Android Emulator Research Articles

Advanced Fraud Threats And Detection In Browser, Android, And Ios Environments

As digital technologies evolve, so do the methods employed by cybercriminals to exploit vulnerabilities within browser and mobile environments. This paper explores advanced fraud threats such as VPN detection evasion, browser spoofing, mobile device factory resets, jailbroken phones, user-initiated app cloning, and Android emulators and tampering. We discuss how these threats are misused and outline advanced detection techniques to mitigate risks. The paper emphasizes the importance of implementing robust security measures to protect against sophisticated fraud tactics in browser, Android, and iOS platforms.

Advanced Fraud Threats And Detection In Browser, Android, And Ios Environments

As digital technologies evolve, so do the methods employed by cybercriminals to exploit vulnerabilities within browser and mobile environments. This paper explores advanced fraud threats such as VPN detection evasion, browser spoofing, mobile device factory resets, jailbroken phones, user-initiated app cloning, and Android emulators and tampering. We discuss how these threats are misused and outline advanced detection techniques to mitigate risks. The paper emphasizes the importance of implementing robust security measures to protect against sophisticated fraud tactics in browser, Android, and iOS platforms.

Leveraging Social Engineering Techniques for Ethical Purposes: An Approach to Develop Fake Android App for Collecting Valuable Data Discreetly

Social engineering techniques are often viewed negatively due to their association with deceptive practices. However, these techniques can also be utilized ethically, as many cybersecurity professionals do, particularly when evaluating vulnerabilities and testing security defenses. This paper presents EDC (Ethical Data Collector), an Android application that utilizes social engineering techniques to discreetly collect valuable data from an Android device for ethical purposes. EDC employs deception through a simulated UI (fake) to engage the target for a period, while secretly collecting data such as device information, active phone number, and images in the background, then sending them to a designated server via the internet. The researcher argues that EDC could help identify inexperienced cybercriminals or extortionists without complex efforts or significant cost, provided that its capabilities are judiciously utilized and subject to proper controls and oversight. EDC's development methodology emphasizes understanding the target's personality, predilections, and preferences to tailor the app experience as required for attracting the target to install and run the application. The paper describes the core functions and workflows for collecting and sending data. Additionally, permissions handling has been addressed as being critical for enabling EDC to collect the required information. Testing on Android emulators demonstrated that the EDC's APK file size is 4 MB, and data collection and transmission processes functioned as intended across various Android versions. The minimum SDK version required to run EDC is level 16. The total estimated time to complete the fake UI process (cumulative user engagement time) is 57-60 seconds, where each activity takes 8 seconds based on the adopted development approach.

Advanced Fraud Threats and Detection in Browser, Android, and iOS Environments

As digital technologies evolve, so do the methods employed by cybercriminals to exploit vulnerabilities within browser and mobile environments. This paper explores advanced fraud threats such as VPN detection evasion, browser spoofing, mobile device factory resets, jailbroken phones, user-initiated app cloning, and Android emulators and tampering. We discuss how these threats are misused and outline advanced detection techniques to mitigate risks. The paper emphasizes the importance of implementing robust security measures to protect against sophisticated fraud tactics in browser, Android, and iOS platforms.

Application of Android-based Learning Media Applications for Primary Education

Today's learning media has improved considerably than ever before and English at this time is a very important need because English has become an International language. As a means of supporting these activities, cellular phones (cellphones) can be used where currently there are many people from various circles who own and use them. For this reason, researchers created an English learning media application for children based on multimedia and smartphones that is expected to support learning activities and be easy for children to understand. This application contains basic English materials, such as introduction to alphabets, families, numbers and others. This application is equipped with animated images and how to pronounce them in English as well as practice questions for learning the material. By using the Android platform, with this application, it is hoped that children can better understand material about English. The creation of this android-based English learning application uses Adobe Flash CS5 and Adobe Photoshop CS5 software to design application designs. The software used in the creation of this application is Android-SDK (Software Development Kit), JDK (Java Development Kit) installation package, Eclipse Indigo and this application is tested on Android emulators and some android smartphones.

Application of Android-based Learning Media Applications for Primary Education

Today's learning media has improved considerably than ever before and English at this time is a very important need because English has become an International language. As a means of supporting these activities, cellular phones (cellphones) can be used where currently there are many people from various circles who own and use them. For this reason, researchers created an English learning media application for children based on multimedia and smartphones that is expected to support learning activities and be easy for children to understand. This application contains basic English materials, such as introduction to alphabets, families, numbers and others. This application is equipped with animated images and how to pronounce them in English as well as practice questions for learning the material. By using the Android platform, with this application, it is hoped that children can better understand material about English. The creation of this android-based English learning application uses Adobe Flash CS5 and Adobe Photoshop CS5 software to design application designs. The software used in the creation of this application is Android-SDK (Software Development Kit), JDK (Java Development Kit) installation package, Eclipse Indigo and this application is tested on Android emulators and some android smartphones.

Weather-Based Arthritis Tracking: A Mobile Mechanism for Preventive Strategies

Arthritis is a common joint disorder characterised by symptoms such as swelling, pain, stiffness, and limited joint movement. It primarily affects older individuals, women, and athletes. The advent of information technology has created opportunities for patients to manage their health conditions more effectively. Research indicates that weather can affect arthritis symptoms, with many patients experiencing severe discomfort during rainy weather due to the expansion of already inflamed tissues. However, there is currently no mobile application mechanism available that combines weather forecasting with health recommendations for arthritis patients, which means that patients may not have access to important information that could help them manage their symptoms. Furthermore, few research workflows have focused on weather conditions in online arthritis treatment systems. This research aims to develop a weather-based mobile system for arthritis tracking that provides health advice and alerts based on current and forecast weather conditions, as well as features to help patients track how weather affects their arthritis. This system utilises several tools for its development. The Flutter Framework is used for creating mobile apps, while Firebase is chosen as the cloud-hosted database. Visual Studio Code and Android Studio are utilised as the code editor and Android emulator, respectively. Information about weather forecasts is retrieved via the OpenWeather API. The application mechanism will feature a user-friendly interface to help users stay updated on weather forecasts, and it will collect data in a reliable and user-centric manner for generating robust evidence on health outcomes.

Trinity: High-Performance and Reliable Mobile Emulation through Graphics Projection

Mobile emulation, which creates full-fledged software mobile devices on a physical PC/server, is pivotal to the mobile ecosystem. Unfortunately, existing mobile emulators perform poorly on graphics-intensive apps in terms of efficiency and compatibility. To address this, we introduce graphics projection , a novel graphics virtualization mechanism that adds a small-size projection space inside the guest memory, which processes graphics operations involving control contexts and resource handles without host interactions. While enhancing performance, the decoupled and asynchronous guest/host control flows introduced by graphics projection can significantly complicate emulators’ reliability issue diagnosis when faced with a variety of uncommon or non-standard app behaviors in the wild, hindering practical deployment in production. To overcome this drawback, we develop an automatic reliability issue analysis pipeline that distills the critical code paths across the guest and host control flows by runtime quarantine and state introspection. The resulting new Android emulator, dubbed Trinity, exhibits an average of 97% native hardware performance and 99.3% reliable app support, in some cases outperforming other emulators by more than an order of magnitude. It has been deployed in Huawei DevEco Studio, a major Android IDE with millions of developers.

Digital forensic analysis of the private mode of browsers on Android

The smartphone has become an essential electronic device in our daily lives. We carry our most precious and important data on it, from family videos of the last few years to credit card information so that we can pay with our phones. In addition, in recent years, mobile devices have become the preferred device for surfing the web, already representing more than 50% of Internet traffic. As one of the devices we spend the most time with throughout the day, it is not surprising that we are increasingly demanding a higher level of privacy. One of the measures introduced to help us protect our data by isolating certain activities on the Internet is the private mode integrated in most modern browsers. Of course, this feature is not new, and has been available on desktop platforms for more than a decade. Reviewing the literature, one can find several studies that test the correct functioning of the private mode on the desktop. However, the number of studies conducted on mobile devices is incredibly small. And not only is it small, but also most of them perform the tests using various emulators or virtual machines running obsolete versions of Android. Therefore, in this paper we apply the methodology we presented in a previous work to Google Chrome, Brave, Mozilla Firefox, and Tor Browser running on a tablet with Android 13 and on two virtual devices created with Android Emulator. The results confirm that these browsers do not store information about the browsing performed in private mode in the file system. However, the analysis of the volatile memory made it possible to recover the username and password used to log in to a website or the keywords typed in a search engine, even after the devices had been rebooted.

Auto-Scoring Feature Based on Sentence Transformer Similarity Check with Korean Sentences Spoken by Foreigners

This paper contains the development of a training service for foreigners to help them increase their ability to speak Korean. The service developed in this paper is implemented in the form of a mobile application that shows specific Korean sentences to the user for them to record themselves speaking the sentence. The objective is to generate the score automatically based on how similar the recorded voice with the actual sentence using Speech-To-Text (STT) engines and Sentence Transformers. The application is developed by selecting the four most commonly known STT engines with similar features, which are Google API, Microsoft Azure, Naver Clova, and IBM Watson, which are put into a Rest API along with the Sentence Transformer. The mobile application will record the user’s voice and send it to the Rest API. The STT engines will transcribe the file into a text and then feed it into a Sentence Transformer to generate the score based on their similarity. After measuring the response time and consistency as the performance evaluation by simulating a scenario using an Android emulator, Microsoft Azure with 1.13 s is found to be the fastest STT engine and Naver Clova is found to be the least consistent engine with nine different transcribe results.

Penerapan Metode VIKOR (Visekriterijumsko Kompromisno Rangiranje) dalam Pengambilan Keputusan Pemilihan Emulator Android pada Komputer

This research is a research on a decision support system in choosing the best android emulator to use on a computer as a topic of discussion. The Android emulator is a software that supports computers, both laptops and other computer devices, to be able to continue to access Android in computer use by simulating Android to a computer device. In choosing an android emulator, problems often arise to use which emulator is the best and in accordance with the specifications of the computer you have, so for this conditioning, emulator experiments must be carried out one by one in an effort to ensure which emulator is of the highest quality and in simulating android on. Decision Support System can be a good approach in selecting an android emulator, with several criteria in determining the best android emulator, the VIKOR method is used because it has a multi-criteria basic concept. The VIKOR method is an approach in ranking alternatives to get the ideal and best solution with the criteria that have been owned and determined. In testing by managing data, it was found that the genymotion emulator had a final result of 0 and became the best emulator. By applying the VIKOR method, android users or emulator seekers, namely the community of game lovers or gamers, and android lovers will help to determine the ideal android emulator according to the specifications and the best emulator quality.

Using the Stay Strong App for the Well-being of Indigenous Australian Prisoners: Feasibility Study.

BackgroundThe gap between mental health needs and resources for Aboriginal and Torres Strait Islander people, the Indigenous people of Australia, is most marked in the prison population. Indigenous people are overrepresented in Australian prisons. In prison, this group experiences mental disorders to a greater degree than non-Indigenous prisoners. This group has also been found to experience mental disorder at a higher rate than Indigenous people in the community. In addition to pre-existing determinants of poor mental health, these high prevalence rates may reflect poor engagement in mainstream interventions or the efficacy of available interventions. In community populations, the use of digital mental health resources may help to increase access to well-being support. However, culturally appropriate digital tools have not been available to Indigenous people in prisons. The absence of feasibility and efficacy studies of these tools needs to be addressed.ObjectiveThe aim of this study is to determine the feasibility of the Stay Strong app as a digital well-being and mental health tool for use by Indigenous people in prison.MethodsDual government agency (health and corrective services) precondition requirements of implementation were identified and resolved. This was essential given that the Stay Strong app was to be delivered by an external health agency to Indigenous prisoners. Then, acceptability at a practice level was tested using postuse qualitative interviews with clients and practitioners of the Indigenous Mental Health Intervention Program. All Indigenous Mental Health Intervention Program practitioners (10/37, 27%) and client participants who had completed their second follow-up (review of the Stay Strong app; 27/37, 73%) during the study period were invited to participate.ResultsOwing to the innovative nature of this project, identifying and resolving the precondition requirements of implementation was challenging but provided support for the implementation of the app in practice. Acceptability of the app by clients and practitioners at a practice level was demonstrated, with nine themes emerging across the interviews: satisfaction with the current Stay Strong app, supported client goal setting, increased client self-insight, improved client empowerment, cultural appropriateness, enhanced engagement, ease of use, problems with using an Android emulator, and recommendations to improve personalization.ConclusionsThe Stay Strong Custody Project is a pioneering example of digital mental health tools being implemented within Australian prisons. Using the app within high-security prison settings was found to be feasible at both strategic and practice levels. Feedback from both clients and practitioners supported the use of the app as a culturally safe digital mental health and well-being tool for Aboriginal and Torres Strait Islander people in prison.

Neural architecture search for real-time quality assessment of wearable multi-lead ECG on mobile devices

Users need to pay for the medical services of the wearable ECG signals. The complicated interferences of wearable ECG may cause invalid medical diagnosis. To save medical expenses and reduce the workload of cardiologists, unacceptable wearable ECG should be filtered out on mobile devices in real time. Therefore, a robust and lightweight quality assessment model is essential. Existing convolutional neural network models are more robust than hand-crafted features based models, but most are too cumbersome to run on mobile devices. In this study, we utilize neural architecture search algorithm to search a network with a few parameters and low latency automatically for real-time quality assessment of wearable ECG data. To reach this goal, we construct a searching space with lightweight network blocks and add the hardware latency loss. We also propose a novel and effective strategy, any-lead, to assess the quality of all leads using a single model. We evaluated our method on a large-scale (10,709 signals) wearable 12-lead ECG dataset and a public dataset named Physionet Cinc Challenge 2011. The parameters and FLOPs of the architecture we searched were about 66.76 K and 36.44 M. Our model achieved excellent performance on the aforementioned datasets, with AUC of 98.32% and 97.64%, F1 scores of 94.36% and 93.52%, MCC of 84.74% and 83.22%, respectively, and with the inference time on an Android emulator of about 78 ms. Extensive experimental results demonstrate the effectiveness of our method in assessing the quality of all leads of wearable ECG data on mobile devices in real time.

Sistem Informasi Penjualan Motor Bekas Berbasis Android Untuk Meningkatkan Penjualan di Mokascirebon.Com

Mokascirebon.com is a trusted showroom in Cirebon for buying and selling second hand motorcycle, where in the business of buying and selling second hand motorcycle, it requires a large amount of capital and must be able to turn in and out of the motorcycle quickly considering that the longer the motorcycle is sold, the price will be decreased, and also if the tax of motorcycle stocks are in due date, it will increase the capital costs which is needed. The length of time a motorcycle has been sold has many factors, including tight business competition, where all of them are competing to increase sales of their second hand motorcycle and also have a system that makes working faster and more precise. From those problems, an idea is emerged to increase the motorcycle sales by increasing the reach of promotional media on the Android platform and creating an Android based computerized system that is able to accelerate the internal work of the company. In designing this application using the waterfall method, where the stages are gathering needs, building and evaluating waterfall, coding, testing, evaluating the system until finally the system can be used. The programming language used is Java and also uses the Android Studio application to create the Android application. The database used is MySQL. The supporting tools used are Photoshop, Corel Draw and the Android Emulator. With this android based second hand motorcycle sales information system to Increase Sales at Mokascirebon.com, it is hoped that it will be able to increase sales of second hand motorcycle and to simplify and accelerate the company's internal work

FADE: A forensic image generator for android device education

AbstractRealistic case studies are essential to training successful digital forensics examiners. However, the generation of realistic datasets is time‐consuming and resource taxing. This paper presents a technical solution that populates Android emulators with realistic mobile forensic data. The emulator's data can be extracted into a raw disk image that is usable in mobile forensic training scenarios. In addition, the tool allows a user to populate the Android emulators with custom text messages, phone contacts, phone calls, and files. This population task is achieved by utilizing the Android Debug Bridge, Android Content Providers, SQLite databases, and the NodeJS runtime environment. This paper presents the software design and development, the requirements and limitations, and the testing process implemented in this research. The contribution of this paper is twofold. First, it identifies potential data and mechanisms to generate Android mobile forensic datasets using customized data population. Second, it creates a foundation for future research on the topic of mobile forensic emulators for training purposes.This article is categorized under: Digital and Multimedia Science > Mobile Forensics Crime Scene Investigation > Education and Formation

An exploratory semantic analysis of logging questions

AbstractLogging is an integral part of software development. Software practitioners often face issues in software logging, and they post these issues on Q&A websites to take suggestions from the experts. In this study, we perform a three‐level empirical analysis of logging questions posted on six popular technical Q&A websites, namely, Stack Overflow (SO), Serverfault (SF), Superuser (SU), Database Administrators (DB), Software Engineering (SE), and Android Enthusiasts (AE). The findings show that logging issues are prevalent across various domains, for example, database, networks, and mobile computing, and software practitioners from different domains face different logging issues. The semantic analysis of logging questions using Latent Dirichlet Allocation (LDA) reveals trends of several existing and new logging topics, such as logging conversion pattern, Android device logging, and database logging. In addition, we observe specific logging topics for each website: DB (log shipping and log file growing/shrinking), SU (event log and syslog configuration), SF (log analysis and syslog configuration), AE (app install and usage tracking), SE (client server logging and exception logging), and SO (log file creation/deletion, Android emulator logging, and logger class of Log4j). We obtain an increasing trend of logging topics on the SO, SU, and DB websites whereas a decreasing trend of logging topics on the SF website.

SMS Observer: A dynamic mechanism to analyze the behavior of SMS-based malware

Nowadays smartphones become an indispensable tool in many people's everyday life that makes themselves attractive targets for attackers. Among various malware targeting at smartphones, SMS-based malware is one of the most notorious ones. Though a number of Android dynamic analysis frameworks have been proposed to analyze SMS-based malware, most of these frameworks or some Android tools, such as Google Android Emulator, do not support an app or malware to send SMS messages to a real smartphone; hence, security researchers cannot use them directly to analyze the behavior of SMS-based malware. In our previous work, SMS Helper, we designed an application layer tool to allow an app or malware in an Android emulator to send and receive SMS messages to or from a real smartphone. Based on SMS Helper, this paper proposes an Android dynamic analysis framework, called SMS Observer, to assist security researchers to analyze SMS-based malware. SMS Observer integrates SMS Helper into it as a client agent, meanwhile, and it maintains the integrity of system logs. This paper also figures out a way to detect whether an app is executed in an emulator and describes how to use SMS Observer to prevent such evasion. Experimental results using real-world malware samples show SMS Observer is much more effective in detecting SMS-related behavior of SMS-based malware than existing frameworks, such as Google Android Emulator, Andrubis, CopperDroid, and DroidBox. SMS Observer can analyze sophisticated SMS-based malware samples and provide a comprehensive view of malicious behavior.

SISTEM PAKAR DIAGNOSA PENYAKIT TANAMAN KELAPA SAWIT BERBASIS ANDROID

The lack of farmers' knowledge about various palm oil palm plant diseases and how to prevent plant is not attacked by the disease even with the lack of knowledge has led to mistakes in dealing with diseases that attack the oil palm plantations. On the other hand, to meet experts who are experts in the field of agriculture plant oil palm is very difficult, it is necessary for the right technology to solve the problem of oil palm plantations. One way to overcome this problem by building a plant disease expert system palm, to facilitate the farmers know the oil palm plant diseases. There are various methods in an expert system, but here using certainty factor. This study resulted in an expert system that can be used as a means for diagnosing the disease of oil palm trees are diseased, in the application development using Android SDK android studio and used to run android emulator on a computer or pc

PEMBUATAN APLIKASI PEMBELAJARAN AKOR DASAR GITAR

Every person is now easier to express themselves through music. Many music-themed applications can be found on smartphones, including those based on Android. With the rapid development of smartphone technology nowadays, more and more applications are used as learning media. With the rapid development of technology, an application that can help a beginner guitarist learn basic guitar chords, their shape and tone, is needed. Therefore, an application was developed to facilitate beginner guitarists to learn basic guitar chords. In making this application, the software used consisted of Adobe Flash CS5, Adobe Air, Android Emulator, Android SDK, Adobe Photoshop CS6, and Sound Recorder application. This application had been tested and successfully implemented to facilitate beginner guitarists to learn basic guitar chords, along with their shape and tone.

TaintMan: An ART-Compatible Dynamic Taint Analysis Framework on Unmodified and Non-Rooted Android Devices

Dynamic taint analysis (DTA), as a mainstream information flow tracking technique, has been widely used in mobile security. On the Android platform, the existing DTA approaches are typically implemented by instrumenting the Dalvik virtual machine (DVM) interpreter or the Android emulator with taint enforcement code. The most prominent problem of the interpreter-based approaches is that they cannot work in the new Android RunTime (ART) environment introduced since the 5.0 release. For the emulator-based approaches, the most prominent problem is that they cannot be deployed on real devices. In addition, almost all the existing Android DTA approaches only concern the explicit information flow caused by data dependence, while completely ignore the impact of implicit information flow caused by control dependence. These problems limit their adoption in the latest Android system and make them ineffective in detecting the state-of-the-art malware whose privacy-breaching behaviors are inactivated in the analyzed environment (e.g., the emulator) or conducted via implicit information flow. In this paper, we present TaintMan, an ART-compatible DTA framework that can be deployed on unmodified and non-rooted Android devices. In TaintMan, the taint enforcement code is statically instrumented into both the target application and the system class libraries to track data flow and common control flow. A specially designed execution environment reconstruction technique, named reference hijacking, is proposed to force the target application to reference the instrumented system class libraries. By enforcing on-demand instrumentation and on-demand tracking, the performance overhead is significantly reduced. We have developed TaintMan and deployed it on two popular stock smartphones (HTC One S equipped with Android-4.0 and Motorola MOTO G equipped with Android-5.0). The evaluation with malware samples and real-world applications shows that TaintMan can effectively detect privacy leakage behaviors with an acceptable performance overhead.