• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.5
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• pp.691-700
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• 2021

The IP cameras have rapidly replaced the analog CCTVs as the cameras have the advantages of not only being able to remotely monitor, but also supplying power through the UTP cable, In this paper, we introduce the protocol architecture of the ONVIF standard which is widely applied to the IP camera and other Internet protocols to support it, and implement the ONVIF Device on a commercial board. Although these functions can be controlled by the Client (PC), several functions such as privacy masks, temperature display of the thermal camera, and ROI (Region of Interest) are implemented through a web viewer on the device. Through the experiment, the functions of ONVIF Profile S and web viewer are verified through SOAP messages exchanged between Device (IP camera) and Client program and streamed images.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.22 no.3
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• pp.553-564
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• 2012

Today's security initiatives tend to integrate the physical and information securities which have been run by completely separate departments. That is, the converged security management becomes the core in the security market trend. However, to the best of our knowledge, we cannot find any solutions how to combine these two security events for the converged security. In this paper, we propose an information security object-driven approach which utilizes the physical security events to enhance and improve the information security. For scalability, we also present a systematic method using the analytic hierarchy process finding the meaningful event combinations among the large number of physical security events. In particular, we show the whole implementation processes in detail where we consider the information security object 'illegal computing system access' combined with two physical security devices - access controller and CCTV+video analyzer system.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.1
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• pp.146-151
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• 2021

Currently, the demand for vehicles from one family is increasing in many countries at home and abroad, reducing the number of people on the vehicle and increasing the number of vehicles on the road. The multi-passenger lane system, which is available to solve the problem of traffic congestion, is being implemented. The system allows police to monitor fast-moving vehicles with their own eyes to crack down on illegal vehicles, which is less accurate and accompanied by the risk of accidents. To address these problems, applying deep learning object recognition techniques using images from road sites will solve the aforementioned problems. Therefore, in this paper, we compare and analyze the performance of existing deep learning models, select a deep learning model that can identify real-time vehicle occupants through video, and propose a vehicle occupancy detection algorithm that complements the object-ident model's problems.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.11
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• pp.1507-1518
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• 2020

High-quality images have a lot of information, so sensitive data is stored by encryption for private company, military etc. Encrypted images can only be decrypted with a secret key, but the original data cannot be retained when attacked by the Shear attack and Noise pollution attack techniques that overwrite some pixel data with arbitrary values. Important data is the more necessary a countermeasure for the recovery method against attack. In this paper, we propose a random number generator PingPong256 and a shuffling method that rearranges pixels to resist Shear attack and Noise pollution attack techniques so that image and video encryption can be performed more quickly. Next, the proposed PingPong256 was examined with SP800-22, tested for immunity to various noises, and verified whether the image to which the shuffling method was applied satisfies the Anti-shear attack and the Anti-noise pollution attack.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.11
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• pp.1321-1329
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• 2019

With the development of social information networks, the marketing methods are also changing in various ways. Unlike successful marketing methods based on existing celebrities and financial support, Influencer-based marketing is a big trend and very famous. In this paper, we first extract influencer features from more than 54 YouTube channels using the multi-dimensional qualitative analysis based on the meta information and comment data analysis of YouTube, model representative themes to maximize a personalized video satisfaction. Plus, the purpose of this study is to provide supplementary means for the successful promotion and marketing by creating and distributing videos of new items by referring to the existing Influencer features. For that we assume all comments of various videos for each channel as each document, TF-IDF (Term Frequency and Inverse Document Frequency) and LDA (Latent Dirichlet Allocation) algorithms are applied to maximize performance of the proposed scheme. Based on the performance evaluation, we proved the proposed scheme is better than other schemes.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.5
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• pp.576-583
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• 2020

This paper proposes a technique to determine the spam comments on YouTube, which have recently seen tremendous growth. On YouTube, the spammers appeared to promote their channels or videos in popular videos or leave comments unrelated to the video, as it is possible to monetize through advertising. YouTube is running and operating its own spam blocking system, but still has failed to block them properly and efficiently. Therefore, we examined related studies on YouTube spam comment screening and conducted classification experiments with six different machine learning techniques (Decision tree, Logistic regression, Bernoulli Naive Bayes, Random Forest, Support vector machine with linear kernel, Support vector machine with Gaussian kernel) and ensemble model combining these techniques in the comment data from popular music videos - Psy, Katy Perry, LMFAO, Eminem and Shakira.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.10
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• pp.1288-1293
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• 2020

As fears of infection with the Corona 19 virus increase, an untact mood is also blowing in the real estate market. Changes in life style are bringing about changes in the way of life and patterns of consumption. In the real estate marketing market, such changes are inevitable. In particular, marketing using a real estate model house has the characteristics of marketing that is closely related to the denseness that many people visit in an enclosed space. These characteristics include all three features (airtight, dense, close), characteristics mentioned in the COVID-19 prevention rules. Therefore, in this study, we will look at ways to reinforce model house customer marketing in line with the untact (non-face-to-face) trend and to avoid the above three features, characteristics in the model house customer marketing process, and show the implementation results to avoid features. Through this, we propose a safe and expandable real estate marketing strategy through the avoidance of the three features of corona 19.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.2
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• pp.234-239
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• 2021

Recently, as the installation of a large number of high-performance CCTVs for crime prevention and traffic control has increased rapidly, the problem of increasing system requirements for response to privacy infringement factors and analysis of high-definition image information transmitted from multiple cameras has been actively emerging. Accordingly, there is a need for a method for responding to privacy infringement and a method for efficiently processing surveillance images input from multiple cameras. In this paper, in order to reduce the processing cost of the input image and improve the processing speed, an integrated image is generated by grouping images input from a plurality of cameras. After analyzing the pre-generated integrated video, it detects a preset privacy event or an event that highlights interest. Depending on whether or not an event is detected, you will perform an editing operation corresponding to the event.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.3
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• pp.355-360
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• 2021

Recently Youtube has been more popular. As many studies show the comparative deprivation of the Social Medeia, this study looks into whether the comparative deprivation is expressed on the YouTube comments. It focuses on the Luxury Haul contents, videos about huge amounts of luxurious products, of which Youtubers'economic feature are demonstrative. The comments of the videos are analyzed with LDA TF-IDF and Word2Vec. Additionally, the comments were classified into positive and negative groups by the LSTM model as well. As a result of the study, even though many comments turned out positive, the negative keywords were indicated related to comparative deprivation. Also it was found that the viewers compared themselves with Youtubers. In particular, some YouTubers are more criticized if they are younger or does not seem to afford the luxurious products themselves. This study suggests that the users express the comparative deprivation on YouTube as well like on the other Social Media.

• The Journal of the Convergence on Culture Technology
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• v.7 no.3
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• pp.163-171
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• 2021

This study aimed to investigate the main characteristics of the COVID-19 vaccine-related videos spread on YouTube and differences in user responses in the infodemic situation caused by COVID-19. As a result of content analysis of 579 videos related to the COVID-19 vaccine, it was found that all of the false information was written by individual channels. Institutions, organizations, media companies, and government channels reported spread of false information as well as fact-oriented reporting. The progressive channel had a high percentage of positive sentiment in favor of vaccination, and the conservative channel had a high percentage of negative emotion against vaccination. After the vaccination started, the number of videos on government channels increased, and it was found that the number of videos with positive emotions increased. Results of regression analysis of video characteristics that affect the number of likes indicated that personal expert videos and videos from progressive channels received more likes. Combining the research results, we propose a plan to promote government policies regarding the COVID-19 vaccine using social media.