• Journal of the Korea Institute of Military Science and Technology
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• v.26 no.1
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• pp.44-53
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• 2023

Adversarial attacks have received great attentions for their capacity to distract state-of-the-art neural networks by modifying objects in physical domain. Patch-based attack especially have got much attention for its optimization effectiveness and feasible adaptation to any objects to attack neural network-based object detectors. However, despite their strong attack performance, generated patches are strongly perceptible for humans, violating the fundamental assumption of adversarial examples. In this paper, we propose a camouflaged adversarial patch optimization method using military camouflage assessment metrics for naturalistic patch attacks. We also investigate camouflaged attack loss functions, applications of various camouflaged patches on army tank images, and validate the proposed approach with extensive experiments attacking Yolov5 detection model. Our methods produce more natural and realistic looking camouflaged patches while achieving competitive performance.

• Annual Conference of KIPS
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• 2008.05a
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• pp.913-916
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• 2008

TPS(Triple Play Service)를 통한 IP-TV,인터넷, 전화 등이 통합되는 추세에서, IPv6 상용네트워크가 수 년 안에 구축될 필연성을 공감하고 있다. 그러나 [1] 현재 IP-TV 서비스에서 Delay, Jitter,전송장애등 QoS에 대한 사용자 불만이 계속 발생하고 있다. 또한 현재 서비스중지 (DoS : Denial of Service)를 유발하는 [2] 인터넷 침해 사고가 월 평균 2157건 이상 발생하는 등, Security Issue의 증가 문제가 지속 되고 있다. IPv4/IPv6 듀얼 스택 멀티 캐스트 네트워크를 구현하여, 라우팅, 멀티캐스트(PIM-SM), QoS, Security 이슈에 대한, 최적의 방안을 도출하여, 라우팅 구현시 IPv6 라우팅 프로토클 간에 재분배(Redistribution) 장애 해결책, IPv6 특성에 따른 멀티캐스트 그룹주소 지정시의 장애대책을 제시하였고, QoS 에서는 기존의 QoS 정책의 문제점과 IPv6의 고유한 패킷 구조의 장점을 활용한 Adaptive QoS 방법을 제시하고, IPv6 멀티캐스트 서비스 중지 공격 유형을 정의하여, 최적화된 IPv6 멀티캐스트 구성 모델을 제시 하였다. 결론적으로 구현된 시스템에서 IPv6 패킷 분석을 통해서 최적화된 경로 통신 및 차별화된 IPv6 패킷의 QoS 방안을 제시하였으며, 서비스 중지공격을 대응하는 Security 보장성을 갖고 있음을 검증하여, 향후 상용화된 IPv4/IPv6 네트워크 구현을 위한 최적화 방안을 제시 하였다.

• Journal of Korea Multimedia Society
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• v.6 no.3
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• pp.508-517
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• 2003

This paper presents perceptual model with a stochastic multiresolution characteristic that can be applied with watermark embedding in the biorthogonal wavelet domain. The perceptual model with adaptive watermarking algorithm embeds at the texture and edge region for more strongly embedded watermark by the SSQ. The watermark embedding is based on the computation of a NVF that has local image properties. This method uses non- stationary Gaussian and stationary Generalized Gaussian models because watermark has noise properties. The particularities of embedding in the stationary GG model use shape parameter and variance of each subband regions in multiresolution. To estimate the shape parameter, we use a moment matching method. Non-stationary Gaussian model uses the local mean and variance of each subband. The experiment results of simulation were found to be excellent invisibility and robustness. Experiments of such distortion are executed by Stirmark 3.1 benchmark test.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.31 no.3
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• pp.401-410
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• 2021

Recently, as cyber attacks targeting industrial control systems increase, various studies are being conducted on the detection of abnormalities in industrial processes. Considering that the industrial process is deterministic and regular, It is appropriate to determine abnormality by comparing the predicted value of the detection model from which normal data is trained and the actual value. In this paper, HAI Datasets 20.07 and 21.03 are used. In addition, an ensemble model is created by combining models that have applied different time steps to Gated Recurrent Units. Then, the detection performance of the single model and the ensemble recurrent neural networks model were compared through various performance evaluation analysis, and It was confirmed that the proposed model is more suitable for abnormal detection in industrial control systems.

• KNOM Review
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• v.24 no.2
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• pp.24-34
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• 2021

Service providers using edge computing provide a high level of service. As a result, devices store important information in inner storage and have become a target of the latest cyberattacks, which are more difficult to detect. Although experts use a security system such as intrusion detection systems, the existing intrusion systems have low detection accuracy. Therefore, in this paper, we proposed a machine learning model for more accurate intrusion detections of devices in edge computing. The proposed model is a hybrid model that combines a stacked sparse autoencoder (SSAE) and a convolutional neural network (CNN) to extract important feature vectors from the input data using sparsity constraints. To find the optimal model, we compared and analyzed the performance as adjusting the sparsity coefficient of SSAE. As a result, the model showed the highest accuracy as a 96.9% using the sparsity constraints. Therefore, the model showed the highest performance when model trains only important features.

• The KIPS Transactions:PartB
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• v.15B no.4
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• pp.307-314
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• 2008

This paper presents a new robust watermarking method for curves that uses informed-detection. To embed watermarks, the presented algorithm parameterizes a curve using the B-spline model and acquires the control points of the B-spline model. For these control points, 2D mesh are created by applying Delaunay triangulation and then the mesh spectral analysis is performed to calculate the mesh spectral coefficients where watermark messages are embedded in a spread spectrum way. The watermarked coefficients are inversely transformed to the coordinates of the control points and the watermarked curve is reconstructed by calculating B-spline model with the control points. To detect the embedded watermark, we apply curve matching algorithm using inflection points of curve. After curve registration, we calculate the difference between the original and watermarked mesh spectral coefficients with the same process for embedding. By calculating correlation coefficients between the detected and candidate watermark, we decide which watermark was embedded. The experimental results prove the proposed scheme is more robust than previous watermarking schemes against print-scan process as well as geometrical distortions.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.8
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• pp.530-536
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• 2020

The use of minutiae by fingerprint readers is robust against presentation attacks, but one weakness is that the mismatch rate is high. Therefore, minutiae tend to be used with skeleton images. There have been many studies on security vulnerabilities in the characteristics of minutiae, but vulnerability studies on the skeleton are weak, so this study attempts to analyze the vulnerability of presentation attacks against the skeleton. To this end, we propose a method based on the skeleton to recover the original fingerprint using a learning algorithm. The proposed method includes a new learning model, Pix2Pix, which adds a latent vector to the existing Pix2Pix model, thereby generating a natural fingerprint. In the experimental results, the original fingerprint is restored using the proposed machine learning, and then, the restored fingerprint is the input for the fingerprint reader in order to achieve a good recognition rate. Thus, this study verifies that fingerprint readers using the skeleton are vulnerable to presentation attacks. The approach presented in this paper is expected to be useful in a variety of applications concerning fingerprint restoration, video security, and biometrics.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.48 no.3
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• pp.76-81
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• 2011

Intrusion prevention systems (IPS) are important solution about solved problems for inside system security or outsider attacks. When introduce this system, first consideration item is secured rather than multiple function. Colored Petri Nets (CPNs) used that in order to secured verification for user authentication function of intrusion prevention system security model. CPNs is a graphical modeling language suitable for modeling distributed, concurrent, deterministic or non-deterministic systems with synchronous. Like these CPNs was expressed every possible state and occurrence graph. Secured of IPS security model was verified because expression every state using CPN tool and as a result of analyzing the occurrence graph was without a loop or interruption.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.9B
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• pp.867-875
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• 2009

The reliability of wireless body area networks is an important research issue since it may jeopardize the vital human life, unless managed properly. In this article, a new modeling and analysis of node misbehaviors in wireless body area networks is presented, in the presence of multi-type failures. First, the nodes are classified into types in accordance with routing capability. Then, the node behavior in the presence of failures such as energy exhaustion and/or malicious attacks has been modeled using a novel Semi-Markov process. The proposed model is very useful in analyzing reliability of WBANs in the presence of multi-type failures.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.22 no.4
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• pp.913-921
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• 2012

On the strength of the rapid development and propagation of U-healthcare service, the service technologies are full of important changes. However, U-healthcare service has security problem that patient's biometric information can be easily exposed to the third party without service users' consent. This paper proposes a distributed model according authority and access level of hospital officials in order to safely access patients' private information in u-Healthcare Environment. Proposed model can both limit the access to patients' biometric information and keep safe system from DoS attack using time stamp. Also, it can prevent patients' data spill and privacy intrusion because the main server simultaneously controls hospital officials and the access by the access range of officials from each hospital.