• Annual Conference of KIPS
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• 2013.05a
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• pp.640-643
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• 2013

차량용 블랙박스는 영상, 음성 및 자동차의 주행정보를 저장하는 매체로서 저장되는 데이터를 통해 차량 접촉사고 시 운전자의 과실여부를 판단할 수 있는 중요한 장치로 최근 자동차 시장에서 많은 주목을 받고 있다. 그러나 현재 차량용 블랙박스는 단순히 주행 데이터를 저장만 하고 있어 법적인 근거 자료로 활용되기 위해서는 데이터에 대한 무결성 보장을 제공하는 기능이 없는 상황이다. 블랙박스에 저장된 데이터는 공격자에 의해 위, 변조될 위험이 존재함으로 본 논문에서는 보다 안전한 환경에서의 무결성 보장을 위해 클라우드 컴퓨팅 환경에서의 무결성을 제공하는 시스템을 설계 한다.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.4
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• pp.522-528
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• 2020

Rapidly spreading malware, such as ransomware, trojans and Internet worms, have become one of the new major threats of the Internet recently. In order to resist against their malicious behaviors, it is essential to comprehend how malware propagate and how main factors affect spreads of them. In this paper, we aim to develop a spread prediction tool based on the modeling of malware epidemics. So we surveyed the related studies, and described the system design and implementation. In addition, we experimented on the spread of malware with major factors of malware using the developed spread prediction tool. If you make good use of the proposed prediction tool, it is possible to predict the malware spread at major factors and explore under various responses from a macro perspective with only basic knowledge of the recently wormable malware.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.5
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• pp.1687-1707
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• 2022

With the development of multiuser online meetings, more group-oriented technologies and applications for instance collaborative work are becoming increasingly important. Authenticated Group Key Agreement (AGKA) schemes provide a shared group key for users with after their identities are confirmed to guarantee the confidentiality and integrity of group communications. On the basis of the Public Key Cryptography (PKC) system used, AGKA can be classified as Public Key Infrastructure-based, Identity-based, and Certificateless. Because the latter type can solve the certificate management overhead and the key escrow problems of the first two types, Certificateless-AGKA (CL-AGKA) protocols have become a popular area of research. However, most CL-AGKA protocols are vulnerable to Public Key Replacement Attacks (PKRA) due to the lack of public key authentication. In the present work, we present a CL-AGKA scheme that can resist PKRA in order to solve impersonation attacks caused by those attacks. Beyond security, improving scheme efficiency is another direction for AGKA research. To reduce the communication and computation cost, we present a scheme with only one round of information interaction and construct a CL-AGKA scheme replacing the bilinear pairing with elliptic curve cryptography. Therefore, our scheme has good applicability to communication environments with limited bandwidth and computing capabilities.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.05a
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• pp.25-27
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• 2021

With the recent development of deep learning technology, computer vision-based AI technologies have been studied to analyze the abnormal behavior of objects in image information acquired through CCTV cameras. There are many cases where surveillance cameras are installed in dangerous areas or security areas for crime prevention and surveillance. For this reason, companies are conducting studies to determine major situations such as intrusion, roaming, falls, and assault in the surveillance camera environment. In this paper, we propose a real-time abnormal behavior analysis algorithm using object detection and tracking method.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.5
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• pp.1671-1686
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• 2022

Face manipulation tools represented by Deepfake have threatened the security of people's biological identity information. Particularly, manipulation tools with deep learning technology have brought great challenges to Deepfake detection. There are many solutions for Deepfake detection based on traditional machine learning and advanced deep learning. However, those solutions of detectors almost have problems of poor performance when evaluated on different quality datasets. In this paper, for the sake of making high-quality Deepfake datasets, we provide a preprocessing method based on the image pixel matrix feature to eliminate similar images and the residual channel attention network (RCAN) to resize the scale of images. Significantly, we also describe a Deepfake detector named Cascaded-Hop which is based on the PixelHop++ system and the successive subspace learning (SSL) model. By feeding the preprocessed datasets, Cascaded-Hop achieves a good classification result on different manipulation types and multiple quality datasets. According to the experiment on FaceForensics++ and Celeb-DF, the AUC (area under curve) results of our proposed methods are comparable to the state-of-the-art models.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.10a
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• pp.520-522
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• 2022

Lone Death is increasing as elderly population increases. Lone elderly is vulnerable in society for many reasons. This paper explores digital solution to protect solitary in society. First, sensor and AI care robot can be used to collect digital data and situation check. Second, digital device is checked regularly and visiting is expanded in digital environment. Third, digital emergency security system should be established. Fourth, user education is to be regularly carried out including complementary education.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.46 no.4
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• pp.281-293
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• 2023

This study addresses the optimal design methodology for switching between active electronically scanned array (AESA) radar operating modes to easily select the necessary information to reduce pilots' cognitive load and physical workload in situations where diverse and complex information is continuously provided. This study presents a procedure for defining a hidden Markov chain model (HMM) for modeling operating mode changes based on time series data on the operating modes of the AESA radar used by pilots while performing mission scenarios with inherent uncertainty. Furthermore, based on a transition probability matrix (TPM) of the HMM, this study presents a mathematical programming model for proposing the optimal structural design of AESA radar operating modes considering the manipulation method of a hands on throttle-and-stick (HOTAS). Fighter pilots select and activate the menu key for an AESA radar operation mode by manipulating the HOTAS's rotary and toggle controllers. Therefore, this study presents an optimization problem to propose the optimal structural design of the menu keys so that the pilot can easily change the menu keys to suit the operational environment.

• Journal of Information Processing Systems
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• v.19 no.5
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• pp.688-701
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• 2023

The conventional methods of network intrusion detection system (NIDS) cannot measure the trend of intrusiondetection targets effectively, which lead to low detection accuracy. In this study, a NIDS method which based on a deep neural network in a big-data environment is proposed. Firstly, the entire framework of the NIDS model is constructed in two stages. Feature reduction and anomaly probability output are used at the core of the two stages. Subsequently, a convolutional neural network, which encompasses a down sampling layer and a characteristic extractor consist of a convolution layer, the correlation of inputs is realized by introducing bidirectional long short-term memory. Finally, after the convolution layer, a pooling layer is added to sample the required features according to different sampling rules, which promotes the overall performance of the NIDS model. The proposed NIDS method and three other methods are compared, and it is broken down under the conditions of the two databases through simulation experiments. The results demonstrate that the proposed model is superior to the other three methods of NIDS in two databases, in terms of precision, accuracy, F1- score, and recall, which are 91.64%, 93.35%, 92.25%, and 91.87%, respectively. The proposed algorithm is significant for improving the accuracy of NIDS.

• International Journal of Advanced Culture Technology
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• v.12 no.3
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• pp.140-147
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• 2024

Oil and gas industry is a unique sector with complex activities, long supply chains and strict rules for the business. It is important to use enterprise resource planning (ERP) systems to address these challenges as it helps in simplifying operations, improving efficiency and facilitating evidence-based decision making. Nonetheless, successful integration of ERP systems in this industry involves careful planning, customization and alignment with specific business processes including regulatory requirements. Several critical factors, such as strong change management, support of top managers and training that works have been identified in the study. Amongst the hurdles are employee resistance towards the changes, data migration complications and integration with existing systems. Nonetheless, NOCL's ERP implementation resulted in significant improvements in operating efficiency, better data visibility and compliance management. It also led to a decrease in financial reporting timeframes, more accurate inventory tracking and improved decision-making capabilities. The study provides useful insights on how to optimize oil and gas sector ERP implementations; key among them is practical advice including strengthening change management strategies, prioritizing data security and collaborating with ERP vendors. The research highlights the importance of tailoring ERP solutions to specific industry needs as well as emphasizes the strategic role of ongoing monitoring/feedback for future benefits sustainability.

• Journal of the Korean housing association
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• v.18 no.3
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• pp.115-123
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• 2007

The purpose of this study was to examine how housing facilities have been progressed, how housing life has been technicalized and which factors contributed to the modernization of Korean housing in the economic development era. Review of advertising material for apartment sales in the newspaper from 1970s' to the 1990s' are mainly utilized to follow up the changes of kitchen equipment and furnitures, bathroom equipments, heating and cooking facilities and their fuel system, information and telecommunication system as well as security and intelligent system. However, high technology in apartment was a symbol of modem housing in each time. The improvement of housing facilities brought about the improvement of efficiency in household works. In other words, housing space plays as "Living Machine". And appearance of new technology systems leaded to a pluralistic activities in the home. As well as improvement on the material environments accelerated the individualization phenomena in housing space.