomposition (VMD), are introduced to decompose wind signals into intrinsic mode functions (IMFs) to reduce the randomness of wind signals. Their principles and applicability are also discussed. Then, four artificial intelligence (AI) algorithms are utilized for wind signal reconstruction by combining the particle swarm optimization (PSO) algorithm with back propagation neural network (BPNN), support vector regression (SVR), long short-term memory (LSTM) and bidirectional long short-term memory (Bi-LSTM), respectively. Measured wind signals from a bridge site in a deep-cutting gorge are taken as experimental subjects. The results showed that the reconstruction error of high-frequency components of EMD is too large. On the contrary, VMD fully extracts the multiscale rules of the signal, reduces the component complexity. The combination of VMD-PSO-Bi-LSTM is demonstrated to be the most effective among all hybrid models.

• ETRI Journal
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• v.31 no.4
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• pp.408-418
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• 2009

Adopting an encryption function in voice over Wi-Fi service incurs problems such as additional power consumption and degradation of communication quality. To overcome these problems, a partial encryption (PE) algorithm for compressed speech was recently introduced. However, from the security point of view, the partial encryption sets (PESs) of the conventional PE algorithm still have much room for improvement. This paper proposes a new selection method for finding a smaller PES while maintaining the security level of encrypted speech. The proposed PES selection method employs the perceptual evaluation of the speech quality (PESQ) algorithm to objectively measure the distortion of speech. The proposed method is applied to the ITU-T G.729 speech codec, and content protection capability is verified by a range of tests and a reconstruction attack. The experimental results show that encrypting only 20% of the compressed bitstream is sufficient to effectively hide the entire content of speech.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.33 no.1
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• pp.63-74
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• 2023

In order to ensure safety to invasion of privacy, Federated Learning(FL) that learns using parameters is emerging. However a paper that leaks training data using gradients was recently published. Our paper implements an experiment to leak training data using gradients in a federated learning environment, and proposes a method to improve reconstruction performance by improving existing attacks that leak training data. Experiments using Yale face database B, MNIST dataset on the proposed method show that federated learning is not safe from invasion of privacy by reconstructing up to 100 data out of 100 training data when performance of federated learning is high at accuracy=99~100%. In addition, by comparing the performance (MSE, PSNR, SSIM) of pixels and the performance of identification by Human Test, we want to emphasize the importance of the performance of identification rather than the performance of pixels.

• Journal of the Korean Association of Oral and Maxillofacial Surgeons
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• v.46 no.5
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• pp.353-357
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• 2020

Fractures of the orbital floor and walls are among the most frequent maxillofacial fractures. Virtual three-dimensional (3D) planning and use of patient-specific implants (PSIs) could improve anatomic and functional outcomes in orbital reconstruction surgery. The presented case was a victim of a terrorist attack involving improvised explosive devices. This 58-year-old female suffered severe wounds caused by a single piece of metal from a bomb, shattering the left orbital floor and lateral orbital wall. Due to remaining hypotropia of the left eye compared to the right eye, late orbital floor reconstruction was carried out with a personalised 3D printed titanium implant. We concluded that this technique with PSI appears to be a viable method to correct complex orbital floor defects. Our research group noted good aesthetic and functional results one year after surgery. Due to the complexity of the surgery for a major bony defect of the orbital floor, it is important that the surgery be executed by experienced surgeons in the field of maxillofacial traumatology.

• Archives of Reconstructive Microsurgery
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• v.6 no.1
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• pp.56-62
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• 1997

Latissimus dorsi(LD) muscle is the largest transplantable block of vascularized tissue. Since LD free flap was introduced in 1970's, this flap has been widely used for the reconstruction of large soft tissue defect of the limb. From 1981 to 1996, we had experienced 37 cases of LD free flap. Serratus anterior muscle was combined with LD in three of them whose defects were very large. The average age of the patients was 31 years(range : 4-74 years), and thirty one patients were male. Trauma was cause of the defect in every case. For the recipient sites, the foot and ankle was the most common(22 cases); and the knee and lower leg(11 cases), the elbow and forearm(2 cases), the hand(2 cases) were the next. The duration of follow-up was averaged as 16 months(range: 6 months-12 years). Thirty one cases(84%) out of 37 were successful transplantations. In one case the failure of the flap was due to heart attack and subsequent death of the patient. One failure was caused by sudden violent seizure of the patient who had organic brain damage. Immediate reexploration of the flap was performed in 4 patients, and the flap survived in three of them. There was one necrosis of the grafted split-thickness skin on the survived LD flap. LD free flap was considered as one of the good methods, for the reconstruction of the large soft tissue defect of the limb.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.42 no.5
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• pp.951-958
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• 2017

In an attack context, the adversary wants to retrieve the message from the intercepted noisy bit stream without any prior knowledge of the channel codes used. The process of finding out the code parameters such as code length, dimension, and generator, for this purpose, is called the blind recognition of channel codes or the reconstruction of channel codes. In this paper, we suggest an improved algorithm of the blind recovery of rate k/n convolutional encoders in a noisy environment. The suggested algorithm improves the existing algorithm by Marazin, et. al. by evaluating the threshold value through the estimation of the channel error probability of the BSC. By applying the soft decision method by Shaojing, et. al., we considerably enhance the success rate of the channel reconstruction.