Dong-Seong Kim

Kumoh National Institute of Technology · School of Electronic Engineering

The industrial internet of things (IIoT) and supervisory control and data acquisition (SCADA) have experienced ubiquitous growth recently. This growth comes with the challenge of an increased number of unusual attacks constituting threats. The existence and effect of intruders and their innovative attack techniques are rising. Although the existing...

Falsification detection is a critical advance in ensuring that real-time information about vehicles and their movement states is certified on the Internet of Vehicles (IoV). Thus, detecting nodes that are propagating inaccurate information is a requirement for the successful deployment of IoV services although only a few research studies have been...

Fog computing systems have been widely integrated in IoT-based applications to improve quality of services (QoS) such as low response service delays. This improvement is enabled by task offloading schemes, which perform task computation near the task generation sources (i.e., IoT devices) on behalf of remote cloud servers. However, reducing delay r...

The development of the intelligent transport space (ITS) comes with the challenge of securing transportation data. As the vehicular network is highly dynamic, the network architecture is susceptible to distributed malicious attacks irrespective of the emergence and integration of enabling technologies. A Software Defined Network (SDN) based VANET i...

The increasing variability of ciphered network communication has elevated the difficulty and complexity of network management. Finding the best optimal solution for identifying and categorizing network traffic requires a methodical approach. To predict heterogeneous ciphered network traffic, this study presented a Tree Bayesian Optimization (TBO) t...

Detection of nodes disseminating false data is a prerequisite for effective deployment of Internet of Vehicles (IoV) services. This work proposed a novel hyper-tuned ensemble Random Forest (Ens. RF) algorithm to detect false basic safety messages in IoV. Performance evaluation done using the Vehicular Reference Misbehavior (VeReMi) dataset comprisi...

To ensure that batteries that power electric vehicles are used to their full capacity, it is critical that the state of charge (SoC) is monitored in real-time. However, due to the computation-intensive nature of long short-term memory (LSTM) models, it is difficult to achieve real-time state of charge (SoC) estimation at the edge. This paper addres...

Fog computing networks have been widely integrated in IoT-based systems to improve the quality of services (QoS) such as low response service delay through efficient offloading algorithms. However, designing an efficient offloading solution is still facing many challenges including the complicated heterogeneity of fog computing devices and complex...

Priority-based logistics and the polarization of drones in civil aviation will cause an extraordinary disturbance in the ecosystem of future airborne intelligent transportation networks. A dynamic invention needs dynamic sophistication for sustainability and security to prevent abusive use. Trustworthy and dependable designs can provide accurate ri...

The pervasiveness in the industrial internet of things (IIoT) due to the application of supervisory control and data acquisition (SCADA) has led to the growth of heterogeneous sensor data, thereby increasing the risk of intrusions and attacks. The existence and effect of intruders and their innovative attack techniques are on the rise. Existing int...

The potential for an intelligent transportation system (ITS) has been made possible by the growth of the Internet of things (IoT) and artificial intelligence (AI), resulting in the integration of IoT and ITS-known as the Internet of vehicles (IoV). To achieve the goal of automatic driving and efficient mobility, IoV is now combined with modern comm...

The Metaverse is a concept used to refer to a virtual world that exists in parallel to the physical world. It has grown from a conceptual level to having real applications in virtual reality games. The applicability of the Metaverse in numerous sectors like marketing, education, social, and even advertising exists. However, there exists little or n...

Along with the massive growth of the Internet from the 1990s until now, various innovative technologies have been created to bring users breathtaking experiences with more virtual interactions in cyberspace. Many virtual environments have been developed with immersive experience and digital transformation, but most are incoherent instead of being i...

Preventive measures to stop copyright infringement are yet to be implemented on current decentralized music-sharing platforms. There is no mechanism to reject modified audio before they go online, so some decentralized music platforms become places full of pirated audio files. To address this problem, a perceptual hash-based audio detection method...

Three-dimensional printing, often known as additive manufacturing (AM), is a groundbreaking technique that enables rapid prototyping. Monitoring AM delivers benefits, as monitoring print quality can prevent waste and excess material costs. Machine learning is often applied to automating fault detection processes, especially in AM. This paper explor...

This study proposes secure federated learning (FL)-based architecture for the industrial internet of things (IIoT) with a novel client selection mechanism to enhance the learning performance. In order to secure the FL architecture and ensure that available clients are trustworthy, a certificate authority (CA) is adopted. In traditional FL, an aggre...

The deployment of unmanned aerial vehicles (UAV) for logistics and other civil purposes is consistently disrupting airspace security. Consequently, there is a scarcity of datasets for the development of real-time systems that can checkmate the incessant deployment of UAVs in carrying out nefarious activities. This succinct work fills this void by p...

The significant proliferation of the Internet of drone (IoD) network due to its enormous benefits in adverse terrains has become crucial in military operations, especially for swift aerial maneuvering and combat scenarios. However, military-based IoD networks are highly susceptible to lethal attacks as a result of severed network configuration. To...

This study proposed a hierarchical and optimized random forest (RF) anomaly-based IDS for the military internet of drones network based on the randomized search cross-validation (RSCV) technique. The simulation results show the superiority of the proposed model achieving the highest F1-score of 96.38error of 0.13, and adequate training time of 749m...

This study explores various AI models for RF-based drone detection and surveillance. Both quality and quantitative analyses of extant literature are carried out. The preliminary review results hint that Deep Learning (DL) approaches provides greater detection accuracy than other AI models. The consistent reinvention of the current enabling technolo...

Due to the increased threats these devices offer, the development of radars for detecting miniature drones has become of the greatest priority. This is due to their demonstrated ability in automotive and military applications, as well as in low-light, noisy, blurry, or misty settings. This paper will present the advantages of using radar technology...

The security and integrity of an intelligent system are a function of the reliability of its data legitimacy, its appropriation , and its authorization in end-to-end communication between the participating nodes in its network. This work examines the extent artificial intelligence (AI) models have faired in promoting AI trust in intelligent autonom...

Security threats in the aviation sector and across countries' borders are culpable by chemical explosives and improvised explosive devices (IED). Remotely detecting traces of these chemicals limits the statistics of explosions worldwide. To proffer a security solution, this paper proposed the use of a laser-radar-equipped drone with an embedded dee...

Protecting the industrial internet of things (IIoT) devices through vulnerability detection is critical as the consequences of attacks can be devastating. Machine learning (ML) has assisted several works in this regard, improving vulnerability detection accuracy. Based on established vulnerability assessment, development and performance comparison...

This article presents a novel reconfigurable physical resource block (PRB), where long-term evolution (LTE) and mobile cell-edge terminals are interfaced using low-power tunable second-order $G_{m}-C$ filter beamforming circuit, hence achieving an uplink–downlink (UL-DL) cellular system. A total of ten wireless multipoint (MP) terminals were stru...

Since the metaverse is like a virtual representation of the real world, bullying is bound to occur in many different ways. One such way is in the use of hate speech and offensive words. As a result, there is a need to detect, recognize, and censor these words. Motivated by this, we created a system that uses convolutional neural networks (CNN) to d...

In this work QR Codes are embedded in vehicle license plate to detect its information real-time, The objective of this work is to detect QRcodes in license plates, which can serve as a more secure replacement to the regular license plates. The experiment successfully detected 100 customized QRcode license plates, using the OpenCV Python-based libra...

The adoption of electric vehicles is affected by the use of batteries which need to be constantly monitored and controlled. The creation of battery digital twins can help make battery management more effective. In this paper, three deep neural networks were used to develop digital twins of a battery. The digital twin models were developed using bat...

The synchronization of swarms of drones (also known as unmanned aerial vehicles (UAV)) in a network can be attributed to their high mobility and maneuverability capabilities, making them deployable for time-critical operations such as security surveillance, disaster management, and search and rescue operations. However, the resource constraints of...

Internet of Things (IoT) devices generate massive amounts of data continuously, making it difficult to combine this data at the edge node or central edge server for AI techniques to be applied, especially on low bandwidth networks. Traditional computation offloading involves extensive resource management, queuing, and high bandwidth usage to send d...

The constant development and deployment of the supervisory control and data acquisition (SCADA) in the industrial internet of things (IIoT) have enabled vast communication leading to the generation of large volumes of sensor data. This phenomenon has increased SCADA's susceptibility to vulnerability and attacks which calls for attack detection mech...

Many modern roboticists, particularly those who model themselves after the octopus, draw inspiration from biology to construct unique robotic structures. This research expands this trend by using a biomimetic technique to create soft robots that imitate the complicated motion patterns of octopus tentacles. This method of propulsion is studied using...

Unclean water for drinking is unavailable to many people. By enabling automatic water quality measurement, this problem can be mitigated. In recent years, edge computing has gained popularity for remote monitoring. In order to track the water quality in rivers and household tanks in response to this trend, we developed an edge computing support sys...

Achieving communication intelligence with a low computational cost is necessary for wireless sensor networks for the drone transportation system. This work proposed a novel localization system with low computational and time efficiency that uses an unmanned aerial vehicle (UAV) as an anchor node and lightweight neural networks to evaluate the UAV p...

Energy consumption prediction and planning in Smart factories are vital for an optimistic smart grid. Adequate and efficient prediction of required energy in the smart factory is essential for decision-making. This study focuses on a time-efficient energy consumption prediction in a typical smart factory. The study presented a convolutional neural...

To meet the safety requirements of pedestrians and other vehicles in smart parking systems, vehicles rely heavily on visual data to classify and detect target objects. In real-time, deep learning (DL)-based algorithms have shown excellent results in object detection. While several studies have thoroughly investigated various DL-based object detecti...

The metaverse is a virtual world that is based on numerous technologies. One of such technologies is the wireless communication system. Specifically, 5G wireless communication will have a role to play in the development of the metaverse. Since the metaverse has features that require certain service requirements, it is necessary to analyze the speci...

The reliability and security of information within and between connected vehicles is now a burning research issue. Connected vehicle security is of utmost importance to military, civil, and civil-military operations. In addition, the vehicular network is a mission-critical system, placing the demand for real-time and accurate detection on machine l...

Web 3.0 has occasioned an increase in research interest in the metaverse. The research interest in the metaverse gained attention during the pandemic with the increased use of online (virtual) platforms for day-to-day activities and work. Museums and exhibition centers were affected during the pandemic. Using online (virtual) media for museums and...

Shodan Eye scanning technology has proven to be very helpful for network administrators and security personnel to scan, detect and analyze vulnerable ports and traffic in organizations' networks. This work presents a simulated network scanning activity and manual vulnerability analysis of an internet-connected industrial equipment of two chosen ind...

The accelerating heterogeneity of encoded network traffic has increased complexity and difficulty in network administration. An efficient approach is vital to find the maximum objective function to detect and classify network traffic effectively. This study proposed an ensemble optimization (EO) approach to classify diverse encrypted network traffi...

The need for a cyber-edge and cognitive artificial intelligence (AI)-based security strategy to boost autonomous underwater navigation and prevent heterogeneous attacks from pirates is imperative in maritime operations. This paper proposes a split of super-resolution (SR) to reconstruct the channel state information (CSI) through self-supervised le...

Information and communication technology (ICT) is continually expanding and converging in various industries, particularly in the maritime industry, and this trend will strengthen Maritime supervisory and data acquisition (SCADA) security. However, these application areas have the challenge of mitigating attacks. The Maritime SCADA systems are crit...

A presentation on FED-MARINE: A Federated learning framework for DDoS detection and mitigation in Maritime-SCADA network

This work reviewed the potential and need for Metaverse, Digital twin, and the enhancement of maritime communication infrastructure in the Nigerian maritime sector. The preliminary review results reveal the need for a more robust digital twin platform for real-time marine communication fault detection and evaluation. Similarly, Metaverse promises a...

As unmanned aerial vehicles (UAVs) are progressively deployed for logistics purposes, there is need for paradigm shift from mere drone detection to proactive identification of the conveyed objects and proper risk assessment from a far distance. This paper proposed a timely, efficient, accurate, and situation-aware (TEAS) mission critical operation...

Internet of Things (IoT) networks are key to the realization of modern industries and societies. A key application of IoT is in smart-grid communications. Smart-grid networks are resource-constrained in terms of computing power and energy capacity. Similarly, the wireless links between devices are typically associated with high packet loss rates, l...

Chemical asphyxiation at petrochemical factories can provoke the unconsciousness or death of factory workers through suffocation. Some chemicals vaporize and mix with air without showing any warning properties that raise the risk of oxygen deficiency. In light of this, Industry 5.0 focuses more on human‐centricity than technology‐driven implementat...

Parked vehicle-assisted multi-access edge computing (PVMEC) is a paradigm that exploits the under-utilized resources of parked vehicles (PVs) to assist MEC servers for offloaded task execution. This article investigates a partial offloading strategy for multi-user PVMEC, where each mobile device (MD)’s task can be partially offloaded to the MEC ser...