• Journal of Internet Computing and Services
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• v.14 no.6
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• pp.125-139
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• 2013

Distribution of malicious applications developed by attackers is increasing along with general normal applications due to the openness of the Android-based open market. Mechanism that allows more accurate ways to distinguish normal apps and malicious apps for common mobile devices should be developed in order to reduce the damage caused by the rampant malicious applications. This paper analysed the normal event pattern from the most highly used game apps in the Android open market to analyse the event pattern from normal apps and malicious apps of mobile devices that are based on the Android platform, and analysed the malicious event pattern from the malicious apps and the disguising malicious apps in the form of a game app among 1260 malware samples distributed by Android MalGenome Project. As described, experiment that extracts normal app and malicious app events was performed using Strace, the Linux-based system call extraction tool, targeting normal apps and malicious apps on Android-based mobile devices. Relevance analysis for each event set was performed on collected events that occurred when normal apps and malicious apps were running. This paper successfully extracted event similarity through this process of analyzing the event occurrence characteristics, pattern and distribution on each set of normal apps and malicious apps, and lastly suggested a mechanism that determines whether any given app is malicious.

• KIPS Transactions on Software and Data Engineering
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• v.4 no.4
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• pp.169-176
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• 2015

Recently smartphone market is rapidly growing and application market has also grown significantly. Mobile applications have been provided in various forms, such as education, game, SNS, weather and news. And It is distributed through a variety of distribution channels. Malicious applications deployed with malicious objectives are growing as well as applications that can be useful in everyday life well. In this study, Events from a malicious application that is provided by the normal application deployment and Android MalGenome Project through the open market were extracted and analyzed. And using the results, We create a model to determine whether the application is malicious. Finally, model was evaluated using a variety of statistical method.

• Journal of Institute of Control, Robotics and Systems
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• v.17 no.12
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• pp.1256-1265
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• 2011

Automated parking assist systems are being commercialized and rapidly spread in the market. In order to improve odometry accuracy, we proposed a practical odometry calibration scheme of Car-Like Mobile Robot (CLMR). However, there were some open problems in our prior work. For example, it was not clear whether the kinematic parameters always converged or not using the proposed calibration scheme. In addition, test driving had to be carried out "twice" without detailed explanation. This research aims to provide answers for the addressed questions though the convergence property analysis of the calibration scheme. In this paper, we evaluate on the effect of the kinematic parameter error on the odometry error at the final pose by numerical computation. The evaluation will show that the wheel diameter and tread of the CLMR can be calibrated by iterative test drives. In addition, the region of convergence in the parametric space will be discussed. Presented experimental results clearly showed that the proposed calibration scheme would be useful in practical applications.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.12 no.6
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• pp.2793-2800
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• 2011

The purpose of this research is to develop and optimize a lane departure warning application based on a smartphone which can be applicable as a new platform for various mobile information applications. Recently, a lane detection warning system which is a representative application among safe driving assistant solutions is being commercialized. Due to the necessity of powerful embedded hardware platform and its price, its market is still not growing. In this research, it is proposed to develop and optimize a lane departure warning application on iPhone 3GS. OpenCV is used for efficient image processing, and for lane detection a heuristic algorithm based on Hough Transform is proposed. The application was developed under Macintosh PC platform with Xcode 3.2.4 development tools, downloaded to the iPhone and has been tested on the real paved road. The experimental result has shown that the detection ratio of the straight lane was over 90% and the processing speed was 1.52fps. For the enhancement of the speed, a few optimization methods were introduced and the fastest speed was 3.84fps. Through the improvement of lane detection algorithm, additional optimization works and the adoption of a new powerful platform, it will be successfully commercialized on smartphone application market.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.23 no.3
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• pp.479-490
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• 2013

Recently, the number of attacks by malicious application has significantly increased, targeting Android-platform mobile terminal such as Samsung Galaxy Note and Galaxy Tab 10.1. The malicious application can be distributed to currently used mobile devices through open market masquerading as an normal application. An attacker inserts malicious code into an application, which might threaten privacy by rooting attack. Once the rooting attack is successful, malicious code can collect and steal private data stored in mobile terminal, for example, SMS messages, contacts list, and public key certificate for banking. To protect the private information from the malicious attack, malicious code detection, rooting attack detection and countermeasure method are required. To meet this end, this paper investigates rooting attack mechanism for Android-platform mobile terminal. Based on that, this paper proposes countermeasure system that enables to extract and collect events related to attacks occurring from mobile terminal, which contributes to active protection from malicious attacks.

• Journal of Internet Computing and Services
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• v.14 no.3
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• pp.35-46
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• 2013

As mobile terminal environment gets matured, the use of Android platform based mobile terminals has been growing high. Recently, the number of attacks by malicious application is also increasing as Android platform is vulnerable to private information leakage in nature. Most of these malicious applications are easily distributed to general users through open market or internet and an attacker inserts malicious code into malicious app which could be harmful tool to steal private data and banking data such as SMS, contacts list, and public key certificate to a remote server. To cope with these security threats more actively, it is necessary to develop countermeasure system that enables to detect security vulnerability existing in mobile device and take an appropriate action to protect the system against malicious attacks. In this sense, this paper aggregates diverse system events from multiple mobile devices and also implements a system to detect attacks by malicious application.

• Journal of Digital Contents Society
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• v.18 no.2
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• pp.357-363
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• 2017

The Linux operating system, considered to be a subset of the UNIX operating system, is becoming the backbone of the enterprise server market and is seen as the key to building cloud computing and big data infrastructures. Linux has a variety of Linux distributions due to the fact that the source is open and anyone can freely modify and distribute it. First of all, Linux dominated the server market, the emergence of various distributions dominates the desktop and mobile operating system markets. In this paper, we examine the birth and history of Linux and classify and characterize various Linux distributions. The emergence of various Linux distributions will play a pivotal role in the Internet of Things and will further expand their power.

• Proceedings of the KIEE Conference
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• 2006.10c
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• pp.518-520
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• 2006

Due to the rapid popularization of mobile multimedia devices and the Internet as well as the realization of high-speed data transmission and large-volume data recording media, high quality content distribution and ubiquitous information services are making progress and a new type of information distribution and network sharing service has gradually emerged into the market. It is capable of utilizing terabyte sized home servers also in private homes. Under these circumstances, in distribution of content over shared networks, it is crucial to establish DRM (Digital Rights Management) technologies to protect the content from illegal copying and usage. A truly successful DRM system must be built on open worldwide specifications and provide maximum interoperability and user acceptance. An open interoperability of DRM is able to construct highly expandable PKI based DRM, targeting usage between systems, considering the expansion of recent content distribution services and clients This document gives protocol specifications for the exchange of rights information between the DRM module, description of specifications for rights information and encrypted content formats.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2014.05a
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• pp.538-541
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• 2014

With the increased market demand for advanced specifications in smart phones, smart phones that have functions with wireless communications with high speed, cameras with high pixel and with high graphic processing ability have appeared. Furthermore, as traditional Augmented Reality technology has been practicable in mobile devices, many application's use AR technology, so AR's portability has been increased. But application with AR technology, which was implemented in smart phones has created capacity issues as applications are taking up a large portion of the memory capacity of phones. This research designed and implemented optimized AR technology by Mixare, AR open source, to solve such problems. As a result, I assured that there has been a decrease in application's memory used on the basis of mobiles.

• International Journal of Computer Science & Network Security
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• v.23 no.5
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• pp.73-88
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• 2023

Brain tumors can also be an abnormal collection or accumulation of cells in the brain that can be life-threatening due to their ability to invade and metastasize to nearby tissues. Accurate diagnosis is critical to the success of treatment planning, and resonant imaging is the primary diagnostic imaging method used to diagnose brain tumors and their extent. Deep learning methods for computer vision applications have shown significant improvements in recent years, primarily due to the undeniable fact that there is a large amount of data on the market to teach models. Therefore, improvements within the model architecture perform better approximations in the monitored configuration. Tumor classification using these deep learning techniques has made great strides by providing reliable, annotated open data sets. Reduce computational effort and learn specific spatial and temporal relationships. This white paper describes transfer models such as the MobileNet model, VGG19 model, InceptionResNetV2 model, Inception model, and DenseNet201 model. The model uses three different optimizers, Adam, SGD, and RMSprop. Finally, the pre-trained MobileNet with RMSprop optimizer is the best model in this paper, with 0.995 accuracies, 0.99 sensitivity, and 1.00 specificity, while at the same time having the lowest computational cost.