• Smart Media Journal
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• v.9 no.1
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• pp.60-66
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• 2020

In this paper, the FIDO (Fast IDentity Online) transaction certification platform was proposed for applying the DID (Decentralized ID) of blockchain with home shopping channels to the IPTV service providers based on the Remocon (Remote Control). In this case, the DID based smart remocon applies biometric identification techniques for personal identification. These individual DID smart remote controls apply distributed ID blockchain, enabling home shopping viewers to conduct reliable ratings surveys through the detection of channel changed information. In addition, this smart remocon utilizes the product purchased information history on home shopping channels, allowing IPTV's home shopping viewers to compare the same broadcasted production information on all channels by blockchain technique and their production characteristics. IPTV service providers can process home shopping order/authorization informations in one-stop service via a number of home shopping broadcasting companies, and DID smart remote controls for home shopping viewers with the checking results of their real-time online access to confirm the FIDO2.0 transaction certification homepage. Thus, the FIDO transaction authentication platforms of IPTV service provider(Telecommunication company) can be expected to improve the benefits of home shopping customers, and to reduce the broadcasting companies' burden of payment, too.

• Proceedings of the Korea Society of Information Technology Applications Conference
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• 2005.11a
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• pp.325-329
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• 2005

Vast amount of information is generated and shared in this active digital As the digital informatization is vividly going on now, most of documents are in digitalized forms, and this kind of information is on the increase. It is no exaggeration to say that this kind of newly created information and knowledge would affect the competitiveness and the future of our nation. In addition to that, a lot of investment is being made in information and knowledge based industries at national level and in reality, a lot of efforts are intensively made for research and development of human resources. It becomes easier in digital era to create and share the information as there are various tools that have been developed to create documents along with the internet, and as a result, the share of dual information is increasing day in and day out. At present, a lot of information that is provided online is actually being plagiarized or illegally copied. Specifically, it is very tricky to identify some plagiarism from tremendous amount of information because the original sentences can be simply restructured or replaced with similar words, which would make them look different from original sentences. This means that managing and protecting the knowledge start to be regarded as important, though it is important to create the knowledge through the investment and efforts. This dissertation tries to suggest new method and theory that would be instrumental in effectively detecting any infringement on and plagiarism of intellectual property of others. DICOM(Dynamic Incremental Comparison Method), a method which was developed by this research to detect plagiarism of document, focuses on realizing a system that can detect plagiarized documents and parts efficiently, accurately and immediately by creating positive and various detectors.

• The Journal of the Korea Contents Association
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• v.9 no.7
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• pp.159-170
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• 2009

It is very important to extract the expression data and capture a face image from a video for online-based 3D face animation. In recently, there are many researches on vision-based approach that captures the expression of an actor in a video and applies them to 3D face model. In this paper, we propose an automatic data extraction system, which extracts and traces a face and expression data from realtime video inputs. The procedures of our system consist of three steps: face detection, face feature extraction, and face tracing. In face detection, we detect skin pixels using YCbCr skin color model and verifies the face area using Haar-based classifier. We use the brightness and color information for extracting the eyes and lips data related facial expression. We extract 10 feature points from eyes and lips area considering FAP defined in MPEG-4. Then, we trace the displacement of the extracted features from continuous frames using color probabilistic distribution model. The experiments showed that our system could trace the expression data to about 8fps.

• Journal of the Korean Institute of Intelligent Systems
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• v.13 no.2
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• pp.169-174
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• 2003

The trial and success of malicious cyber attacks has been increased rapidly with spreading of Internet and the activation of a internet shopping mall and the supply of an online, or an offline internet, so it is expected to make a problem more and more. The goal of intrusion detection is to identify unauthorized use, misuse, and abuse of computer systems by both system insiders and external penetrators in real time. In fact, the general security system based on Internet couldn't cope with the attack properly, if ever. other regular systems have depended on common vaccine softwares to cope with the attack. But in this paper, we will use the positive selection and negative selection mechanism of T-cell, which is the biologically distributed autonomous system, to develop the self/nonself recognition algorithm and AIS (Artificial Immune System) that is easy to be concrete on the artificial system. For making it come true, we will apply AIS to the network environment, which is a computer security system.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.49 no.4
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• pp.9-15
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• 2012

With the rise of internet and e-commerce, this is more applicable now than ever. People rely on computer networks to provide them with news, stock prices, e-mail and online shopping. People's credit card details, medical records and other personal information are stored on computer systems. Many companies have a web presence as an essential part of their business. The research community uses computer systems to undertake research and to disseminate findings. The integrity and availability of all these systems have to be protected against a number of threats. Amateur hackers, rival corporations, terrorists and even foreign governments have the motive and capability to carry out sophisticated attacks against computer systems. Therefore, the field of information and communication security has become vitally important to the safety and economic well being of society as a whole. This paper provides an overview of IDS and IPS, their functions, detection and analysis techniques. It also presents comparison of security capability and characteristics of IDPS techniques. This will make basis of IDPS(Intrusion Detection and Protection System) technology integration for a broad-based IDPS solutions

• Journal of KIISE
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• v.44 no.7
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• pp.680-685
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• 2017

The emergence of online media and their data has enabled data-driven methods to solve challenging and complex tasks such as rumor classification problems. Recently, deep learning based models have been shown as one of the fastest and the most accurate algorithms to solve such problems. These new models, however, either rely on complete data or several days-worth of data, limiting their applicability in real time. In this study, we go beyond this limit and test the possibility of super early rumor detection via recurrent neural networks (RNNs). Our model takes in social media streams as time series input, along with basic meta-information about the rumongers including the follower count and the psycholinguistic traits of rumor content itself. Based on analyzing millions of social media posts on 498 real rumors and 494 non-rumor events, our RNN-based model detected rumors with only 30 initial posts (i.e., within a few hours of rumor circulation) with remarkable F1 score of 0.74. This finding widens the scope of new possibilities for building a fast and efficient rumor detection system.

• Journal of Information Processing Systems
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• v.11 no.4
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• pp.601-615
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• 2015

Region of interest (ROI) is the most informative part of a medical image and mostly has been used as a major part of watermark. Various shapes ROIs selection have been reported in region-based watermarking techniques. In region-based watermarking schemes an image region of non-interest (RONI) is the second important part of the image and is used mostly for watermark encapsulation. In online healthcare systems the ROI wrong selection by missing some important portions of the image to be part of ROI can create problem at the destination. This paper discusses the complete medical image availability in original at destination using the whole image as a watermark for authentication, tamper localization and lossless recovery (WITALLOR). The WITALLOR watermarking scheme ensures the complete image security without of ROI selection at the source point as compared to the other region-based watermarking techniques. The complete image is compressed using the Lempel-Ziv-Welch (LZW) lossless compression technique to get the watermark in reduced number of bits. Bits reduction occurs to a number that can be completely encapsulated into image. The watermark is randomly encapsulated at the least significant bits (LSBs) of the image without caring of the ROI and RONI to keep the image perceptual degradation negligible. After communication, the watermark is retrieved, decompressed and used for authentication of the whole image, tamper detection, localization and lossless recovery. WITALLOR scheme is capable of any number of tampers detection and recovery at any part of the image. The complete authentic image gives the opportunity to conduct an image based analysis of medical problem without restriction to a fixed ROI.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.1
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• pp.36-43
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• 2021

In this research, the accuracy of YOLO v3 algorithm in object detection during AGV (Automated Guided Vehicle) operation was investigated. First of all, AGV with 2D LiDAR and stereo camera was prepared. AGV was driven along the route scanned with SLAM (Simultaneous Localization and Mapping) using 2D LiDAR while front objects were detected through stereo camera. In order to evaluate the accuracy of YOLO v3 algorithm, recall, AP (Average Precision), and mAP (mean Average Precision) of the algorithm were measured with a degree of machine learning. Experimental results show that mAP, precision, and recall are improved by 10%, 6.8%, and 16.4%, respectively, when YOLO v3 is fitted with 4000 training dataset and 500 testing dataset which were collected through online search and is trained additionally with 1200 dataset collected from the stereo camera on AGV.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.2
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• pp.312-334
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• 2023

In large-scale computing, cloud computing plays an important role by sharing globally-distributed resources. The evolution of cloud has taken place in the development of data centers and numerous servers across the globe. But the cloud information centers incur huge operational costs, consume high electricity and emit tons of dioxides. It is possible for the cloud suppliers to leverage their resources and decrease the consumption of energy through various methods such as dynamic consolidation of Virtual Machines (VMs), by keeping idle nodes in sleep mode and mistreatment of live migration. But the performance may get affected in case of harsh consolidation of VMs. So, it is a desired trait to have associate degree energy-performance exchange without compromising the quality of service while at the same time reducing the power consumption. This research article details a number of novel algorithms that dynamically consolidate the VMs in cloud information centers. The primary objective of the study is to leverage the computing resources to its best and reduce the energy consumption way behind the Service Level Agreement (SLA)drawbacks relevant to CPU load, RAM capacity and information measure. The proposed VM consolidation Algorithm (PVMCA) is contained of four algorithms: over loaded host detection algorithm, VM selection algorithm, VM placement algorithm, and under loading host detection algorithm. PVMCA is dynamic because it uses dynamic thresholds instead of static thresholds values, which makes it suggestion for real, unpredictable workloads common in cloud data centers. Also, the Algorithms are adaptive because it inevitably adjusts its behavior based on the studies of historical data of host resource utilization for any application with diverse workload patterns. Finally, the proposed algorithm is online because the algorithms are achieved run time and make an action in response to each request. The proposed algorithms' efficiency was validated through different simulations of extensive nature. The output analysis depicts the projected algorithms scaled back the energy consumption up to some considerable level besides ensuring proper SLA. On the basis of the project algorithms, the energy consumption got reduced by 22% while there was an improvement observed in SLA up to 80% compared to other benchmark algorithms.

• Journal of Korean Society of Occupational and Environmental Hygiene
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• v.33 no.1
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• pp.34-39
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• 2023

Objectives: In this study, the safety of alcohol-based hand sanitizers (ABHSs) for quasi-drugs and cosmetics was investigated by analyzing the ethanol content, which is an active ingredient with a sterilizing effect, and methanol, which is toxic. Methods: Forty-one ABHSs were purchased at large supermarkets and online stores. Ethanol quantification was performed by gas chromatography-flame ionization detector, and methanol quantification was performed by headspace-gas chromatography-mass spectrometry. Results: The ethanol content of ABHS in quasi-drugs was 49.6-67.8%, which was suitable for standard manufacturing procedures for external disinfectants, and the ethanol content of ABHS in cosmetics was 9.1-61.3%. The methanol content of ABHS in quasi-drugs ranged from not detected(N.D.)-131.8 ppm, which was suitable for the methanol detection standard of ethanol raw materials in the Korean Pharmacopoeia. The methanol content of ABHS in cosmetics was 23.4-859.7 ppm, which was suitable for the detection limit of methanol in cosmetics. Conclusions: The ethanol and methanol content of ABHS was judged to be safe. When selecting an ABHS to be used for sterilization, it seems necessary to check the content of ethanol, an active ingredient, and use it according to its intended purpose.