• 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.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.49 no.4
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• pp.31-41
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• 2012

The law enforcement agencies in the worldwide are confiscating or retaining computer systems involved in a crime/civil case, if there are any, at the preliminary investigation stage, even though the case does not involve a cyber-crime. They are collecting digital evidences from the suspects's systems and using them in the essential investigation procedure. It requires much time, though, to collect, duplicate and analyze disk images in general crime cases, especially in cases in which rapid response must be taken such as kidnapping and murder cases. The enterprise forensics, moreover, it is impossible to acquire and duplicate hard disk drives in mass storage server, database server and cloud environments. Therefore, it is efficient and effective to selectively collect only traces of the behavior of the user activities on operating systems or particular files in focus of triage investigation. On the other hand, if we acquire essential digital evidences from target computer, it is not forensically sound to collect just files. We need to use standard digital evidence container from various sources to prove integrity and probative of evidence. In this article, we describe a new digital evidence container, we called Xebeg, which is easily able to preserve collected digital evidences selectively for using general technology such as XML and PKZIP compression technology, which is satisfied with generality, integrity, unification, scalability and security.

• Proceedings of the Korea Contents Association Conference
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• 2009.05a
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• pp.45-50
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• 2009

The educational exchange through e-learning is working very well in such case as develop e-learning, development of various learning tools, cooperative practical use of e-learning contents, etc. However because there were no considerations of LMS(Learning Management System) interconnection when each systems were developed, the exchange through e-learning is starting to raise a problem. Especially the exchange through e-learning between university produced problem for a variety of reasons by absence of direct exchange in every case such as communication of students information, communication of lecture information, etc. Hence in this thesis, I will present designed model about efficient LMS interconnection through analysis case of exchange through e-learning and deduce problem. In the first place I define essential part for study such as lecture establishment data, lecture data, user data, class data, student learning tracking to interconnection data, then constituted data interconnection table used view by data interconnection prcess. By experiment result, the accessibility between students and professors was more convenience, and decreased work process by less data exchange. Henceforth there are researches in development of various essential parts for study, considered security of LMS interconnection.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.2
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• pp.751-770
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• 2019

Action recognition is an essential task in computer vision due to the variety of prospective applications, such as security surveillance, machine learning, and human-computer interaction. The availability of more video data than ever before and the lofty performance of deep convolutional neural networks also make it essential for action recognition in video. Unfortunately, limited crafted video features and the scarcity of benchmark datasets make it challenging to address the multi-person action recognition task in video data. In this work, we propose a deep convolutional neural network-based Effective Hybrid Learning (EHL) framework for two-person interaction classification in video data. Our approach exploits a pre-trained network model (the VGG16 from the University of Oxford Visual Geometry Group) and extends the Faster R-CNN (region-based convolutional neural network a state-of-the-art detector for image classification). We broaden a semi-supervised learning method combined with an active learning method to improve overall performance. Numerous types of two-person interactions exist in the real world, which makes this a challenging task. In our experiment, we consider a limited number of actions, such as hugging, fighting, linking arms, talking, and kidnapping in two environment such simple and complex. We show that our trained model with an active semi-supervised learning architecture gradually improves the performance. In a simple environment using an Intelligent Technology Laboratory (ITLab) dataset from Inha University, performance increased to 95.6% accuracy, and in a complex environment, performance reached 81% accuracy. Our method reduces data-labeling time, compared to supervised learning methods, for the ITLab dataset. We also conduct extensive experiment on Human Action Recognition benchmarks such as UT-Interaction dataset, HMDB51 dataset and obtain better performance than state-of-the-art approaches.

• Journal of the Society of Disaster Information
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• v.14 no.1
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• pp.65-71
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• 2018

In this study, it is aimed to prevent the spread of pollutants in the event of a major disaster caused by CBRNE accidents and attacks and build up system to provide optimal transport environment for each patient condition By identifying characteristics of existing products and make them immediately applicable in the field. The purpose of this study is suggesting essential consideration in both functional and performance in the development of the isolation unit. As a result of the study, it suggests (1) basic function, (2) efficient field utilization, (3) isolation unit interface and combination of modules in development of isolation unit.

• The KIPS Transactions:PartC
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• v.12C no.4 s.100
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• pp.465-472
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• 2005

IEEE 802.11 wireless LAN technology is essential for wireless internet, next generation converged network and home network. But, it is certain that user's privacy must be provided to expand the applicable area in IEEE 802.11 WLAN. Recently, WEP and 802.11i security scheme can be used in MAC Layer. But with VPN technology which is applied to WLAN user, it means that suity mechanism is used redundantly. One bit authentication mechanism was already proposed to solve this redundancy. In this paper, we analyze problems of 1-bit Authentication mechanism which are failure of synchronization and waste of packet. And we propose new algorithm which synchronizes sender with receiver, at once, using duplicated-packet-count information. We show that our algorithm improves success probability of packet authentication up to $98\%$ and efficiency of authentication bit stream up to $97\%$.

• The Journal of the Korea Contents Association
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• v.10 no.9
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• pp.57-67
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• 2010

Smart grid technology can expand energy efficiency into the home by monitoring consumer energy usage in real time and communicating with household devices that respond to demands to shut off during periods of non-use, allowing individual consumers to control their electricity usage more effectively. But, the information collected on a smart grid will form a library of personal information, the mishandling of which could be highly invasive of consumer privacy. There will be major concerns if consumer-focused principles of transparency and control are not treated as essential design principles from beginning to end. In this paper, using. All-Or-Nothing Transform encryption mode for providing smart grid security, we propose efficient distributed data Management based on XOR operation. The contribution of this paper is to provide a secure algorithm that manages efficiently distributed data in the field of private data in smart grid environment.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.2A
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• pp.79-85
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• 2006

Generally, it is essential that high-speed routers, switches, and network security appliances should have an efficient packet classification scheme in order to achieve the high-speed packet forwarding capability. For the multi-gigabit packet-processing network equipment the high-speed content search hardware such as TCAM and search engine is recently used to support the content-based packet inspection. During the packet classification process, hundreds and thousands of rules are applied to provide the network security policies regarding traffic screening, traffic monitoring, and traffic shaping. In addition, these rules could be dynamically changed during operations of systems if anomaly traffic patterns would vary. Particularly, in the high-speed network, an efficient algorithm that updates and reorganizes the packet classification rules is critical so as not to degrade the performance of the network device. In this paper, we have proposed an efficient update algorithm using a partial-ordering that can relocate the dynamically changing rules at the TCAM. Experimental results should that our algorithm does not need to relocate existing rules feature until 70$\%$ of TCAM utilization.

• Journal of KIISE
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• v.44 no.12
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• pp.1258-1268
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• 2017

Capturing real-time daily information on food prices is invaluable to help policymakers and development organizations address food security problems and improve public welfare. This study analyses the possible use of large-scale online data, available due to growing Internet connectivity in developing countries, to provide updates on food security landscape. We conduct a case study of Indonesia to develop a time-series prediction model that nowcasts daily food prices for four types of food commodities that are essential in the region: beef, chicken, onion and chilli. By using Twitter price quotes, we demonstrate the capability of social data to function as an affordable and efficient proxy for traditional offline price statistics.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.16 no.10
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• pp.2207-2216
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• 2012

Recently, wireless Internet environment with mobile phones and wireless sensor networks with severe resource restrictions have been actively studied. Moreover, an overall security issues are essential to build a reliable and secure sensor network. One of secure solution is to develop a fast cryptographic algorithm for data encryption. Therefore, we propose a 128-bit stream cipher, AA128 which has efficient implementation of software and hardware and is suitable for real-time applications such as wireless Internet environment with mobile phones, wireless sensor networks and Digital Right Management (DRM). AA128 is stream cipher which consists of 278-bit ASR and non-linear transformation. Non-linear transformation consists of Confusion Function, Nonlinear transformation(SF0 ~ SF3) and Whitening. We show that the proposed stream cipher AA128 is faster than AES and Salsa20, and it satisfies the appropriate security requirements. Our hardware simulation result indicates that the proposed cipher algorithm can satisfy the speed requirements of real-time processing applications.