• Journal of the Korea Institute of Information Security & Cryptology
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• v.22 no.6
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• pp.1243-1252
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• 2012

Due to the widespread use of smart devices, threats of direct observation attacks such as shoulder surfing and recording attacks, by which user secrets can be stolen at user interfaces, are increasing greatly. Although formal security models are necessary to evaluate the possibility of and security against those attacks, such a model does not exist. In this paper, based on the previous work in which a HCI cognitive model was firstly utilized for analyzing security, we propose STM-GOMS model as an improvement of GOMS-based model with regard to memory limitations. We then apply STM-GOMS model for analyzing usability and security of a password entry scheme commonly used in smart devices and show the scheme is vulnerable to the shoulder-surfing attack. We finally conduct user experiments to show the results that support the validity of STM-GOMS modeling and analysis.

• International Journal of Computer Science & Network Security
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• v.24 no.9
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• pp.127-134
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• 2024

The acute respiratory infection known as a coronavirus (COVID-19) may present with a wide range of clinical manifestations, ranging from no symptoms at all to severe pneumonia and even death. Expert medical systems, particularly those used in the diagnostic and monitoring phases of treatment, have the potential to provide beneficial results in the fight against COVID-19. The significance of healthcare mobile technologies, as well as the advantages they provide, are quickly growing, particularly when such applications are linked to the internet of things. This research work presents a knowledge-based smart system for the primary diagnosis of COVID-19. The system uses symptoms that manifest in the patient to make an educated guess about the severity of the COVID-19 infection. The proposed inference system can assist individuals in self-diagnosing their conditions and can also assist medical professionals in identifying the ailment. The system is designed to be user-friendly and easy to use, with the goal of increasing the speed and accuracy of COVID-19 diagnosis. With the current global pandemic, early identification of COVID-19 is essential to regulate and break the cycle of transmission of the disease. The results of this research demonstrate the feasibility and effectiveness of using a knowledge-based smart system for COVID-19 diagnosis, and the system has the potential to improve the overall response to the COVID-19 pandemic. In conclusion, these sorts of knowledge-based smart technologies have the potential to be useful in preventing the deaths caused by the COVID-19 pandemic.

• IEIE Transactions on Smart Processing and Computing
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• v.4 no.2
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• pp.115-125
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• 2015

This paper presents a Cuckoo search algorithm to secure adversaries misdirecting multi-hop routing in Mobile ad hoc networks (MANETs) using a robust Trust Predicated Routing Framework with an optimized cluster head selection. The clustering technique designed in this framework leads to efficient routing in MANETs. The heavy work load in the node causes an energy drop in cluster head, which leads to re-clustering of the group, and another cluster head is selected to avoid packet loss during data transmission. The problem in the re-clustering process is that the overall efficiency of the routing process is reduced and the processing time is increased. A Cuckoo search based optimization algorithm is proposed to solve the problem of re-clustering by selecting the secondary cluster head within the initially formed cluster group and eliminating the reclustering process. The proposed framework enables a node to select a reliable and secure route for MANET and the performance can be evaluated by comparing the simulated results with the AODV routing protocol, which shows that the performance of the proposed routing protocol are improved significantly.

• Journal of Drive and Control
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• v.19 no.4
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• pp.97-103
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• 2022

Low fertility rates and increased life expectancy further exacerbate the process of an aging society. This is also reflected in the gradual increase in the proportion of vulnerable groups in the social population. The demand for improved mobility among vulnerable groups such as the elderly or the disabled has greatly driven the growth of the electric-assisted mobility device market. However, such mobile devices generally require a certain operating capability, which limits the range of vulnerable groups who can use the device and increases the cost of learning. Therefore, autonomous driving technology needs to be introduced to make mobility easier for a wider range of vulnerable groups to meet their needs of work and leisure in different environments. This study uses mini PC Odyssey, Velodyne Lidar VLP-16, electronic device and Linux-based ROS program to realize the functions of working environment recognition, simultaneous localization, map generation and navigation of electric powered mobile devices for vulnerable groups. This autonomous driving mobility device is expected to be of great help to the vulnerable who lack the immediate response in dangerous situations.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.7
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• pp.1774-1794
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• 2024

In the field of environmental sensing, it is necessary to develop radio planning techniques for the next generation Internet of Things (IoT) networks over mixed terrains. Such techniques are needed for smart remote monitoring of utility supplies, with links situated close to but out of range of cellular networks. In this paper, a three-dimension (3-D) geometric optimization algorithm is proposed, considering the positions of edge IoT devices and antenna coupling factors. Firstly, a multi-level single linkage (MLSL) iteration method, based on geometric objectives, is derived to evaluate the data rates over ISM 915 MHz channels, utilizing optimized power-distance profiles of continuous waves. Subsequently, a federated learning (FL) data selection algorithm is designed based on the 3-D geometric positions. Finally, a measurement example is taken in a meadow biome of the Mexican Colima district, which is prone to fluvial floods. The empirical path loss model has been enhanced, demonstrating the accuracy of the proposed optimization algorithm as well as the possibility of further prediction work.

• Journal of Internet Computing and Services
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• v.15 no.3
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• pp.31-43
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• 2014

Large number of Android mobile application has been developed and deployed through the Android open market by increasing android-based smart work device users recently. But, it has been discovered security vulnerabilities on malicious applications that are developed and deployed through the open market or 3rd party market. There are issues to leak user's personal and financial information in mobile devices to external server without the user's knowledge in most of malicious application inserted Trojan Horse forms of malicious code. Therefore, in order to minimize the damage caused by malignant constantly increasing malicious application, it is required a proactive detection mechanism development. In this paper, we analyzed the existing techniques' Pros and Cons to detect a malicious application and proposed discrimination and detection result using malicious application discrimination mechanism based on Jaccard similarity after collecting events occur in real-time execution on android-mobile devices.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.5
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• pp.1339-1355
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• 2023

Localization is a hot research spot for many areas, especially in the mobile robot field. Due to the weak signal of the global positioning system (GPS), the alternative schemes in an indoor environment include wireless signal transmitting and receiving solutions, laser rangefinder to build a map followed by a re-localization stage and visual positioning methods, etc. Among all wireless signal positioning techniques, Wi-Fi is the most common one. Wi-Fi access points are installed in most indoor areas of human activities, and smart devices equipped with Wi-Fi modules can be seen everywhere. However, the localization of a mobile robot using a Wi-Fi scheme usually lacks orientation information. Besides, the distance error is large because of indoor signal interference. Another research direction that mainly refers to laser sensors is to actively detect the environment and achieve positioning. An occupancy grid map is built by using the simultaneous localization and mapping (SLAM) method when the mobile robot enters the indoor environment for the first time. When the robot enters the environment again, it can localize itself according to the known map. Nevertheless, this scheme only works effectively based on the prerequisite that those areas have salient geometrical features. If the areas have similar scanning structures, such as a long corridor or similar rooms, the traditional methods always fail. To address the weakness of the above two methods, this work proposes a coarse-to-fine paradigm and an improved localization algorithm that utilizes Wi-Fi to assist the robot localization in a geometrically similar environment. Firstly, a grid map is built by using laser SLAM. Secondly, a fingerprint database is built in the offline phase. Then, the RSSI values are achieved in the localization stage to get a coarse localization. Finally, an improved particle filter method based on the Wi-Fi signal values is proposed to realize a fine localization. Experimental results show that our approach is effective and robust for both global localization and the kidnapped robot problem. The localization success rate reaches 97.33%, while the traditional method always fails.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.18 no.1
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• pp.23-28
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• 2018

In this work, we developed a platform that can monitor status and manage events of factory workplaces by providing events and data collected from various types of multi-touch technology based sensors installed in the workplace. By using the image recognition technology, faces of the people in the factory workplace are recognized and the customized contents for each worker are provided, and security of contents is enhanced by the authenticating an individual worker through face recognition. Contents control function through gesture recognition is constructed, so that workers can easily search documents. Also, it is possible to provide contents for workers by implementing face recognition function in mobile devices. The result of this work can be used to improve workplace safety, convenience of workers, contents security and can be utilized as a base technology for future smart factory construction.

• International Journal of Internet, Broadcasting and Communication
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• v.12 no.4
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• pp.218-225
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• 2020

The purpose of this paper is to establish an IoT-based big data platform that can check the space and form analysis in various play cultures of children. Therefore, to this end, in order to understand the healthy play culture of children, we are going to build a big data platform that allows IoT and smart devices to work together to collect data. Therefore, the goal of this study is to develop a big data platform linked to IoT first in order to collect data related to observation of children's mobile movements. Using the developed big data platform, children's play culture can be checked anywhere through observation and intuitive UI design, quick information can be automatically collected and real-time feedback, data collected through repeaters can be aggregated and analyzed, and systematic database can be utilized in the form of big data.

• Proceedings of the Korean Information Science Society Conference
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• 2001.10c
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• pp.676-678
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• 2001

Jini는 분산 컴퓨팅 환경에서 네트워크 플러그 앤 워크(Network Plug and Work)를 가능하게 해주는 기로서, 실세계의 네트워크에 연결된 주변기기나 응용프로그램을 Jini 서비스로 등록하여 동적으로 작업경을 구성할 수 있는 새로운 분산 패러다임으로 자리잡고 있다. 본 논문에서는 Jini 기반의 이동 에이전트 시스템을 설계하고 구현하였다. SMART, Grasshopper, Aglets 같은 CORBA 기반의 이동 에이전트 시스템은 표준화, 동적 서비스 등록 및 에이전트의 영속성을 지원하기에 미흡하였으나, 개발된 시스템은 Jini 서비스를 이용하여 이러한 문제들을 체계적으로 해결하고자 하였다. 본 시스템은 Jini 서비스로 동작하는 이동 에이전트 시스템, 에이전트와 에이전트 시스템의 위치 보를 관리하는 위치정보 제공자, 그리고 이동 불가능한 에이전트를 임시 저장하는 이동경로관리자로 구성 된다.