Chang Choi

• Ph. D
• Professor (Associate) at Gachon University

Since most real-world network data include nodes and edges that evolve gradually, an embedding model for dynamic heterogeneous networks is crucial for network analysis. Transformer models have remarkable success in natural language processing but are rarely applied to learning representations of dynamic heterogeneous networks. In this study, we pro...

Proper exploitation of artificial intelligence (AI) models is required to achieve precise and efficient healthcare. However, this is an obstacle to the possibility of exchanging medical data, as they are considered instances of personal information and subject to data protection legislation and legal requirements. Moreover, because fully automatic...

This article has been retracted. Please see the Retraction Notice for more detail: https://doi.org/10.1186/s42408-023-00220-4.

Research on multi‐biometric authentication systems using multiple biometric modalities to defend against adversarial attacks is actively being pursued. These systems authenticate users by combining two or more biometric modalities using score or feature‐level fusion. However, research on adversarial attacks and defences against each biometric modal...

Recently, in the offline distribution field, as the number of data collection and analysis cases increases by applying IoT devices to kiosks, research on hyper-personalized recommendation systems has become critical. Recommendation systems only work well in some data-rich areas (industries). Therefore, it is unsuitable for kiosk systems with multip...

Background Ultrasound imaging is the most frequently performed for the patients with chronic hepatitis or liver cirrhosis. However, ultrasound imaging is highly operator dependent and interpretation of ultrasound images is subjective, thus well-trained radiologist is required for evaluation. Automated classification of liver fibrosis could alleviat...

In recent times, there has been active research on multi-disease classification that aim to diagnose lung diseases and respiratory conditions using respiratory data. Recorded respiratory data can be used to diagnose various chronic diseases, such as asthma and pneumonia by applying different feature extraction methods. Previous studies have primari...

In the field of computer vision, active research is conducted to improve model performance. The successful application of transformer models in computer vision has led to the development of new models that incorporate this structure. However, the security vulnerabilities of these new models against adversarial attacks have not yet been thoroughly e...

Over the past decades, fire has been considered one of the most serious natural disasters because of its devastating nature, rapid spread, and high impact on the ecology, economy, environment, and life preservation. Therefore, early fire detection has immense significance in computer vision. However, existing methods suffer from high false predicti...

Single image super‐resolution (SISR) has gained significant attention in image processing and computer vision, driven by deep learning‐based models like convolutional neural networks (CNN). Yet, the resource‐intensive nature of these models poses challenges when deploying them on edge devices. To address this issue, resource‐constrained models need...

Phishing is a severe security risk that has negative impacts on both the individuals and the brands it targets. Despite the fact that this danger has been around for a while, it is still quite active and effective. In truth, attackers’ strategies have continued to evolve to make their attacks more convincing and successful. Identification of phishi...

Information and communication technology (ICT) has simplified our lives and revolutionised many facets of human existence. It has been used in several sectors and has streamlined corporate procedures by grouping, condensing, coding, and personalising them. ICT has, however, resulted in unforeseen effects, including various cybercrimes. The term “cy...

Implementing the necessary countermeasures to detect the growing and highly destructive family of malware is an urgent obligation. The proliferation and diversity of malware make these problems more challenging. For beginners, it is arduous to attain crucial features for multi‐class family classification and extract valuable information from the ob...

Timely detection of fires is crucial for saving human lives and minimizing the economic and ecological impact of such incidents. Although numerous attempts have been made to identify a fire in its early stage, significant challenges remain in achieving accurate and reliable detection. Therefore, we fine-tuned a pre-trained ConvNeXtTiny architecture...

Recently, the tourism trend has been shifting towards the Tourism 2.0 paradigm due to increased travel experiences and the increase in acquiring and sharing information through the Internet. The Tourism 2.0 paradigm requires developing intelligent tourism service tools for positive effects such as time savings and marketing utilization. Existing to...

As security is emphasized inside and outside the vehicle, research on driver identification technology using bio-signals is being actively studied. The bio-signals acquired by the behavioral characteristics of the driver include artifacts generated according to the driving environment, which could potentially degrade the accuracy of the identificat...

With the advances in deep learning, including Convolutional Neural Networks (CNN), automated diagnosis technology using medical images has received considerable attention in medical science. In particular, in the field of ultrasound imaging, CNN trains the features of organs through an amount of image data, so that an expert-level automatic diagnos...

The final version is published by Elsevier, in "Expert Systems with Applications" and available from https://doi.org/10.1016/j.eswa.2023.121323

The incidence of cancer among modern people has recently increased due to various reasons such as eating habits, smoking, and drinking. Therefore, medical image analysis for effective disease diagnosis is considered an extremely important diagnostic tool. In particular, endoscopy is used as a representative screening method for diagnosing diseases...

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In recent dentistry research, deep learning techniques have been employed for various tasks, including detecting and segmenting third molars and inferior alveolar nerves, as well as classifying their positional relationships. Prior studies using convolutional neural networks (CNNs) have successfully detected the adjacent area of the third molar and...

Recent user recognition technologies have focused on biometric signals to remotely identify users in the access management, medical welfare, and public sectors. The electrocardiogram (ECG) signal is an individual’s unique electrophysiological signal generated within the body and is difficult to forge or change; thus, it can be used to uniquely iden...

With the arrival of the 5G era, wireless communication technologies and services are rapidly exhausting the limited spectrum resources. Spectrum auctions came into being, which can effectively utilize spectrum resources. Because of the complexity of the electronic spectrum auction network environment, the security of spectrum auction can not be gua...

Plant diseases are a major cause of reduction in agricultural output, which leads to severe economic losses and unstable food supply. The citrus plant is an economically important fruit crop grown and produced worldwide. However, citrus plants are easily affected by various factors, such as climate change, pests, and diseases, resulting in reduced...

Due to the high transmission rate and high pathogenicity of the novel coronavirus (COVID-19), there is an urgent need for the diagnosis and treatment of outbreaks around the world. In order to diagnose quickly and accurately, an auxiliary diagnosis method is proposed for COVID-19 based on federated learning and blockchain, which can quickly and eff...

Due to the advent of the expressions of data other than tabular formats, the topological compositions which make samples interrelated came into prominence. Analogically, those networks can be interpreted as social connections, dataflow maps, citation influence graphs, protein bindings, etc. However, in the case of social networks, it is highly cruc...

Educators have been calling for reform for a decade. Recent technical breakthroughs have led to various improvements in the semantic web-based education system. After last year's COVID-19 outbreak, development quickened. Many countries and educational systems now concentrate on providing students with online education, which differs greatly from tr...

When building the large-scale distributed decision control system based on mobile terminal devices (MTDs), electronic voting (E-voting) is a necessary technique to settle the dispute among parties. Due to the inherent insecurity of Internet, it is difficult for E-voting to attain complete fairness and robustness. In this study, we argue that Bitcoi...

Temporal action proposal generation aims to output the starting and ending times of each potential action for long videos and often suffers from high computation cost. To address the issue, we propose a new temporal convolution network called Multipath Temporal ConvNet (MTCN). In our work, one novel high performance ring parallel architecture based...

The early diagnosis of pre-existing coronary disorders helps to control complications such as pulmonary hypertension, irregular cardiac functioning, and heart failure. Machine-based learning of heart sound is an {efficient} technology which can help minimize the workload of manual auscultation by automatically identifying irregular cardiac sounds....

The development of the industrial Internet of Things paradigm brings forth the possibility of a significant transformation within the manufacturing industry. This paradigm is based on sensing large amounts of data, so that it can be employed by intelligent control systems (i.e., artificial intelligence algorithms) eliciting optimal decisions in...

Images and videos in multimedia data are typical representation methods that include various types of information, such as color, shape, texture, pattern, and other characteristics. Besides, in video data, information such as object movement is included. Objects may move with time, and spatial features can change, which is incorporated in spatio-te...

At present, the influence of the surrounding environment on the health of humans is attracting increasing attention, and the indoor environment plays a significant role in people's health. Therefore, it is necessary to effectively monitor indoor environments in real time. With the increase of end‐devices, the rapid growth of data is exerting a pres...

A blockchain-based processing framework for sensitive data is proposed. The smart network comprises a blockchain module, an electronic contract (E-contract) layer node, and a Software-as-a-Service (SaaS) layer module. The underlying blockchain module provides technical support, such as virtual machines, consensus algorithms, transaction verificatio...

Internet of Things (IoT) is the utmost assuring framework to facilitate human life with quality and comfort. IoT has contributed significantly to numerous application areas. The stormy expansion of smart devices and their credence for data transfer using wireless mechanics boosts their susceptibility to cyber-attacks. Consequently, the rate of cybe...

In this paper, to increase the attack success rate, we analyzed the distribution of all collected keyboard data based on the distance of time and keyboard scancode data, which presents the crucial data from the previous study. To achieve this, we derived time-distance based features that have higher attack success rates than in previous studies. Th...

This paper proposes the application of three key methods to multimodal neuroimaging data fusion. The first step is to classify neurodegenerative brain diseases in the considered scans from the available neuroimaging techniques. We propose to classify scans by selecting relevant disease detection features utilizing a game-theoretic approach and evid...

Internet of Things (IoT) is the utmost assuring framework to facilitate human life with quality and comfort. IoT has contributed significantly in numerous application areas. The stormy expansion of smart devices and their credence for data transfer on wireless mechanics boosts their susceptibility to cyber-attacks. Consequently, the rate of cybercr...

With the rapid development and application of information technology, blockchain technology (BT) has become an important means to promote the integration of the real economy and the digital economy. BT reached a certain level of development for application in asset transactions, finance, and traceability. However, existing technology provides no re...

Due to the large scale of the typical deployments and the involvement of moving objects to the Internet of Things, participating nodes opportunistically establish data exchanging connections, spanning across multiple organizations and security domains. This opportunistic behavior causes the impossibility of defining valid security policies to rule...

This Special Issue aims at collecting several original state-of-the-art research experiences in the area of intelligent applications in the IoT and Sensor networks environment, by analyzing several open issues and perspectives associated with such scenarios, in order to explore novel potentialities and solutions and face with the emerging challenge...

As the request for network access and a variety of services, the Internet of Things (IoT) has evolved from special networks with simple functions to global information infrastructure, challenging the current authentication mechanism. Due to the dense population in the massive IoT scenario, the increasing connectivity requirements may aggravate the...

Research on electrocardiogram (ECG) signals has been actively undertaken to assess their value as a next generation user recognition technology, because they require no stimulation and are robust against forgery and modification. However, even within the same user, the heart rate and waveform of ECG signals will vary depending on physical activity,...

Aesthetic appeal and image quality are two important features of photographs, which play the dominant role when people clean their albums. Currently, the objective image quality assessment has been documented very well whereas the objective aesthetic appeal assessment algorithms are not developed well enough. This paper first subjectively evaluated...

Social Platforms transpired as the fascinating attack surface to explode multitude of cyber-attacks as it facilitates sharing of personal and professional information. XSS vulnerability exists approximately in 80% of the social platforms. Hence, this paper presents an approach, XSSPro, to defend social networking platforms against XSS attacks. XSSP...

The faster and regular usage of Web 2.0 technologies like Online Social Networks (OSNs) addicted to millions of users worldwide. This popularity made target for spammers and fake users to spread phishing attack, viruses, false news, pornography and unwanted advertisements like URLs, images and videos etc. The present paper proposes a behavioral ana...

In Vehicular ad-hoc network (VANET) vehicles communicate with other vehicles and with the RSU(Road Side Unit). It provides safety and other help to the drivers and the passengers of the vehicles. It is important for Intelligent Transport Systems, hence in recent years the Industrial sector and researchers give it special importance and did much res...

Localization plays an important role in the field of Wireless Sensor Networks (WSNs) and robotics. Currently, localization is a very vibrant scientific research field with many potential applications. Localization offers a variety of services for the customers, for example, in the field of WSN, its importance is unlimited, in the field of logistics...

Ship movement information is becoming increasingly available, resulting in an overwhelming increase of data transmitted to human operators. Understanding the Maritime traffic patterns is important to Maritime Situational Awareness (MSA) applications in particular, to classify and predict trajectories on sea. Therefore, there is need for automatic p...

We present moving intelligence of Mobile Edge Computing (MEC) closer to the vessel terminal devices in the maritime network. This technology proves to be a better approach for managing data resources generated by the internet of things (IoT) devices in a marine vessel. Regarding the problem of high transmission delay and low bandwidth in the conven...

Applying network function virtualization (NFV) technology to an ocean network can increase the flexibility and agility of deploying network functions and provide an easy, centralized way to manage the network, including service networks such as transport networks, data center networks, and security functions. It is also possible to allocate storage...

The articles in this special issue aim at collecting contributions focused on the application of soft computing, including the areas of fuzzy logic, neural networks, evolutionary computing, rough sets, and other similar techniques, in novel distributed and/or parallel systems, where cloud computing is one of the widely known examples, in order to b...

For a variety of cyber-attacks occurring in a power IoT-Cloud environment, conventional security intrusion incident detection and response technologies typically use pattern-and behavior-based statistical methods. However, they cannot provide fundamental solutions for a security intrusion or attacks, which are becoming more intelligent and diverse...

The smart healthcare area is expanding its application to telemedicine, mobile health, EHR/EMR/PHR, wireless medical services, and precision medicine through a combination of Internet of Things (IoT) technologies. In the IoT environment, it is difficult to actively control packets and traffic using existing network technologies because multiple dev...

Temporal action proposal generation is an important and challenging problem in computer vision. The biggest challenge for the task is generating proposals with precise temporal boundaries. To address these difficulties, we improved the algorithm based on boundary sensitive network. The popular temporal convolution network today overlooked the origi...

At present, human action recognition is a challenging and complex task in the field of computer vision. The combination of CNN and RNN is a common and effective network structure for this task. Especially, we use 3DCNN in CNN part and ConvLSTM in RNN part. We divide the video into multiple temporal segments by average and compress each segment into...

The Internet of things (IoT) that allows connectivity of network devices embedded with sensors undergoes severe data exchange interference as the unlicensed spectrum band becomes overcrowded. By applying cognitive radio (CR) capabilities to IoT, a novel cognitive radio internet of things (CR-IoT) network arises as a promising solution to tackle the...

Underwater localization is used as a key element in most applications of underwater communications. Despite Global Positioning System (GPS) receivers are usually employed in Terrestrial Wireless Sensor Networks, they cannot be exploited for underwater localization. In fact, GPS signals are highly attenuated by the water, and higher than a couple of...

Recommender Systems are increasingly playing an important role in our life, enabling users to find “what they need” within large data collections and supporting a variety of applications, from e-commerce to e-tourism. In this paper, we present a Big Data architecture supporting typical Cultural Heritage applications. On the top of querying, browsin...

Existing antivirus programs detect malicious code based on fixed signatures; therefore, they have limitations in detecting metamorphic malicious code that lacks signature information or possesses circumventing code inserted into it. Research on the methods for detecting this type of metamorphic malicious code primarily focuses on techniques that ca...

Owing to the advantages of Unmanned Aerial Vehicle (UAV), such as the extendibility, maneuverability and stability, multiple UAVs are having more and more applications in security surveillance. The object searching and trajectory planning become the important issues of uninterrupted patrol. We propose an online distributed algorithm for tracking an...

Cloud computing is a promising paradigm to provide flexible and reliable services. Nevertheless, concern and anxiety about data security and tenants’ privacy are still a major barrier for the popularity of cloud computing. Oblivious transfer (OT) is a cryptographic primitive that enables a client to selectively retrieve data in a privacy-preserving...

A secure USB memory appears to store data safely, protect the data stored inside by the security features such as user authentication, data protection, and access control. However, there is a problem that the security of the data stored inside of a USB device can not actually be preserved on all levels due to several discovered vulnerabilities such...

Due to the development of mobile transmission techniques, more exciting services can be launched that may change our daily lives in more easy and comfortable ways. The introduction of device‐to‐device (D2D) service in future 5G communication systems can extend the service coverage of intelligent medical treatment from hospitals to anywhere inside t...

With the growing number of malware, malware analysis technologies need to be advanced continuously. Malware authors use various packing techniques to hide their code from malware detection tools and techniques. The packing techniques are generally used to compress and encrypt executable code in executable files, and the unpacking code is usually em...

Security surveillance is critical to social harmony and people's peaceful life. It has a great impact on strengthening social stability and life safeguarding. Detecting anomaly timely, effectively and efficiently in video surveillance remains challenging. This paper proposes a new approach, called S <sup xmlns:mml="http://www.w3.org/1998/Math/MathM...

Successive interference cancellation (SIC) receiver is adopted by power domain non-orthogonal multiple access (NOMA) at the receiver side as the baseline receiver scheme taking the forthcoming expected mobile device evolution into account. Development technologies and advanced techniques are boldly being considered in order to achieve power saving...

Ocean observation networks have become important data acquisition platform for marine scientific research. This paper first summarizes the characteristics of the ocean observation networks, briefly introduces the development history of the world in the field of ocean observatory networks, and then gives a detailed introduction to the research progr...

Smart grid technology is the core technology for the next-generation power grid system with enhanced energy efficiency through decision-making communication between suppliers and consumers enabled by integrating the IoT into the existing grid. This open architecture allowing bilateral information exchange makes it vulnerable to various types of cyb...

The number of mobile users and the volume of big traffic data generated by user terminals are dramatically increased with diverse applications. Development in different economic and social sectors not only require higher network speed but also need low-cost on information exchanges. The market needs a complete set of solutions, which can provide a...