Android Mobile Platform Research Articles

User Interface Design for the Orca Music Player Mobile Application

The rapid development in the field of information technology has resulted in a significant change in the way music is listened to. The current digital generation prefers to listen to music online through their digital devices. Thus, designing User Interface and User Experience on Mobile Music Player Applications using the User Centered Design method which consists of Plan the human centered process, Specify the context of use, Specify user and organizational requirements, and Produce design Solution. The target audience for this design is productive age children 15-35 years old with product limitations that only reach the prototype stage and feature services that are still lacking. The platform used is the android and ios mobile platform and UI design by making Wireframe of the application design.

Android malware detection framework based on sensitive opcodes and deep reinforcement learning

Malware attack is a growing problem on the Android mobile platform due to its popularity and openness. Although numerous malware detection approaches have been proposed, it still remains challenging for malware detection due to a large amount of constantly mutating apps. The opcode, as the most fundamental part of Android app, possesses good resistance against obfuscation and Android version updates. Due to the large number of opcodes, most opcode-based methods employ statistical-based feature selection, which disrupts the correlation and semantic information among opcodes. In this paper, we propose an Android malware detection framework based on sensitive opcodes and deep reinforcement learning. Firstly, we extract sensitive opcode fragments based on sensitive elements and then encode the features using n-gram. Next, we use deep reinforcement learning to select the optimal subset of features. During the process of handling opcodes, we focus on preserving semantic information and the correlation among opcodes. Finally, our experimental results show an accuracy of 0.9670 by using the 25 opcode features we obtained.

A GCC Artificial Food Additives Management based Mobile Application Development

Artificial food additives pose significant health risks to Gulf Cooperation Council (GCC) citizens despite regional authorities' extensive medical, legislative, and technological efforts. Literature highlights the detrimental impacts of these additives, including malnutrition, digestive disorders, respiratory problems, skin issues, hives, nausea, diarrhea, shortness of breath, allergic reactions, high blood pressure, and tumors. The research project at hand aims at becoming the first official and comprehensive mobile application of its own in the GCC region that manages the calculation and demonstration of an up-to-date health and legal knowledge base of the impacts of artificial additives, enhances the awareness, automatically recognizes the artificial additives, and provides alternative solutions, for both android and IOS mobile platforms. This research project introduces "Weqaya," a pioneering mobile application designed to manage, educate, and raise awareness about the effects of artificial additives. Weqaya provides real-time health and legal information, identifies additives, and suggests alternative solutions for Android and iOS platforms. The project employs an Agile-based SDLC model to explore, develop, and evaluate the food additive phenomena in Weqaya. The application's usability evaluation scores a promising 95.21%, indicating its potential utility for GCC health ministries, dietitians, academics, researchers, and food producers in enhancing knowledge and promoting non-artificial food options.

AI Wings: An AIoT Drone System for Commanding ArduPilot UAVs

Recent advances in drone and artificial intelligence (AI) technologies have enabled many innovative applications, such as package delivery, reconnaissance, and search and rescue, to name a few. In this article, we propose AI wings, an artificial intelligence of things (AIoT) drone system for commanding multiple unmanned aerial vehicles and deploying AI models. We integrated ArduPilot with the Android mobile platform, which equips DIY drones with AI computing power and 4G/5G connectivity. Embedded control software is developed to cooperate with the AI Wings cloud. Users can easily convert ArduPilot drones into AIoT drones using Android phones, and connect to a cloud server to create their own Internet of Drones. Our cloud server is also integrated with the drone simulation software AirSim for simulating drone missions in virtual reality (VR) worlds. The virtual simulation enables users to test software/hardware configurations as well as train AI models. Moreover, to ensure secure communication, we propose an authentication protocol based on elliptic-curve cryptography with pseudoidentities and time freshness check. In summary, AI Wings provides a cloud server for commanding drone fleets securely, software/hardware design for AIoT drones, and VR simulation for training and testing AI models. Users can install the AI models on the drones directly. To test the system, we built an experimental medical drone service, which delivers an automated external defibrillator to people with a sudden cardiac attack in the shortest time possible.

Research on Key Technologies of 3D Rendering Algorithm in Urban Architecture Design

With the rapid development of 3D rendering technology, the country attaches great importance to the strategic significance of the "digital city", and the emergence of high-performance mobile devices has given the mobile terminal 3D city visualization technology a broad development prospect and strong technical support. Based on the Android mobile platform, this paper studies the key technologies of 3D city visualization. Focus on the establishment of 3D city models, 3D data organization, and the use of their respective advantages in 2D and 3D to realize the linkage display of 2D and 3D city scenes, and realize the multi-resolution display of 3D cities through the streamlining of building models and the study of model selection strategies. The final design realizes the mobile terminal 3D city visualization interactive system.

HB-ReTriple: Mobile rendering optimization based on efficient history reusing

UI rendering on smartphones needs powerful CPU and GPU to meet user-perceived smoothness, and it contributes a significant portion of energy consumption of the battery-driven device. Improving energy efficiency of rendering process without degrading user experience has attracted research attention in both academia and industry. In this work, we propose an energy-efficient rendering optimization framework, called HB-ReTriple, based on reusing the rendering results of the unchanged Views across adjacent frames. This reusing can effectively reduce the amount of computation spent on UI rendering, thereby saving considerable energy. We implement our framework on a real Android mobile platform, and the experiments show that HB-ReTriple achieves an average speedup of 2.89x in terms of frames-per-second (FPS) and an energy saving of 38.2% per-frame.

On the evaluation of android malware detectors against code-obfuscation techniques.

The Android mobile platform is the most popular and dominates the cell phone market. With the increasing use of Android, malware developers have become active in circumventing security measures by using various obfuscation techniques. The obfuscation techniques are used to hide the malicious code in the Android applications to evade detection by anti-malware tools. Some attackers use the obfuscation techniques in isolation, while some attackers use a mixed approach (i.e., employing multiple obfuscation techniques simultaneously). Therefore, it is crucial to analyze the impact of the different obfuscation techniques, both when they are used in isolation and when they are combined as hybrid techniques. Several studies have suggested that the obfuscation techniques may be more effective when used in a mixed pattern. However, in most of the related works, the obfuscation techniques used for analysis are either based on individual or a combination of primitive obfuscation techniques. In this work, we provide a comprehensive evaluation of anti-malware tools to gauge the impact of complex hybrid code-obfuscations techniques on malware detection capabilities of the prominent anti-malware tools. The evaluation results show that the inter-category-wise hybridized code obfuscation results in more evasion as compared to the individual or simple hybridized code obfuscations (using multiple and similar code obfuscations) which most of the existing related work employed for the evaluation. Obfuscation techniques significantly impact the detection rate of any anti-malware tool. The remarkable result i.e., almost 100% best detection rate is observed for the seven out of 10 tools when analyzed using the individual obfuscation techniques, four out of 10 tools on category-wise obfuscation, and not a single anti-malware tool attained full detection (i.e., 100%) for inter-category obfuscations.

An investigation study for risk calculation of security vulnerabilities on android applications

Applications within mobile devices, although useful and entertaining, come with security risks to private information stored within the device such as name, address, and date of birth. Standards, frameworks, models, and metrics have been proposed and implemented to combat these security vulnerabilities, but they remain to persist today. In this review, we discuss the risk calculation of android applications which is used to determine the overall security of an application. Besides, we also present and discuss the permission-based access control models that can be used to evaluate application access to user data. The study also focuses on examining the predictive analysis of security risks using machine learning. We conduct a comprehensive review of the leading studies accomplished on investigating the vulnerabilities of the applications for the Android mobile platform. The review examines various well-known vulnerabilities prediction models and highlights the sources of the vulnerabilities, prediction technique, applications and the performance of these models. Some models and frameworks prove to be promising but there is still much more research needed to be done regarding security for Android applications.

A Low-Cost Smart Digital Mixer System Based on Speech Recognition

When a band is performing at a public occasion, certain sound effects are expected to be added to enliven the atmosphere. To achieve this effect, microphones and instruments are all connected to an audio mixer, then the expected audio output will be played through the speakers. However, sound engineers always spend plenty of time tuning the mixer until the satisfied results are obtained. This paper presents a smart digital mixer system that integrates touch control, speech control, and commonly used functions on an Android mobile platform to improve the mobility of audio mixer while tuning. The proposed system adopts a digital signal processor (DSP) as the core of the hardware architecture. The application provides a UI interface on an Android mobile phone in order to achieve the functions of speech recognition and touch control. The control commands will be transmitted to DSP via Bluetooth 5.0, self-defined Bluetooth packet format (SBPF), and data transfer controller (DTC). The main contribution of this work is to propose multiple functions of a mixer system with a convenient and interactive user interface. The experimental results show the average accuracy of all respondents reached 92.3%. Moreover, the proposed system has the advantage of having a low-cost hardware circuit design, and provides high flexibility of setting for the audio mixer system according to the user’s preference.

Aceh's Historic Tourist Attractions: An Augmented Reality-Based Prototype of a Virtual Tour Application

Indonesia has attractive tourist destinations for tourism such as beautiful interior areas and historical places. The purpose of this research is to design and build a virtual tour application for Aceh tourism objects using augmented reality. One of the problems that occur in tourist objects is that foreign tourists do not have an idea about the tourist objects they want to visit. The technology used in this study and previous research is Augmented Reality, but previous research only displays 3D tourist objects, while in this study, augmented reality technology is incorporated into the design of the 4 Aceh tourist attractions by showing a 3-dimensional illustration of the object as a whole. for the outside of the building and displays a virtual tour image in the form of a video to illustrate the inside of the tourist attraction building on the Android mobile platform. Based on the results of distance and angle testing, the best (ideal) distance that produces clear and bright marker detection is found at a distance between 25 to 45 cm, while the best angle is between an angle with a slope of 0° to 60°. Measurements of distances and angles are carried out using threads, bows and measuring tapes. The 3D object is successfully displayed by pointing the camera at the marker to be detected.Â

M2VMapper: Malware-to-Vulnerability mapping for Android using text processing

Over 90% of the mobile malware target Android mobile platform. Many Machine Learning (ML) and Deep Learning (DL) techniques have been used to detect and analyze Android malware, however, there is a many-to-many mapping between malware and vulnerability. This means a single malware can exploit multiple security vulnerabilities (known or unknown) and a single vulnerability can be exploited by multiple malware. Therefore, it is important to analyze the behaviour of malware to identify and reduce the vulnerabilities. Till date, no ML/DL or other technique has been deployed to analyze the malware behaviour to identify and reduce the vulnerabilities. The paper proposes a DL framework ‘M2VMapper’ that combines transfer learning and pretrained language models, which aims to map malware and potential vulnerabilities using a 2D matrix. The many-to-many mapping matrix is obtained by using transformer models such as BERT and XLNET; in addition to DL models such as Multi-layer Perceptron (MLP), Recurrent Neural Network (RNN) and Textual Convolutional Neural Network (TextCNN). This malware-to-vulnerability mapping can be leveraged to measure the severity of unknown vulnerabilities and malware during the initial phase of application development. The study is a first of its kind and considers 150 malware families from different datasets, such as AMD, CICInvesAndMal2019, and Androzoo with a total of 48 907 malware samples and 9 vulnerability types affecting Android. M2VMapper has delivered highly promising results with an accuracy of 99.81%, when XLNET is used with TextCNN, and precision and F1-scores above 95% using DL models.

Android mobile application for wildfire reporting and monitoring

Peat fires cause major environmental problems in Central Kalimantan Province, Indonesia and threaten human health and effect the social-economic sector. The lack of peat fire detection systems is one factor that causing these reoccurring fires. Therefore, in this study, we develop an Android mobile platform application and a web-based application to support the citizen-volunteers who want to contribute wildfires reports, and the decision-makers who wish to collect, visualize, and evaluate these wildfires reports. In this paper, the global navigation satellite system (GNSS) and a global position system (GPS) sensor from a smartphone’s camera, is a useful tool to show the potential fire and smoke’s close-range location. The exchangeable image (EXIF) file image and GPS metadata captured by a mobile phone can store and supply raw observation to our devices and sent it to the data center through global internet communication. This work’s results are the proposed application easy-to-use to monitoring potential peat fire by location and data activity. This paper focuses on developing an application for the mobile platform for peat fire reporting and a web-based application to collect peat fire location for decision-makers. Our main objective is to detect the potential and spread of fire in peatlands as early as possible by utilizing community reports using smartphones.

Modeling Correlation between Android Permissions Based on Threat and Protection Level Using Exploratory Factor Plane Analysis

The evolution of mobile technology has increased correspondingly with the number of attacks on mobile devices. Malware attack on mobile devices is one of the top security challenges the mobile community faces daily. While malware classification and detection tools are being developed to fight malware infection, hackers keep deploying different infection strategies, including permissions usage. Among mobile platforms, Android is the most targeted by malware because of its open OS and popularity. Permissions is one of the major security techniques used by Android and other mobile platforms to control device resources and enhance access control. In this study, we used the t-Distribution stochastic neighbor embedding (t-SNE) and Self-Organizing Map techniques to produce a visualization method using exploratory factor plane analysis to visualize permissions correlation in Android applications. Two categories of datasets were used for this study: the benign and malicious datasets. Dataset was obtained from Contagio, VirusShare, VirusTotal, and Androzoo repositories. A total of 12,267 malicious and 10,837 benign applications with different categories were used. We demonstrate that our method can identify the correlation between permissions and classify Android applications based on their protection and threat level. Our results show that every permission has a threat level. This signifies those permissions with the same protection level have the same threat level.

Α PATTERN-BASED AUGMENTED REALITY APPLICATION FOR THE DISSEMINATION OF CULTURAL HERITAGE

Abstract. Augmented Reality (AR) is more than an added value for Cultural Heritage (CH); it is vital for its sustainability, promotion and dissemination, increasing accessibility in CH even during difficult periods of time, like the Covid-19 pandemic. In order to be meaningful and engaging, an AR application should have the following characteristics: easiness of use, high-quality representations and compatibility. This paper presents a marker-less mobile AR application for the display and inspection of high-resolution 3D cultural assets, overlayed on a particular location in the real-world scene. Instead of predefined markers, an image captured by the user is exploited as a pattern for real-time feature matching, pose estimation and scene augmentation. Our approach is based on pure computer vision and photogrammetric techniques, implemented using native C++ and Java code for Android mobile platforms. It is built with the use of the OpenCV library and the OpenGL ES graphics API without any dependencies of AR Software Development Kits (SDKs). Therefore, it supports cross-vendor portability regarding mobile model devices and hardware specifications. The evaluation of the developed application examines the performance of various matching techniques and the overall responsiveness of processing and 3D rendering on mid-range and low-end smartphones. The results showcase the reliability and responsiveness of the pattern recognition as well as the potential of the 3D graphics engine to render and overlay complex 3D models balancing between visual quality and time. The proposed methodology is applied to the Ciborium of the church of St. Charalabos, located at St. Stephen’s Monastery in Meteora, Greece.

Research and Development of Smart Home Security System Based on Wechat Control

With the improvement of living standards, people’s requirements for safety and comfort gradually improve, which requires us to constantly improve home security. With the rapid development of the Internet of things (hereinafter referred to as IOT), we have set up a smart home security system (hereinafter referred to as SHSS), which can be controlled by wechat. Through the IOT technology, the SHSS can contact various subsystems according to the needs of users, including lighting control, security protection, fire prevention and anti-theft, which will bring more humanized operation experience. Through wireless communication technology, we can monitor all kinds of indoor environment in real time, which will prevent illegal intrusion and other behaviors. At the same time, with the popularity of Android, IOS and other mobile platforms, SHSS has been developed into a variety of applications, such as wechat, which can realize remote control of indoor devices. Firstly, this paper analyzes the overall architecture and control module of SHSS. Then, this paper analyzes various subsystems, which can complete the system development in more detail.

HEFESTDROID: Highly Effective Features for Android Malware Detection and Analysis

Rapid globalization and advances in mobile technology have brought about phenomenal attention and great opportunities for android application developers to contribute meaningfully to the global digital market. The android mobile platform being one of the famous mobile operating systems has the highest number of applications in the digital market with a total market share of 76.23% between August 2018 and August 2019, according to a report of global stats counter. However, the substantial number of applications on the platform has led to a great number of malware attacks on the user’s privacy and sensitive documents. Consequently, a significant number of malware detection studies have been carried out to reduce the number of malware attacks. This paper analyses the impact of using highly effective android permission features to decipher the problem malware attack. The Highly Effective Features for Android Malware Detection and Analysis (HEFEST) summarises four effective android permission features to be considered in conducting malware detection analysis and classifications. The features recognized in this study are; Normal Declared Permission, Dangerous Permission, Signature-Based Permission, and Signature-or-system. The selection is based on the capabilities of the features in depicting the behaviors of android apps. The research data are drawn from Drebin open source, the dataset comprises 15,036 benign and malicious applications extracted from 215 distinct features, the records 9,026 were malicious and 6,010 benign applications. However, this research compares the detection accuracy of android permission features using machine learning-based algorithms; Support Vector Machine, and K-Nearest Neighbor to achieve a comprehensive accuracy ratio of malware detection, the classifier has a strong accuracy decision of classification and exceptional computational efficiency. The model correctly classified 2,812 out of 2,869 malicious applications appropriately with an accuracy of 98.0% and also classified 1,607 out of 1,642 accurately with a success rate of 97.9%. Generally, 98.0% of classification accuracy was archived.

Design and Development of Mobile Application in Indonesian Language Learning For Foreign Speakers Level A1

This paper describes about the design and development of Android mobile platform application in the learning of Indonesian Language for Foreign Speakers as the term used Bahasa Indonesia bagi Penutur Asing or as abbreviated BIPA. The Android Studio is used to create and set up a set of application programming interfaces (APIs) and Kernel Linux Platform. The interface program was designed to give effectiveness and flexibilities required in the process of learning. The program code was written and installed in the users Smart Phone. The official language programming used for Android development is Java to make the program running easily for the users to use the application because the mobile application does not use many resources. Once the application was ready, then installed into various types of Smart Phone with various Android platforms, and tested. The program was tested to BIPA foreign students who were learning BIPA Level A1 to see if the program ran well. This aimed to test its effectiveness and impact. The data of pre-test and interview were collected from foreign students who have already learned Indonesian language before and who were never in order to see the baseline of respondents competencies. Pre-test, Post-test and interview test scores were compared to see if there was an increase in respondents competencies. The research findings shows that there was a significant increase on the foreign students’ skills. The increase on the written test through pre-test and post-test showed by 30% and 18 % on the interview. In contrast, the most significant increase was occurred in the group of students who never learned before. This increase showed by 56%, whereas the increase in the group of foreign students who have already learned Indonesian language showed by 12%. Furthermore, this increase significantly also occurred in interview at 32% to the group of foreign students who never learned Indonesian language before and 8% to the group of foreign students who already learned Indonesian language. This findings shows that Mobile Application provides effectiveness, efficiency, flexibilities, and accelerated learning to the group of foreign speakers who never learned BIPA before.

Graphical Password Authentication For Child Personal Storage Application

Mobile applications are very popular among the children nowadays as children use it for many purposes such as entertainment, learning or education. Keeping hand written notes in hard copy is not a good choice as the accumulated papers would mess up child’s study space. Although there is high adoption of mobile application among children nowadays, but children are not educated to practice password to secure their personals in their primary school syllabus. Therefore, an application which can provide personal storage for children to store their notes in softcopy forms called Graphical Password Authentication for Child Personal Storage Application was proposed. The adoption of graphical password authentication in the proposed system is intended to cultivate children practice password to secure their files in an interesting method. The proposed system is developed in Android mobile application platform and the Object-oriented Mobile Application Development is applied as methodology of the project. The proposed system’s functional requirements are implemented according to user’s requirements and the application interfaces implementation also based on user’s characteristics that has been studied in literature reviews. The significance of the project is awareness on secure file keeping among the children. Children can use graphical password in their childhood age would be the advantage for them in the future because they would make a sense to protect privacy by setting up password. In terms of information security, the proposed system has mentioned some values that would be achieved which are authentication, confidentiality and availability.

Pengenalan Rumah Adat Sumatera Utara Menggunakan Augmented Rality Berbasis Android

This study aims to increase knowledge through multimedia-based learning by utilizing information technology, namely Augmented Reality (AR) in knowing the types of traditional houses in North Sumatra province.Augmented reality (AR), is the appearance of real-world dimensions with virtual worlds in real time. In contrast to virtual reality which completely replaces what is in the real world, augmented reality is a process of adding or completing virtual reality. Augmented reality depicts a three-dimensional object on a marker as a unique pattern so that it can be recognized by the object processing application. Augmented reality can be used to create a more interactive recognition environment where users can interact directly with objects in cyberspace. The augmented reality application produced in this study was developed using the Vuforia Software Development Kit. In addition, the resulting application runs on the android mobile platform, which is expected to provide easy access for users

Realization of Mobile Augmented Reality System Based on Image Recognition

With the development of computation technology, the augmented reality (AR) is widely applied in many fields as well as the image recognition. However, the AR application on mobile platform is not developed enough in the past decades due to the capability of the mobile processors. In recent years, the performance of mobile processors has changed rapidly, which makes it comparable to the desktop processors. This paper proposed and realized an AR system to be used on the Android mobile platform based on the image recognition through EasyAR engine and Unity 3D development tools. In this system, the image recognition could be done locally and/or using cloud recognition. Test results show that the cloud-based recognition is more efficient and accuracy than the local recognition for the mobile AR when there are more images to be recognized at the same time.