• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.11
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• pp.3723-3737
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• 2022

Google Play is one of the largest Android phone app markets and it contains both free and paid apps. It provides a variety of categories for every target user who has different needs and purposes. The customer's rate every product based on their experience of apps and based on the average rating the position of an app in these arch varies. Fraudulent behaviors emerge in those apps which incorporate search rank maltreatment and malware proliferation. To distinguish the fraudulent behavior, a novel framework is structured that finds and uses follows left behind by fraudsters, to identify both malware and applications exposed to the search rank fraud method. This strategy correlates survey exercises and remarkably joins identified review relations with semantic and behavioral signals produced from Google Play application information, to distinguish dubious applications. The proposed model accomplishes 90% precision in grouping gathered informational indexes of malware, fakes, and authentic apps. It finds many fraudulent applications that right now avoid Google Bouncers recognition technology. It also helped the discovery of fake reviews using the reviewer relationship amount of reviews which are forced as positive reviews for each reviewed Google play the android app.

• Journal of Korea Multimedia Society
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• v.17 no.5
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• pp.601-612
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• 2014

As the more people use smart phones, the interest in the apps gets the higher. Studies such as App Inventor, app generation methods using templates provide app development process with app development methods by substituting programming work. However, the realm of producible apps is limited and there are a lot of set up operations and input informations. Also, there is lack of support for smart phone sensors that are in a high demand of utilization. This paper proposed an android app development method for resolving existing problems, and implemented an accompanying app development tool. When the proposed app development method derived through combination of function modules and sensor modules is used, it's possible to produce apps with minimal user inputs, and to use sensors easily. Also, because it is simple to identify overall flow of app execution, and functions addible to the app are provided for users by units of module, it is possible to develop apps quickly.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.28 no.3
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• pp.643-653
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• 2018

Xamarin is a representative cross-platform development framework that allows developers to write mobile apps in C# for multiple mobile platforms, such as Android, iOS, or Windows Phone. Using Xamarin, mobile app developers can reuse existing C# code and share significant code across multiple platforms, reducing development time and maintenance costs. Meanwhile, malware authors can also use Xamarin to spread malicious apps on more platforms, minimizing the time and cost of malicious app creation. In order to cope with this problem, it is necessary to analyze and detect malware written with Xamarin. However, little studies have been conducted on static analysis methods of the apps written in Xamarin. In this paper, we examine the structure of Android apps written with Xamarin and propose a static analysis technique for the apps. We also demonstrate how to statically reverse-engineer apps that have been transformed using code obfuscation. Because the Android apps written with Xamarin consists of Java bytecode, C# based DLL libraries, and C/C++ based native libraries, we have studied static reverse engineering techniques for these different types of code.

• Journal of Digital Convergence
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• v.12 no.7
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• pp.189-196
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• 2014

Mobile applications are significantly impacting people's smart phone using behavior and mobile industry value chain. By examining sources of data on mobile applications use, this study presents evidence about what factors would affect the amount of apps download, which may be useful to guide app designers and publishers to develop more persuasive new apps and marketing strategies. The results indicated app ranking had effect on download amount of apps in both Android app market and Apple app store, while prices of apps had no impact on the amount of download. App type, developer experience, and locality had effect on the amount of download only for paid apps in Apple app store.

• International Journal of Computer Science & Network Security
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• v.23 no.7
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• pp.202-209
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• 2023

Android malware is now on the rise, because of the rising interest in the Android operating system. Machine learning models may be used to classify unknown Android malware utilizing characteristics gathered from the dynamic and static analysis of an Android applications. Anti-virus software simply searches for the signs of the virus instance in a specific programme to detect it while scanning. Anti-virus software that competes with it keeps these in large databases and examines each file for all existing virus and malware signatures. The proposed model aims to provide a machine learning method that depend on the malware detection method for Android inability to detect malware apps and improve phone users' security and privacy. This system tracks numerous permission-based characteristics and events collected from Android apps and analyses them using a classifier model to determine whether the program is good ware or malware. This method used the machine learning techniques KNN-SVM, DBN, and GRU in which help to find the accuracy which gives the different values like KNN gives 87.20 percents accuracy, SVM gives 91.40 accuracy, Naive Bayes gives 85.10 and DBN-GRU Gives 97.90. Furthermore, in this paper, we simply employ standard machine learning techniques; but, in future work, we will attempt to improve those machine learning algorithms in order to develop a better detection algorithm.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.10
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• pp.4191-4203
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• 2015

WebView is a vital component in smartphone platforms like Android, Windows and iOS that enables smartphone applications (apps) to embed a simple yet powerful web browser inside them. WebView not only provides the same functionalities as web browser, it, more importantly, enables a rich interaction between apps and webpages loaded inside the WebView. However, the design and the features of WebView lays path to tamper the sandbox protection mechanism implemented by browsers. As a consequence, malicious attacks can be launched either against the apps or by the apps through the exploitation of WebView APIs. This paper presents a critical attack called Supplementary Event-Listener Injection (SEI) attack which adds auxiliary event listeners, for executing malicious activities, on the HTML elements in the webpage loaded by the WebView via JavaScript Injection. This paper also proposes an automated static analysis system for analyzing WebView embedded apps to classify the kind of vulnerability possessed by them and a solution for the mitigation of the attack.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.12 no.2
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• pp.111-117
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• 2012

With the rapid growth of smart phone technologies, mobile user's demands for using services provided by existing web or portal cites are highly increased. These services, however, are designed for the environment of desktop PCs or laptops in general, so it requires lots of costs for corrections and has difficulties for system protection to use in current mobile devices. In this paper, we design and implement a middleware for android-based smart phone apps to cooperate with a portal system with minimum corrections and function configuration. Our middleware system is working as an interface between an existing portal system and mobile devices to provide harmonious usage and safe system protection.

• International journal of advanced smart convergence
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• v.8 no.4
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• pp.188-193
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• 2019

This paper is about environment-based low-code and no-code execution platform and execution method that combines hybrid and native apps. In detail, this paper describes the Low-Code/No-Code execution structure that combines the advantages of hybrid and native apps. It supports the iPhone and Android phones simultaneously, supports various templates, and avoids developer-oriented development methods based on the production process of coding-free apps and the produced apps play the role of Java virtual machine (VM). The Low-Code /No-Code (LCNC) development platform is a visual integrated development environment that allows non-technical developers to drag and drop application components to develop mobile or web applications. It provides the functions to manage dependencies that are packaged into small modules such as widgets and dynamically loads when needed, to apply model-view-controller (MVC) pattern, and to handle document object model (DOM). In the Low-Code/No-Code system, the widget calls the AppOS API provided by the UCMS platform to deliver the necessary requests to AppOS. The AppOS API provides authentication/authorization, online to offline (O2O), commerce, messaging, social publishing, and vision. It includes providing the functionality of vision.

• Convergence Security Journal
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• v.12 no.1
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• pp.49-54
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• 2012

Special applications designed for smart phone, so called "Apps" are rapidly emerging as unique and effective sources of environmental monitoring tools. Using the advantages of Information and Communication Technology (ICT), this paper propose an application that provides Indoor Gas Monitoring System. In this paper, use four wireless gas sensor modules to acquire sensors data wirelessly coupled with the advantages of existing portable smart device based on Android platform to display the real-time data from the sensor modules. Additionally, this paper adapts a simple gas classification algorithm to inform in-door Gas for users real-time based.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.12 no.5
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• pp.177-183
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• 2012

Cell-phones functions have advanced so rapidly and they are now called 'smart-phones.' Typical approach to optimization the performance of a smartphone is the increasing the speed of device and acquiring more free memory. In this paper, we propose relatively simple techniques that average users can apply to their devices to optimize the performance. For performance upgrade, we proposed an over-clocking technique usually used by computer manufacturers. For memory optimization, we proposed deleting unnecessary apps and replacing with better-functioning apps. We also performed experimentation by applying these techniques to a popular Android phone model and presented the results.