• KSII Transactions on Internet and Information Systems (TIIS)
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• 제16권6호
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• pp.1818-1832
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• 2022

Violence in the Internet era poses a new challenge to the current counter-riot work, and according to research and analysis, most of the violent incidents occurring are related to the dissemination of violence images. The use of the popular deep learning neural network to automatically analyze the massive amount of images on the Internet has become one of the important tools in the current counter-violence work. This paper focuses on the use of transfer learning techniques and the introduction of an attention mechanism to the residual network (ResNet) model for the classification and identification of violence images. Firstly, the feature elements of the violence images are identified and a targeted dataset is constructed; secondly, due to the small number of positive samples of violence images, pre-training and attention mechanisms are introduced to suggest improvements to the traditional residual network; finally, the improved model is trained and tested on the constructed dedicated dataset. The research results show that the improved network model can quickly and accurately identify violence images with an average accuracy rate of 92.20%, thus effectively reducing the cost of manual identification and providing decision support for combating rebel organization activities.

• International journal of advanced smart convergence
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• 제5권1호
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• pp.23-29
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• 2016

The information is to be considered as important part of any network, the communication nodes within network can able to communicate and transmit information by the means of configured LAN/WAN, or/and using internet technology. Thus, vast enhancement has been made in- exchanging of information over transmission media, this should be beneficial in various disciplines of modern client/server applications but at other side, several massive vulnerabilities have been directly/in-directly associated with them. To resolve the security issues, a security mechanism is proposed which hide the sensitive information of images before transmitting to networks. Random size image samples have used and encrypted to protect them from unauthorized entities. The encryption mechanism manipulates the sample images, and corresponding secret codes are generated which help to protect the images from adversaries. To provide an indestructible security mechanism, cryptography algorithms are deployed and considered as best solutions to keep the secret information of images.

• ETRI Journal
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• 제28권4호
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• pp.444-452
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• 2006

Biometric-based authentication can provide a strong security guarantee of the identity of users. However, the security of biometric data is particularly important as any compromise of the biometric data will be permanent. In this paper, we propose a secure and efficient protocol to transmit fingerprint images from a fingerprint sensor to a client by exploiting the characteristics of the fingerprint images. Because the fingerprint sensor is computationally limited, a standard encryption algorithm may not be applied to the full fingerprint images in real-time to guarantee the integrity and confidentiality of the fingerprint images transmitted. To reduce the computational workload on the resource-constrained sensor, we apply the encryption algorithm to a nonce for integrity and to a specific bitplane of each pixel of the fingerprint image for confidentiality. Experimental results show that the integrity and confidentiality of the fingerprint images can be guaranteed without any leakage of the fingerprint ridge information and can be completed in real-time on embedded processors.

• International Journal of Computer Science & Network Security
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• 제24권3호
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• pp.93-100
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• 2024

In this paper, we propose a novel robust blind crypto-watermarking method for medical images security based on hiding of DICOM patient information (patient name, age...) in the medical imaging. The DICOM patient information is encrypted using the AES standard algorithm before its insertion in the medical image. The cover image is divided in blocks of 8x8, in each we insert 1-bit of the encrypted watermark in the hybrid transform domain by applying respectively the 2D-LWT (Lifting wavelet transforms), the 2D-DCT (discrete cosine transforms), and the SVD (singular value decomposition). The scheme is tested by applying various attacks such as noise, filtering and compression. Experimental results show that no visible difference between the watermarked images and the original images and the test against attack shows the good robustness of the proposed algorithm.

• 정보보호학회논문지
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• 제22권4호
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• pp.761-770
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• 2012

컴퓨터와 사람을 구분하기 위한 수단인 캡차는 광고, 스팸 메일, DDoS 등의 공격을 하는 자동화된 봇을 막기 위해 널리 사용되고 있다. 초창기에는 문자가 출력된 이미지를 왜곡시켜 이를 컴퓨터가 식별하기 어렵도록 하는 방식이 주로 사용되었지만, 이러한 방법들은 인공지능 기법이나 이미지 처리 기법으로 쉽게 무력화 될 수 있음이 여러 연구들을 통해 밝혀졌다. 그러한 이유에서 문자 기반 캡차의 대안으로 이미지를 사용하는 캡차가 주목받게 되었고 그에 따라 여러 가지 형태의 이미지 기반 캡차가 제안되었다. 하지만 텍스트 기반 캡차보다 높은 보안성을 제공하기 위해서는 많은 양의 소스 이미지가 필요하였다. 이에 따라 강전일(2008) 등은 소규모의 이미지 데이터베이스를 이용한 이미지 기반 캡차를 제안하였다. 이 캡차는 사용자 실험을 통해 현재 널리 사용되는 문자 기반 캡차에 비해 사용자 편의성을 보였지만, 아직 안전성이 검증되지 않았다. 이 논문에서는 강전일(2008)등이 제안한 복수의 이미지를 합성하여 사용하는 캡차를 실제로 공격해봄으로써 해당 캡차의 안전성을 검증해 보았다.

• Journal of Electrical Engineering and Technology
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• 제10권2호
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• pp.659-669
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• 2015

Face Recognition assumes much significance in the context of security based application. Normally, high resolution images offer more details about the image and recognizing a face from a reasonably high resolution image would be easier when compared to recognizing images from very low resolution images. This paper addresses the problem of recognizing faces from a very low resolution image whose size is as low as $8{\times}8$. With the use of CCTV(Closed Circuit Television) and with other surveillance camera-based application for security purposes, the need to overcome the shortcomings with very low resolution images has been on the rise. The present day face recognition algorithms could not provide adequate performance when employed to recognize images from VLR images. Existing methods use super-resolution (SR) methods and Relation Based Super Resolution methods to construct from very low resolution images. This paper uses a learning based super resolution method to extract and construct images from very low resolution images. Experimental results show that the proposed SR algorithm based on relationship learning outperforms the existing algorithms in public face databases.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제9권12호
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• pp.5058-5072
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• 2015

Quaternions have been commonly employed in color image processing, but when the existing pure quaternion representation for color images is used in perceptual hashing, it would degrade the robustness performance since it is sensitive to image manipulations. To improve the robustness in color image perceptual hashing, in this paper a full quaternion representation for color images is proposed by introducing the local image luminance variances. Based on this new representation, a novel Full Quaternion Discrete Cosine Transform (FQDCT)-based hashing is proposed, in which the Quaternion Discrete Cosine Transform (QDCT) is applied to the pseudo-randomly selected regions of the novel full quaternion image to construct two feature matrices. A new hash value in binary is generated from these two matrices. Our experimental results have validated the robustness improvement brought by the proposed full quaternion representation and demonstrated that better performance can be achieved in the proposed FQDCT-based hashing than that in other notable quaternion-based hashing schemes in terms of robustness and discriminability.

• 전기전자학회논문지
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• 제23권4호
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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.

• 한국멀티미디어학회논문지
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• 제7권3호
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• pp.349-356
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• 2004

본 논문에서는 SA(simulated annealing) 알고리듬에 기반한 4-f 광 상관 시스템을 이용하여 실제적인 영상 보안 시스템을 제안하였다. 반복적인 SA알고리듬을 이용하여 이진 위상 성분을 갖는 암호화된 영상과 키 영상을 얻고, 4-f 광 상관 시스템을 이용하여 암호화된 영상과 키 영상과의 상관을 통해 복호화된 영상이 구해진다. 제안된 방법에서는 암호화된 영상 및 키 영상이 이진 위상 성분으로 구성되므로 광 보안 시스템을 구현하기 쉬운 장점이 있다. 그리고 만약 암호화된 영상을 암호화 시스템내에서 고정시키고, 키 영상 정보만을 달리 하면 서로 다른 영상을 복호화할 수 있으므로 차별화된 인증시스템에 응용할 수 있는 장점도 있다. 컴퓨터 시뮬레이션 결과는 두 영상(암호화 및 키 영상)의 이진 위상 성분에도 불구하고, 복호화영상이 생성됨을 보여준다.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2003년도 ICCAS
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• pp.1240-1243
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• 2003

In this paper, an encryption method to share a secret binary image is proposed. It divides the image to be encrypted into an arbitrary number of images and encrypts them using XOR process with different binary random images which was prepared by the means of the XOR process, too. Each encrypted slice image can be distributed to the authenticated ones. However, we transfer the encrypted images to the binary phase masks to strengthen the security power, that means phase masks can not be copied with general light-intensity sensitive tools such as CCDs or cameras. For decryption, we used the Mach-Zehnder interferometer in which linearly polarized two light beams in orthogonal direction, respectively. The experimental result proved the efficiency of the proposed method.