• Journal of the Korea Institute of Information Security & Cryptology
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• v.28 no.3
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• pp.617-623
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• 2018

This study focuses on detection of malicious code through AndroidManifest permissoion feature extracted based on Android static analysis. Features are built on the permissions of AndroidManifest, which can save resources and time for analysis. Malicious app detection model consisted of SVM (support vector machine), NB (Naive Bayes), Gradient Boosting Classifier (GBC) and Logistic Regression model which learned 1,500 normal apps and 500 malicious apps and 98% detection rate. In addition, malicious app family identification is implemented by multi-classifiers model using algorithm SVM, GPC (Gaussian Process Classifier) and GBC (Gradient Boosting Classifier). The learned family identification machine learning model identified 92% of malicious app families.

• International Journal of Computer Science & Network Security
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• v.21 no.6
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• pp.286-293
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• 2021

Recently, the quick development rate of apps in the Android platform has led to an accelerated increment in creating malware applications by cyber attackers. Numerous Android malware detection tools have utilized conventional signature-based approaches to detect malware apps. However, these conventional strategies can't identify the latest apps on whether applications are malware or not. Many new malware apps are periodically discovered but not all malware Apps can be accurately detected. Hence, there is a need to propose intelligent approaches that are able to detect the newly developed Android malware applications. In this study, Radial Basis Function (RBF) networks are trained using known Android applications and then used to detect the latest and new Android malware applications. Initially, the optimal permission features of Android apps are selected using Information Gain Ratio (IGR). Appropriately, the features selected by IGR are utilized to train the RBF networks in order to detect effectively the new Android malware apps. The empirical results showed that RBF achieved the best detection accuracy (97.20%) among other common machine learning techniques. Furthermore, RBF accomplished the best detection results in most of the other measures.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.13 no.1
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• pp.199-204
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• 2013

Google's android-based voice interface is limited to the web application and the users are rare. In this paper, We suggest the method that can be done using existing android-based voice engine and develope voice application. We also study the environments of android-based voice interface and present the appropriate voice interface in mobile environment.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.8
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• pp.2964-2983
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• 2015

As the Android operating system has become a key target for malware authors, Android protection has become a thriving research area. Beside the proved importance of system permissions for malware analysis, there is a lot of overlapping in permissions between malware apps and goodware apps. The exploitation of them effectively in malware detection is still an open issue. In this paper, to investigate the feasibility of neuro-fuzzy techniques to Android protection based on system permissions, we introduce a self-adaptive neuro-fuzzy inference system to classify the Android apps into malware and goodware. According to the framework introduced, the most significant permissions that characterize optimally malware apps are identified using Information Gain Ratio method and encapsulated into patterns of features. The patterns of features data is used to train and test the system using stratified cross-validation methodologies. The experiments conducted conclude that the proposed classifier can be effective in Android protection. The results also underline that the neuro-fuzzy techniques are feasible to employ in the field.

• Journal of Information Technology Services
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• v.12 no.3
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• pp.379-387
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• 2013

This paper describes a scheme of motor control for Quadcopter with Android phone instead of a dedicated controller. Basically, user's requests (channel and speed) are inquired and transferred to the Quadcopter with Android phone, then the embedded Linux system receives them and controls the motor speed of corresponding channel. We have designed and implemented an App. for user interface and the modules of device driver and timer ISR for the motor control. Finally, we have up-loaded the App. and the modules to an Android (ver.4.0) phone and ARM processor (S3C6410)-based embedded board respectively, and reviewed the functional correctness by testing the motor control of Quadcopter.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2014.10a
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• pp.606-608
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• 2014

The Study on the technique of applying the method USB redirection on Linux-based SPICE-GTK VDI solution for in (Virtual Desktop Infrastructure) VDI solution for Android-based USB redirection in this paper. VDI solutions are developed according to the development of many of the latest Android-based devices, but a VDI solution that supports USB redirection is limited. Also does not support USB redirection of Android to use the SPICE VDI solution. Therefore, the text presents the techniques applied to the Android-based VDI solutions applied to analyze the way USB redirection of SPICE-GTK VDI solution based on Linux. G PRO smartphone devices to install and use Linux-based VDI server to a test of the method applied in this paper, and the USB redirection applied VDI clients using a USB storage device, USB redirection is done playing files results you can check

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2012.05a
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• pp.327-330
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• 2012

In the rapid growth of cities, road has heavy traffic and many buildings are under constructions. These kinds of environments make more difficulty for a person who is visually handicapped to walk comfortable. To alleviate the problem, we introduce Android based Portable Navigation System to help walking for Visually Impaired Person. It follows, service center give instant real time monitoring to visually impaired person for their convenient by this system. Android based Portable Navigation System has GPS, Camera, Audio and WI-FI(wireless fidelity) available. It means that GPS location and Camera image information can be sent to service center by WI-FI network. To be specific, transmitted GPS location information enables service center to figure out the visually impaired person's whereabouts and mark the location on the map. By delivered Camera image information, service center monitors the visually impaired person's view. Also, they can offer live guidance to visually impaired person by equipped Audio with live talking. To sum up, Android based Portable Navigation System is a specialized navigation system that gives practical effect to realize more comfortable walking for visually impaired person.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.2
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• pp.959-981
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• 2017

Existing Android malware detection approaches mostly have concentrated on superficial features such as requested or used permissions, which can't reflect the essential differences between benign apps and malware. In this paper, we propose a quantitative calculation model of application risks based on the key observation that the essential differences between benign apps and malware actually lie in the way how permissions are used, or rather the way how their corresponding permission methods are used. Specifically, we employ a fine-grained analysis on Android application risks. We firstly classify application risks into five specific categories and then introduce comprehensive risk, which is computed based on the former five, to describe the overall risk of an application. Given that users' risk preference and risk-bearing ability are naturally fuzzy, we design and implement a fuzzy logic system to calculate the comprehensive risk. On the basis of the quantitative calculation model, we propose a risk classification based approach for Android malware detection. The experiments show that our approach can achieve high accuracy with a low false positive rate using the RandomForest algorithm.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.46 no.2
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• pp.58-64
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• 2009

The existing note on mobile can store only text data and cannot share the data, which means that the notes stored on mobile are just seasonal or temporary memo. Therefore, this research designs an improved note on mobile and gives a chance for sharing by importing a concept of Mindmap and backup server through the internet. The mobile application is developed based on Android Platform and the server applications are developed based on Linux. These can communicate each other throughout the internet to upload and download some mindmap data.

• Journal of Fisheries and Marine Sciences Education
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• v.23 no.4
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• pp.568-581
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• 2011

This thesis is the study about application development for management obesity and personal health matters systematically based on Android smart phone system. Growing obesity problem for students organized by the lack of a device or program to manage at home has been favored as a serious problem. Currently developed smart phones has come into wide use by portable features and many applications. And to support populations of these features smart phones will be available for obesity management in your home without any equipment using. Accordingly, this paper is the study about application development for management obesity for growing students at home based on the latest smart phone platform Android.