Open Source Mobile Operating System Research Articles

DroidExaminer: An Android Malware Hybrid Detection System Based on Ensemble Learning

<p>Android is an open-source mobile operating system, with more than 70% of the mobile market share, widely popular on various intelligent devices. At the same time, the number of new malicious applications keeps increasing every year. In this paper, we first discuss the advantages and disadvantages of various detection methods for malicious software. A single detection method can only cover specific types of malware. Therefore, we propose a system that combines static structural analysis and dynamic detection of malware. This system has dual detection capability, which consists of a client and a server. The client is a lightweight Android application that is used to obtain the relevant data information of the installation package. The server is responsible for static analysis of APK and dynamic running of monitoring logs to get the relevant feature information. Based on the feature information, the Bagging algorithm of ensemble learning is adopted, and the decision tree and random forest are combined to identify the malware accurately. We collected 4210 Android software samples, with malicious apps accounting for about 20% of the total. Cross-testing of malware detection on this sample set showed that DroidExaminer achieved approximately 96% accuracy in detecting malware. It can resist confusion and conversion techniques, and the test performance overhead is less. In addition, DroidExaminer can alert the user to the details of malware intrusion so that the user can prevent malware intrusion.</p> <p> </p>

On the Effect of k Values and Distance Metrics in KNN Algorithm for Android Malware Detection

There is a remarkable increase in mobile device usage in recent years. The Android operating system is by far the most preferred open-source mobile operating system around the world. Besides, the Android operating system is preferred in many devices on the Internet of Things (IoT) devices are used in many areas of daily life. Smart cities, smart environment, health, home automation, agriculture, and livestock are some of the usage areas. Health is one of the most frequently used areas. Since the Android operating system is both the widely used operating system and open-source, the vast majority of malware released on the market is now designed for Android platforms. Therefore, devices using the Android operating system are under serious threat. In this study, a system that detects malware on Android operating systems based on machine learning is proposed. Besides, feature vectors are created with permissions that have an important place in the security of the Android operating system. Feature vectors created using the k-nearest neighbor algorithm (KNN), one of the machine learning techniques, are given as input to this algorithm, and a classification of malicious software and benign software is provided. In the KNN algorithm, the k value and the distance metric used to find the closest sample directly affect the classification performance. In addition, the study examining the parameters of the KNN algorithm in detail in permission-based studies is limited. For this reason, the performance of the malware detection system is presented comparatively using five different k values and five different distance metrics under different data sets. When the results are examined, it is observed that higher classification performances are obtained when values such as 1, 3 are given to k and metrics such as Euclidean and Minkowski are chosen instead of the Chebyshev distance metric.

WITHDRAWN: Design and development of artificial intelligence (AI) based board game (Gobang) using android

Abstract In modern society, more and more cell phones come into the work and life of ordinary people. With the popularization and application of the smart-phone technology, the operating system of mobile devices in the use of mobile phones is very broad, like Android, Symbian and iPhone. Among them, Android is a very popular open source mobile operating system for mobile phone and tablet personal computer. As the rapid development of computer and smart-phone, intelligent games have become an integral part of the universal life, not only does it make people entertainment, but also to develop people's intelligence. Intelligent game is one of the important branches of Artificial Intelligence. The artificial intelligence techniques are applied to the Gobang in this article. An intelligent Gobang game is designed and realized in the game between human and computer in Android operating system.

A collaborative policy-based security scheme to enforce resource access controlling mechanism

Advances in both telecommunications and Information technology have improved the way users do business online. Android, an open-source mobile operating system, is becoming an attractive target for cyber criminals to exploit due to its predefined permission model. Without classification, the mobile operating system permits installation of mobile applications of all kinds, including Trojans, thus making its trustworthiness into question. In this paper, we present a security system called collaborative policy-based security scheme (CSS) that permits users to customize the access permissions of Android applications during runtime. The proposed CSS security scheme validates the trustworthiness of each application before being installed. The experimental results show that the proposed CSS successfully detects all malicious applications with a run-time overhead of 2.7%.

Permission-based Android Malware Detection System Using Feature Selection with Genetic Algorithm

As the use of smartphones increases, Android, as a Linux-based open source mobile operating system (OS), has become the most popular mobile OS in time. Due to the widespread use of Android, malware developers mostly target Android devices and users. Malware detection systems to be developed for Android devices are important for this reason. Machine learning methods are being increasingly used for detection and analysis of Android malware. This study presents a method for detecting Android malware using feature selection with genetic algorithm (GA). Three different classifier methods with different feature subsets that were selected using GA were implemented for detecting and analyzing Android malware comparatively. A combination of Support Vector Machines and a GA yielded the best accuracy result of 98.45% with the 16 selected permissions using the dataset of 1740 samples consisting of 1119 malwares and 621 benign samples.

KEYLOGG - A TOUCH BASED KEY LOGGING APPLICATION

As Open Source Technologies are gaining popularity in the IT industry, consumers and developers look forward to it as a cheap and durable resource. However the concerns on privacy on Open Source are highly overlooked. Here, we intend to highlight the potential security risk in the open source mobile operating system, Android by implementing 'Touchlogger'. This application is capable of recording the touch activities happening on the smart phones keyboard. As the application will be a covert application, we wish to achieve our goal of logging by a third party keyboard. Our application will create a log file of activities done by the user in a certain time span. The activities such as call logs, texts, text messages and browsing history can be logged. The log file will keep the record of all activities and can be accessed by authorized user only. The log activity will be sent to the desired receiver. In user's interest to protect the privacy, one should always install application from Google Play Store only. Upon installation, the user should check the requested permission and be alerted if there is some slowness while typing.

Personalized Smartphone Search EngineEnhanced Security Using MAC Technique

Android is an open source mobile operating system developed by the android open source project (ASOP) developed by Google, use of mobile operating system is becoming widely popular, and is being used more and more these days by security personnel such as the department of homeland security, firefighters and also the emergency medical services etc which demands the cell phone to provide robust security. The idea of the project is to create personalized mobile search engine (PMSE) and provide security for user profile by using remote lock and wipe system with integrity checking of SMS notification using MAC based technique which uses a short piece of information which is used to prove the authenticity and the integrity of the message . Integrity determines accidental and intentional message changes and authenticity determines the messages origin

Mobile Botnet Attacks – an Emerging Threat: Classification, Review and Open Issues

The rapid development of smartphone technologies have resulted in the evolution of mobile botnets. The implications of botnets have inspired attention from the academia and the industry alike, which includes vendors, investors, hackers, and researcher community. Above all, the capability of botnets is uncovered through a wide range of malicious activities, such as distributed denial of service (DDoS), theft of business information, remote access, online or click fraud, phishing, malware distribution, spam emails, and building mobile devices for the illegitimate exchange of information and materials. In this study, we investigate mobile botnet attacks by exploring attack vectors and subsequently present a well-defined thematic taxonomy. By identifying the significant parameters from the taxonomy, we compared the effects of existing mobile botnets on commercial platforms as well as open source mobile operating system platforms. The parameters for review include mobile botnet architecture, platform, target audience, vulnerabilities or loopholes, operational impact, and detection approaches. In relation to our findings, research challenges are then presented in this domain.

Design and Implementation on Sina Micro-Blog Client Based on the Android System

This design, based on Android mobile development platform, uses Java language development, making the system have good portability and scalability. Sina micro-blog Android SDK provides third-party twitter application with API invoking service, in which document is easy to use, making the third-party micro-blog client not need to understand the complex validation and API calls process and share text or multimedia information to sina micro-blog.Micro - blog, namely the micro blog, is open Internet social services with the rise of Web 2.0, which allows users to update their status with brief text at any time and place, the length of each message within 140 words, and supports the publication of the images, audio, video and other multimedia. Each user is not only the creator of the micro content, is also the disseminator and distributors of micro content. Compared with the traditional blog, the admittance threshold of micro-blog is lower, and the originality and interactivity of instant messaging are stronger.Android is open source mobile operating system developed by Google and based on Linux platform. It includes operating system, user interface and applications-- all the required software in the mobile phone work. Fast development of the Android operating system mainly profits to a free, open source and good industry operating strategy.

An Android runtime security policy enforcement framework

Today, smart phone's malwares are deceptive enough to spoof itself as a legal mobile application. The front-end service of Trojans is attractive enough to deceive mobile users. Mobile users download similar malwares without knowing their illegitimate background threat. Unlike other vendors, Android is an open-source mobile operating system, and hence, it lacks a dedicated team to analyze the application code and decide its trustworthiness. We propose an augmented framework for Android that monitors the dynamic behavior of application during its execution. Our proposed architecture called Security Enhanced Android Framework (seaf) validates the behavior of an application through its permissions exercising patterns. Based on the exercised permissions' combination, the mobile user is intimated about the dangerous behavior of an application. We have implemented the proposed framework within Android software stack and ported it to device. Our initial investigation shows that our solution is practical enough to be used in the consumer market.