• Journal of IKEEE
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• v.25 no.2
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• pp.362-370
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• 2021

In this paper, we propose the Autonomous Stair-climbing system based on data from ToF sensors and IMU in developing stair-climbing robots to passive wheelchair users. Autonomous stair-climbing system are controlled by separating the timing of landing gear operation by location and utilizing state machines. To prove the theory, we construct and experiment with standard model stairs. Through an experiment to get the Attack angle, the average error of operating landing gear was 2.19% and the average error of the Attack angle was 2.78%, and the step division and status transition of the autonomous stair-climbing system were verified. As a result, the performance of the proposed techniques will reduce constraints of transportation handicapped.

• Journal of the Korea Institute of Military Science and Technology
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• v.23 no.5
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• pp.466-474
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• 2020

Semi-active laser missile systems with high accuracy are necessary to asymmetric threats, such as UAV(Unmanned Aerial Vehicle). They are usually used to attack stationary or slow moving targets, therefore we should study on the laser designator which can detect and track fast moving targets in order to deal with UAV. In this study, design specifications are came up through performance analysis of existing laser designators, and laser designation method for fast moving target is developed. The detection and tracking performance of developed laser designator are verified through inside/outside tests on ground/aerial stationary/moving targets. Through this study, we obtain laser designator techniques that could be applied to actual semi-active laser missile systems.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.39C no.12
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• pp.1243-1249
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• 2014

The naval mine is the explosives that are installed in the water in order to attack surface ships or submarines. So mine warfare is a very important component of naval operations. In this paper, first, understanding of the general concept about mine warfare. Second, introduce the mine hunting progress and mine sweeping progress. And then, suggest the system design method of mine counter measure warfare using several functions. The functions are mine area detection algorithm for side scan sonar image using Adaboost algorithm, and calculation to mine hunting progress rate and mine sweeping progress rate. And techniques that lead the mine disposal vehicle(MDV) to mine.

• Journal of Advanced Navigation Technology
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• v.13 no.6
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• pp.884-893
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• 2009

Recently, malicious attacks for Windows operate through Window API hooking in the Windows Kernel. This paper presents the API hooking attack and protection techniques based on Windows kernel. Also this paper develops a detection tool for Windows API hooking that enables to detect dll files which are operated in the kernel. Proposed tool can detect behaviors that imports from dll files or exports to dll files such as kernel32.dll, snmpapi.dll, ntdll.dll and advapidll.dll, etc.. Test results show that the tool can check name, location, and behavior of API in testing system.

• Journal of Convergence Society for SMB
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• v.4 no.4
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• pp.31-36
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• 2014

Recent advancement in Wireless Sensor Networks (WSNs) has paved the way for WSNs to enable in various environments in monitoring temperature, motion, sound, and vibration. These applications often include the detection of sensitive information from enemy movements in hostile areas or in locations of personnel in buildings. Due to characteristics of WSNs and dealing with sensitive information, wireless sensor nodes tend to be exposed to the enemy or in a hazard area, and security is a major concern in WSNs. Because WSNs pose unique challenges, traditional security techniques used in conventional networks cannot be applied directly, many researchers have developed various security protocols to fit into WSNs. To develop countermeasures of various attacks in WSNs, descriptions and analysis of current security attacks in the network layers must be developed by using a standard notation. However, there is no research paper describing and analyzing security models in WSNs by using a standard notation such as The Unified Modeling Language (UML). Using the UML helps security developers to understand security attacks and design secure WSNs. In this research, we provide standard models for security attacks by UML Sequence Diagrams to describe and analyze possible attacks in the three network layers.

• Journal of the Society of Disaster Information
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• v.19 no.4
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• pp.924-935
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• 2023

Purpose: The central aim of this study is to leverage machine learning techniques for the classification of Intrusion Detection System (IDS) data, with a specific focus on identifying the variables responsible for enhancing overall performance. Method: First, we classified 'R2L(Remote to Local)' and 'U2R (User to Root)' attacks in the NSL-KDD dataset, which are difficult to detect due to class imbalance, using seven machine learning models, including Logistic Regression (LR) and K-Nearest Neighbor (KNN). Next, we use the SHapley Additive exPlanation (SHAP) for two classification models that showed high performance, Random Forest (RF) and Light Gradient-Boosting Machine (LGBM), to check the importance of variables that affect classification for each model. Result: In the case of RF, the 'service' variable and in the case of LGBM, the 'dst_host_srv_count' variable were confirmed to be the most important variables. These pivotal variables serve as key factors capable of enhancing performance in the context of classification for each respective model. Conclusion: In conclusion, this paper successfully identifies the optimal models, RF and LGBM, for classifying 'R2L' and 'U2R' attacks, while elucidating the crucial variables associated with each selected model.

• Journal of Internet Computing and Services
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• v.15 no.3
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• pp.79-90
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• 2014

User authentication based on ID and PW has been widely used. As the Internet has become a growing part of people' lives, input times of ID/PW have been increased for a variety of services. People have already learned enough to perform the authentication procedure and have entered ID/PW while ones are unconscious. This is referred to as the adaptive unconscious, a set of mental processes incoming information and producing judgements and behaviors without our conscious awareness and within a second. Most people have joined up for various websites with a small number of IDs/PWs, because they relied on their memory for managing IDs/PWs. Human memory decays with the passing of time and knowledges in human memory tend to interfere with each other. For that reason, there is the potential for people to enter an invalid ID/PW. Therefore, these characteristics above mentioned regarding of user authentication with ID/PW can lead to human vulnerabilities: people use a few PWs for various websites, manage IDs/PWs depending on their memory, and enter ID/PW unconsciously. Based on the vulnerability of human factors, a variety of information leakage attacks such as phishing and pharming attacks have been increasing exponentially. In the past, information leakage attacks exploited vulnerabilities of hardware, operating system, software and so on. However, most of current attacks tend to exploit the vulnerabilities of the human factors. These attacks based on the vulnerability of the human factor are called social-engineering attacks. Recently, malicious social-engineering technique such as phishing and pharming attacks is one of the biggest security problems. Phishing is an attack of attempting to obtain valuable information such as ID/PW and pharming is an attack intended to steal personal data by redirecting a website's traffic to a fraudulent copy of a legitimate website. Screens of fraudulent copies used for both phishing and pharming attacks are almost identical to those of legitimate websites, and even the pharming can include the deceptive URL address. Therefore, without the supports of prevention and detection techniques such as vaccines and reputation system, it is difficult for users to determine intuitively whether the site is the phishing and pharming sites or legitimate site. The previous researches in terms of phishing and pharming attacks have mainly studied on technical solutions. In this paper, we focus on human behaviour when users are confronted by phishing and pharming attacks without knowing them. We conducted an attack experiment in order to find out how many IDs/PWs are leaked from pharming and phishing attack. We firstly configured the experimental settings in the same condition of phishing and pharming attacks and build a phishing site for the experiment. We then recruited 64 voluntary participants and asked them to log in our experimental site. For each participant, we conducted a questionnaire survey with regard to the experiment. Through the attack experiment and survey, we observed whether their password are leaked out when logging in the experimental phishing site, and how many different passwords are leaked among the total number of passwords of each participant. Consequently, we found out that most participants unconsciously logged in the site and the ID/PW management dependent on human memory caused the leakage of multiple passwords. The user should actively utilize repudiation systems and the service provider with online site should support prevention techniques that the user can intuitively determined whether the site is phishing.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.4C
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• pp.451-457
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• 2006

A peer-to-peer(P2P) network is inherently vulnerable to malicious attacks from participating peers because of its open, flat, and autonomous nature. This paper addresses the problem of effectively defending from active attacks of malicious peers at bootstrapping phase and at online phase, respectively. We propose a secure membership handling protocol to protect the assignment of ID related things to a newly joining peer with the aid of a trusted entity in the network. The trusted entities are only consulted when new peers are joining and are otherwise uninvolved in the actions of the P2P networks. For the attacks in online phase, we present a novel message structure applied to each message transmitted on the P2P overlay. It facilitates the detection of message alteration, replay attack and a message with wrong information. Taken together, the proposed techniques deter malicious peers from cheating and encourage good peers to obey the protocol of the network. The techniques assume a basic P2P overlay network model, which is generic enough to encompass a large class of well-known P2P networks, either unstructured or not.

• Journal of Convergence for Information Technology
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• v.11 no.4
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• pp.55-63
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• 2021

Recently, the incidence rate of malicious codes is over tens of thousands of cases, and it is known that it is almost impossible to detect/respond all of them. This study proposes a method for detecting multiple behavior patterns based on a graph database as a new method for dealing with malicious codes. Traditional dynamic analysis techniques and has applied a method to design and analyze graphs of representative associations malware pattern(process, PE, registry, etc.), another new graph model. As a result of the pattern verification, it was confirmed that the behavior of the basic malicious pattern was detected and the variant attack behavior(at least 5 steps), which was difficult to analyze in the past. In addition, as a result of the performance analysis, it was confirmed that the performance was improved by about 9.84 times or more compared to the relational database for complex patterns of 5 or more steps.

• KIISE Transactions on Computing Practices
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• v.24 no.2
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• pp.99-104
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• 2018

Recently, there are increasing damages by ransomware in the world. Ransomware is a malicious software that infects computer systems and restricts user's access to them by locking the system or encrypting user's files saved in the hard drive. Victims are forced to pay the 'ransom' to recover from the damage and regain access to their personal files. Strong countermeasure is needed due to the extremely vicious way of attack with enormous damage. Malware analysis method can be divided into two approaches: static analysis and dynamic analysis. Recent malwares are usually equipped with elaborate packing techniques which are main obstacles for static analysis of malware. Therefore, this paper suggests a dynamic analysis method to monitor activities of ransomware. The proposed method can analyze ransomwares more accurately. The suggested method is comprised of extracting signatures of benign program, malware, and ransomware, and selecting the most appropriate signatures for ransomware detection.