Android applications : Data leaks via advertising libraries

Recent studies have determined that many Android applications in both official and non-official online markets expose details of the users' smartphones without user consent. In this paper, we explain why such applications leak, how they leak and where the data is leaked to. In order to achieve this, we combine static and dynamic analysis to examine Java classes and application behaviour for a set of popular, clean applications from the Finance and Games categories. We observed that all the applications in our data set which leaked information (10%) had third-party advertising libraries embedded in their respective Java packages.

6 things I know about Geminoid F, or what I think about when I think about android theatre

On Friday evening I saw one of the finest theatre performances from an actor. Her subtle movements, her natural cadence, her ability to portray her character in a way that demonstrated diligent devotion, careful analysis and measured construction, was simply awe-inspiring. Which actor gave this fine performance? It was an android.

Mining permission patterns for contrasting clean and malicious android applications

An Android application uses a permission system to regulate the access to system resources and users' privacy-relevant information. Existing works have demonstrated several techniques to study the required permissions declared by the developers, but little attention has been paid towards used permissions. Besides, no specific permission combination is identified to be effective for malware detection. To fill these gaps, we have proposed a novel pattern mining algorithm to identify a set of contrast permission patterns that aim to detect the difference between clean and malicious applications. A benchmark malware dataset and a dataset of 1227 clean applications has been collected by us to evaluate the performance of the proposed algorithm. Valuable findings are obtained by analyzing the returned contrast permission patterns. © 2013 Elsevier B.V. All rights reserved.

Android malware detection with contrasting permission patterns

As the risk of malware is sharply increasing in Android platform, Android malware detection has become an important research topic. Existing works have demonstrated that required permissions of Android applications are valuable for malware analysis, but how to exploit those permission patterns for malware detection remains an open issue. In this paper, we introduce the contrasting permission patterns to characterize the essential differences between malwares and clean applications from the permission aspect. Then a framework based on contrasting permission patterns is presented for Android malware detection. According to the proposed framework, an ensemble classifier, Enclamald, is further developed to detect whether an application is potentially malicious. Every contrasting permission pattern is acting as a weak classifier in Enclamald, and the weighted predictions of involved weak classifiers are aggregated to the final result. Experiments on real-world applications validate that the proposed Enclamald classifier outperforms commonly used classifiers for Android Malware Detection.

Smartphone malware and its propagation modeling : A survey

Smartphones are pervasively used in society, and have been both the target and victim of malware writers. Motivated by the significant threat that presents to legitimate users, we survey the current smartphone malware status and their propagation models. The content of this paper is presented in two parts. In the first part, we review the short history of mobile malware evolution since 2004, and then list the classes of mobile malware and their infection vectors. At the end of the first part, we enumerate the possible damage caused by smartphone malware. In the second part, we focus on smartphone malware propagation modeling. In order to understand the propagation behavior of smartphone malware, we recall generic epidemic models as a foundation for further exploration. We then extensively survey the smartphone malware propagation models. At the end of this paper, we highlight issues of the current smartphone malware propagation models and discuss possible future trends based on our understanding of this topic. © © 2014 IEEE.

Propagation model of smartphone worms based on semi-Markov process and social relationship graph

Smartphone applications are getting more and more popular and pervasive in our daily life, and are also attractive to malware writers due to their limited computing source and vulnerabilities. At the same time, we possess limited understanding of our opponents in cyberspace. In this paper, we investigate the propagation model of SMS/MMS-based worms through integrating semi-Markov process and social relationship graph. In our modeling, we use semi-Markov process to characterize state transition among mobile nodes, and hire social network theory, a missing element in many previous works, to enhance the proposed mobile malware propagation model. In order to evaluate the proposed models, we have developed a specific software, and collected a large scale real-world data for this purpose. The extensive experiments indicate that the proposed models and algorithms are effective and practical. © 2014 Elsevier Ltd. All rights reserved.

Containing smartphone worm propagation with an influence maximization algorithm

In recent years, wide attention has been drawn to the problem of containing worm propagation in smartphones. Unlike existing containment models for worm propagation, we study how to prevent worm propagation through the immunization of key nodes (e.g.; the top k influential nodes). Thus, we propose a novel containment model based on an influence maximization algorithm. In this model, we introduce a social relation graph to evaluate the influence of nodes and an election mechanism to find the most influential nodes. Finally, this model provides a targeted immunization strategy to disable worm propagation by immunizing the top k influential nodes. The experimental results show that the model not only finds the most influential top k nodes quickly, but also effectively restrains and controls worm propagation.

Comparative mobile platforms security solutions

 Mobile platform security solution has become especially important for mobile computing paradigms, due to the fact that increasing amounts of private and sensitive information are being stored on the smartphones' on-device memory or MicroSD/SD cards. This paper aims to consider a comparative approach to the security aspects of the current smartphone systems, including: iOS, Android, BlackBerry (QNX), and Windows Phone.

Security and privacy of users' personal Information on smartphones

 This research investigated the proliferation of malicious applications on smartphones and a framework that can efficiently detect and classify such applications based on behavioural patterns was proposed. Additionally the causes and impact of unauthorised disclosure of personal information by clean applications were examined and countermeasures to protect smartphone users’ privacy were proposed.

Sayonara interviews: android-human theatre

Featuring a life-like humanoid robot, Seinendan Theatre Company (Japan) brought their performance Sayonara: Android-Human Theatre to Melbourne in August 2012. Geminoid F, an android, starred alongside Canadian actress Bryerly Long, in a performance that asks the question: What does life and death mean for humans as opposed to robots?

Infant feeding websites and apps: a systematic assessment of quality and content

Background: Internet websites and smartphone apps have become a popular resource to guide parents in their children’s feeding and nutrition. Given the diverse range of websites and apps on infant feeding, the quality of information in these resources should be assessed to identify whether consumers have access to credible and reliable information.

Objective: This systematic analysis provides perspectives on the information available about infant feeding on websites and smartphone apps.

Methods: A systematic analysis was conducted to assess the quality, comprehensibility, suitability, and readability of websites and apps on infant feeding using a developed tool. Google and Bing were used to search for websites from Australia, while the App Store for iOS and Google Play for Android were used to search for apps. Specified key words including baby feeding, breast feeding, formula feeding and introducing solids were used to assess websites and apps addressing feeding advice. Criteria for assessing the accuracy of the content were developed using the Australian Infant Feeding Guidelines.

Results: A total of 600 websites and 2884 apps were screened, and 44 websites and 46 apps met the selection criteria and were analyzed. Most of the websites (26/44) and apps (43/46) were noncommercial, some websites (10/44) and 1 app were commercial and there were 8 government websites; 2 apps had university endorsement. The majority of the websites and apps were rated poor quality. There were two websites that had 100% coverage of information compared to those rated as fair or poor that had low coverage. Two-thirds of the websites (65%) and almost half of the apps (47%) had a readability level above the 8th grade level.

Conclusions: The findings of this unique analysis highlight the potential for website and app developers to merge user requirements with evidence-based content to ensure that information on infant feeding is of high quality. There are currently no apps available to consumers that address a variety of infant feeding topics. To keep up with the rapid turnover of the evolving technology, health professionals need to consider developing an app that will provide consumers with a credible and reliable source of information about infant feeding, using quality assessment tools and evidence-based content.

Mobile phone-based electrochemiluminescence sensing exploiting the 'USB On-The-Go' protocol

A low-cost system to generate, control and detect electrochemiluminescence using a mobile smartphone is described. A simple tone-detection integrated circuit is used to switch power sourced from the phone's Universal Serial Bus (USB) 'On-The-Go' (OTG) port, using audible tone pulses played over the device's audio jack. We have successfully applied this approach to smartphones from different manufacturers and with different operating system versions. ECL calibrations of a common luminophore, tris(2,2′-bipyridine)ruthenium(II) ([Ru(bpy)3]²⁺), with 2-(dibutylamino)ethanol (DBAE) as a co-reactant, showed no significant difference in light intensities when an electrochemical cell was controlled by a mobile phone in this manner, compared to the same calibration generated using a conventional potentiostat. Combining this novel approach to control the applied potential with the measurement of the emitted light through the smart phone camera (using an in-house built Android app), we explored the ECL properties of a water-soluble iridium(III) complex that emits in the blue region of the spectrum. The iridium(III) complex exhibited superior co-reactant ECL intensities and limits of detection to that of the conventional [Ru(bpy)3]²⁺ luminophore.

A lightweight virtualization solution for android devices

Mobile virtualization has emerged fairly recently and is considered a valuable way to mitigate security risks on Android devices. However, major challenges in mobile virtualization include runtime, hardware, resource overhead, and compatibility. In this paper, we propose a lightweight Android virtualization solution named Condroid, which is based on container technology. Condroid utilizes resource isolation based on namespaces feature and resource control based on cgroups feature. By leveraging them, Condroid can host multiple independent Android virtual machines on a single kernel to support mutilple Android containers. Furthermore, our implementation presents both a system service sharing mechanism to reduce memory utilization and a filesystem sharing mechanism to reduce storage usage. The evaluation results on Google Nexus 5 demonstrate that Condroid is feasible in terms of runtime, hardware resource overhead, and compatibility. Therefore, we find that Condroid has a higher performance than other virtualization solutions.

Smartphone apps to improve fitness and increase physical activity among young people: protocol of the Apps for IMproving FITness (AIMFIT) randomized controlled trial

BACKGROUND: Physical activity is a modifiable behavior related to many preventable non-communicable diseases. There is an age-related decline in physical activity levels in young people, which tracks into adulthood. Common interactive technologies such as smartphones, particularly employing immersive features, may enhance the appeal and delivery of interventions to increase levels of physical activity in young people. The primary aim of the Apps for IMproving FITness (AIMFIT) trial is to evaluate the effectiveness of two popular "off-the-shelf" smartphone apps for improving cardiorespiratory fitness in young people.

METHODS/DESIGN: A three-arm, parallel, randomized controlled trial will be conducted in Auckland, New Zealand. Fifty-one eligible young people aged 14-17 years will be randomized to one of three conditions: 1) use of an immersive smartphone app, 2) use of a non-immersive app, or 3) usual behavior (control). Both smartphone apps consist of an eight-week training program designed to improve fitness and ability to run 5 km, however, the immersive app features a game-themed design and adds a narrative. Data are collected at baseline and 8 weeks. The primary outcome is cardiorespiratory fitness, assessed as time to complete the one mile run/walk test at 8 weeks. Secondary outcomes are physical activity levels, self-efficacy, enjoyment, psychological need satisfaction, and acceptability and usability of the apps. Analysis using intention to treat principles will be performed using regression models.

DISCUSSION: Despite the proliferation of commercially available smartphone applications, there is a dearth of empirical evidence to support their effectiveness on the targeted health behavior. This pragmatic study will determine the effectiveness of two popular "off-the-shelf" apps as a stand-alone instrument for improving fitness and physical activity among young people. Adherence to app use will not be closely controlled; however, random allocation of participants, a heterogeneous group, and data analysis using intention to treat principles provide internal and external validity to the study. The primary outcome will be objectively assessed with a valid and reliable field-based test, as well as the secondary outcome of physical activity, via accelerometry. If effective, such applications could be used alongside existing interventions to promote fitness and physical activity in this population. TRIAL REGISTRATION: Australian New Zealand Clinical Trials Registry: ACTRN12613001030763. Registered 16 September 2013.