• Annual Conference of KIPS
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• 2013.05a
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• pp.450-451
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• 2013

Considering the recent few years, the usage of mobile content has increased rapidly. This brings out the need for the new internet paradigm. Content-Centric Networking (CCN) caters this need as the future internet paradigm. However, so far, the issue of mobility in the network using CCN has not been considered very efficiently. In this paper, we propose clustering in the network. We apply clustered approach to CCN for catering the mobility of client node in the network. Through this approach we achieve better convergence time and control overhead in contrast to the basic CCN.

• International Journal of Internet, Broadcasting and Communication
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• v.13 no.1
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• pp.100-106
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• 2021

Over the past few decades, natural language processing research has not made much. However, the widespread use of deep learning and neural networks attracted attention for the application of neural networks in natural language processing. Sentiment analysis is one of the challenges of natural language processing. Emotions are things that a person thinks and feels. Therefore, sentiment analysis should be able to analyze the person's attitude, opinions, and inclinations in text or actual text. In the case of emotion analysis, it is a priority to simply classify two emotions: positive and negative. In this paper we propose the deep learning based sentimental analysis system according to various optimizer that is SGD, ADAM and RMSProp. Through experimental result RMSprop optimizer shows the best performance compared to others on IMDB data set. Future work is to find more best hyper parameter for sentimental analysis system.

• International Journal of Internet, Broadcasting and Communication
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• v.13 no.3
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• pp.34-41
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• 2021

Recently, a lossless non-successive interference cancellation (SIC) non-orthogonal multiple access (NOMA) implementation has been proposed. Such lossless NOMA without SIC is achieved via correlated superposition coding (SC), in comparison with conventional independent SC. However, only high-correlated SC was investigated in the lossless non-SIC NOMA implementation. Thus, this paper investigates low-correlated SC, especially a lossless interval, owing to low-correlation between signals. First, for the low-correlated SC scheme, we derive the closed-form expressions for the two roots with which the lossless interval is defined. Then, simulations demonstrate that the lossless interval of low-correlated SC NOMA is enlarged, with a degraded middle interval, compared to that of high-correlated SC NOMA. Moreover, we also show that such tendency becomes stronger as the value of the correlation coefficient varies. As a result, the proposed low-correlated SC scheme could be considered as a promising correlated SC scheme, with the enlarged lossless interval in NOMA toward the future sixth-generation (6G) ultra-reliable low-latency communications (URLLC).

• International Journal of Internet, Broadcasting and Communication
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• v.13 no.3
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• pp.42-49
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• 2021

As cyber attacks become more intelligent, there is difficulty in detecting advanced attacks in various fields such as industry, defense, and medical care. IPS (Intrusion Prevention System), etc., but the need for centralized integrated management of each security system is increasing. In this paper, we collect big data for intrusion detection and build an intrusion detection platform using deep learning and CNN (Convolutional Neural Networks). In this paper, we design an intelligent big data platform that collects data by observing and analyzing user visit logs and linking with big data. We want to collect big data for intrusion detection and build an intrusion detection platform based on CNN model. In this study, we evaluated the performance of the Intrusion Detection System (IDS) using the KDD99 dataset developed by DARPA in 1998, and the actual attack categories were tested with KDD99's DoS, U2R, and R2L using four probing methods.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.3
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• pp.1006-1027
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• 2022

In the crowdfunding market, various crowdfunding platforms can offer founders the possibilities to collect funding and launch someone's next campaign, project or events. Especially, healthcare crowdfunding is a field that is growing rapidly on health-related problems based on online platforms. One of the largest platforms, GoFundMe, has raised US$ 5 billion since 2010. Unfortunately, while providing crucial help to care for many people, it is also increasing risk of fraud. Using the largest platform of crowdfunding market, GoFundMe, we conduct an exhaustive search of detection on fraud from October 2016 to September 2019. Data sets are based on 6 main types of medical focused crowdfunding campaigns or events, such as cancer, in vitro fertilization (IVF), leukemia, health insurance, lymphoma and, surgery type. This study evaluated a detect of fraud process to identify fraud from non-fraud healthcare crowdfunding campaigns using various machine learning technics.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.3
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• pp.986-1005
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• 2022

Text steganography is one of the most imminent and promising research interests in the information security field. With the unprecedented success of the neural network and natural language processing (NLP), the last years have seen a surge of research on generative linguistic steganography (GLS). This paper provides a thorough and comprehensive review to summarize the existing key contributions, and creates a novel taxonomy for GLS according to NLP techniques and steganographic encoding algorithm, then summarizes the characteristics of generative linguistic steganographic methods properly to analyze the relationship and difference between each type of them. Meanwhile, this paper also comprehensively introduces and analyzes several evaluation metrics to evaluate the performance of GLS from diverse perspective. Finally, this paper concludes the future research work, which is more conducive to the follow-up research and innovation of researchers.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.1
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• pp.173-187
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• 2022

Recent studies have focused on self-management of hypertension using smart devices (cellular phones, tablets, watches). It has proven to be an effective tool for early detection and control of high Blood Pressure (BP) without affecting patients' daily routines. This systematic review surveys the existing self-monitoring systems, evaluate their effectiveness and compares the different approaches. We investigated the current systems in terms of various attributes, including methods used, sample size, type of investigation, inputs/ outputs, rate of success in controlling BP, group of users with higher response rate and beneficiaries, acceptability, and adherence to the system. We identified some limitations, shortcomings, and gaps in the research conducted recently studying the impact of mobile technology on managing hypertension. These shortcomings can generate future research opportunities and enable it to become more realistic and adaptive. We recommended including more observable factors and human behaviors that affect BP. Furthermore, we suggested that vital monitoring/logging and medication tuning are insufficient to improve hypertension control. There is also a need to observe and alter patient behavior and lifestyles.

• International Journal of Computer Science & Network Security
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• v.22 no.6
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• pp.163-171
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• 2022

Online services are widely spread, and their use increases day by day. As COVID-19 spread and people spent much time online, fraud scams have risen unexpectedly. Manipulation techniques have become more effective at swindling those lacking basic technological knowledge. Unfortunately, a user needs a quorum. The interest in preventing scammers from obtaining effective quality service has become the most significant obstacle, increasing the variety of daily Internet platforms. This paper is concerned with analyzing purchase data and extracting provided results. In addition, after examining relevant documents presenting research discussing them, the recommendation was made that future work avoids them; this would save a lot of effort, money, and time. This research highlights many problems a person may face in dealing with online institutions and possible solutions to the epidemic through theft operations on the Internet.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.2
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• pp.544-564
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• 2022

Underwater images often suffer from color distortion, blurring and low contrast, which is caused by the propagation of light in the underwater environment being affected by the two processes: absorption and scattering. To cope with the poor quality of underwater images, this paper proposes a multiscale fusion underwater image enhancement method based on channel attention mechanism and local binary pattern (LBP). The network consists of three modules: feature aggregation, image reconstruction and LBP enhancement. The feature aggregation module aggregates feature information at different scales of the image, and the image reconstruction module restores the output features to high-quality underwater images. The network also introduces channel attention mechanism to make the network pay more attention to the channels containing important information. The detail information is protected by real-time superposition with feature information. Experimental results demonstrate that the method in this paper produces results with correct colors and complete details, and outperforms existing methods in quantitative metrics.

• International Journal of Internet, Broadcasting and Communication
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• v.14 no.1
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• pp.170-181
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• 2022

We live in a digital age. Smartphones are used by everyone from children to the elderly. And many smart devices are pouring out and changing our daily life a lot. However, even in the development of this digital age, there are some marginalized groups. There are also those who are reluctant to expose their information in the digital age. They have difficulty making reservations on their smartphones, using payment systems, logging into the site using various authentication and verification procedures, and entering and leaving buildings. We still carry most IDs, seals, certificates, etc. in physical form. Those who use smartphones are enjoying the convenience of the times. However, among the underprivileged, the desire to pass everything with only one device is growing. In this study, the most suitable smart band model was proposed by collecting the Delphi survey and the opinions of the general public. Future research is required to improve practical usability and utility by developing cheaper and more convenient models.