Understanding the Purpose of Permission Use in Mobile Apps

A majority of today's mobile apps integrate web content of various kinds. Unfortunately, the interactions between app code and web content expose new attack vectors: a malicious app can subvert its embedded web content to steal user secrets; on the other hand, malicious web content can use the privileges of its embedding app to exfiltrate sensitive information such as the user's location and contacts. In this paper, we discuss security weaknesses of the interface between app code and web content through attacks, then introduce defenses that can be deployed without modifying the OS. Our defenses feature WIREframe, a service that securely embeds and renders external web content in Android apps, and in turn, prevents attacks between em- bedded web and host apps. WIREframe fully mediates the interface between app code and embedded web content. Un- like the existing web-embedding mechanisms, WIREframe allows both apps and embedded web content to define simple access policies to protect their own resources. These policies recognize fine-grained security principals, such as origins, and control all interactions between apps and the web. We also introduce WIRE (Web Isolation Rewriting Engine), an offline app rewriting tool that allows app users to inject WIREframe protections into existing apps. Our evaluation, based on 7166 popular apps and 20 specially selected apps, shows these techniques work on complex apps and incur acceptable end-to-end performance overhead.

Despite continuous efforts to build and update mobile network infrastructure, mobile devices in developing regions continue to be constrained by limited bandwidth. Unfortunately, this coincides with a period of unprecedented growth in the sizes of mobile applications. Thus it is becoming prohibitively expensive for users in developing regions to download and update mobile apps critical to their economic and educational development. Unchecked, these trends can further contribute to a large and growing global digital divide. Our goal is to better understand the source of this rapid growth in mobile app code size, whether it is reflective of new functionality, and identify steps that can be taken to make existing mobile apps more friendly to bandwidth constrained mobile networks. We hypothesize that much of this growth in mobile apps is due to poor resource/code management, and do not reflect proportional increases in functionality. Our hypothesis is partially validated by mini-programs, apps with extremely small footprints gaining popularity in Chinese mobile platforms. Here, we use functionally equivalent pairs of mini-programs and Android apps to identify potential sources of “bloat,” i.e., inefficient uses of code or resources that contribute to large package sizes. We analyze a large sample of popular Android apps and quantify instances of code and resource bloat. We develop techniques for automated code and resource trimming, and successfully validate them on a large set of Android apps. We hope our results will lead to continued efforts to streamline mobile apps, making them easier to access and maintain for users in developing regions.

With the continuous growth in the usage of Android apps, ensuring their security has become critically important. An increasing number of malicious apps adopt anti-analysis techniques to evade security measures. Although some research has started to consider anti-runtime analysis (ARA), it is unfortunate that they have not systematically examined ARA techniques. Furthermore, the rapid evolution of ARA technology exacerbates the issue, leading to increasingly inaccurate analysis results. To effectively analyze Android apps, understanding their adopted ARA techniques is necessary. However, no systematic investigation has been conducted thus far. <p xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">In this paper, we conduct the first systematic study of the ARA implementations in a wide range of 117,270 Android apps (including both malicious and benign ones) collected between 2016 and 2023. Additionally, we propose a specific investigation tool named <small>ARAP</small> to assist this study by leveraging both static and dynamic analysis. According to the evaluation results, <small>ARAP</small> not only effectively identifies the ARA implementations in Android apps but also reveals many important findings. For instance, almost all apps have implemented at least one category of ARA technology (99.6% for benign apps and 97.0% for malicious apps).

Mobile apps are widely used and often process users’ sensitive data. Many taint analysis tools have been applied to analyze sensitive information flows and report data leaks in apps. These tools require a list of sources (where sensitive data is accessed) as input, and researchers have constructed such lists within the Android platform by identifying Android API methods that allow access to sensitive data. However, app developers may also define methods or use third-party library’s methods for accessing data. It is difficult to collect such source methods, because they are unique to the apps, and there are a large number of third-party libraries available on the market that evolve over time. To address this problem, we propose DAISY, a Dynamic-Analysis-Induced Source discoverY approach for identifying methods that return sensitive information from apps and third-party libraries. Trained on an automatically labeled dataset of methods and their calling context, DAISY identifies sensitive methods in unseen apps. We evaluated DAISY on real-world apps, and the results show that DAISY can achieve an overall precision of 77.9% when reporting the most confident results. Most of the identified sources and leaks cannot be detected by existing technologies.

While Android has become most popular OS in mobile phone market, more and more Android app developers are suffering from intellectual property infringement because it’s easy to extract the assets stored in the Android apps and to decompile Android apps to Java source code. This issue also poses threats to users’ privacy. In this article we reviewed the existing protection approaches for the protection of the source code and assets in Android apps, demonstrated the reason why Java Native Interface (JNI) approach can help improve the protection provided by existing approaches, developed 4 Android demo apps with 2 experiments conducted to evaluate the effectiveness of protection provided by the combination of Encryption and JNI approaches.

As many malicious apps have been distributed in Android markets, it is urgent to fix the vulnerabilities exploited by these apps and develop effective mitigation methods. In this paper, we identify a common vulnerability in many Android apps. This vulnerability is rooted in an unprotected Android component, called "Activity". Utilizing this vulnerability, a malicious app can stealthily and cannily collect sensitive user data. To better understand this issue, we have built "ActivityHijacker", an app that can detect the right moment to hijack the Activity component and intercept a user's password while it is being inputted in real time. To assess the prevalence of this vulnerability, we further analyzed 8 Android OSs (version 2.x to 5.x) and 22 banking apps collected in January 2016 from various Android markets. Our results show that all these Android OSs and apps are susceptible to the vulnerability; 14 out of 22 banking apps can be hijacked without any prompts. We further present a mitigation mechanism that restricts the Activity component to authorized apps.

In recent years, with the growing popularity of smartphones, the number of Android malware shows explosive growth. As malicious apps may steal users' sensitive data and money from mobile and bank accounts, it's important to detect potential malicious behavior in real time. To achieve this goal, we propose a dynamic behavior inspection and analysis framework for malicious behavior detection in Android apps. A customized Android system is built to record apps' API (Application Programming Interface) calls, permission uses, and some other runtime features such as user operations. We also develop an automated testing platform to test massive samples so as to collect dynamic app behavior records. Then we exploit these records to extract apps' runtime features of both user interaction and app dynamic behavior for benign and malicious behavior classification. The experimental results show that the app behavior classification can reach an accuracy of 99.0%, identifying 71.8% instances of malware samples by running each app for only 18 minutes.

Achieving resource-centric access control for web-app interactions on android

Most of today's mobile apps rely on the underlying networks to deliver key functions such as web browsing, file synchronization, and social networking. Compared to desktop-based networks, mobile networks are much more dynamic with frequent connectivity disruptions, network type switches, and quality changes, posing unique programming challenges for mobile app developers. As revealed in this paper, many mobile app developers fail to handle these intermittent network conditions in the mobile network programming. Consequently, network programming defects (NPDs) are pervasive in mobile apps, causing bad user experiences such as crashes, data loss, etc. Despite the development of network libraries in the hope of lifting the developers' burden, we observe that many app developers fail to use these libraries properly and still introduce NPDs. In this paper, we study the characteristics of the real-world NPDs in Android apps towards a deep understanding of their impacts, root causes, and code patterns. Driven by the study, we build NChecker, a practical tool to detect NPDs by statically analyzing Android app binaries. NChecker has been applied to hundreds of real Android apps and detected 4180 NPDs from 285 randomly-selected apps with a 94+% accuracy. Our further analysis of these defects reveals the common mistakes of app developers in working with the existing network libraries' abstractions, which provide insights for improving the usability of mobile network libraries.

The adoption of blockchain technology in prevalent applications has substantially increased the use of blockchain wallets. Even though consensus, cryptography, and decentralization make blockchain data structures pretty safe, it’s still hard to protect sensitive data at endpoints because each new block of data connects to all the previous blocks in a nearly unbreakable way. Thus, we seek to improve upon data security and transaction ease. Blockchain wallet store most of the users’ sensitive data in the form - namely initial-seed, private, public keys and other sensitive asset information. In order, we propose to attain sensitive data protection using an air-gapped hardware wallet and transactional privacy by hashing the transaction with the blake3 algorithm. More precisely, the mechanism consists of a credit card-sized air- gapped hardware wallet owned only by each party. Along with the wallet, a mobile app ‘‘Crypto-Trans’’ for certificate verification is introduced which acts as an interface between the hardware wallet and the blockchain. Last but not least, the proposed wallet is compared to existing wallets on key parameters to establish its relative superiority in terms of effectiveness and efficiency.

Confidentiality-minded framework for blockchain-based BIM design collaboration

Migrating to Android for iOS Developers gives youas an experienced native iOS app developerthe skills to learn native Android apps development from scratch. Starting with preparing your Android integrated development environment and introducing just enough Android application framework fundamentals, youll understand how to create a simple but meaningful HelloAndroid project immediately. This book provides the guidelines and tutorial projects to show you how to translate your existing iOS app to the Android platform. Youll use your mobile app knowledge to structure your Android apps in a similar way to how you would structure your iOS apps. To implement use cases with detailed screens, the most common mobile topics are discussed, including user interfaces, managing data, and networking with remote services. As you move through the book, youll create Android apps with rich UI components to handle common CRUD operations locally and remotely. There are many Android goodies described in the book. Instead of relying on routine text descriptions, youll discover the uniqueness of Android and appreciate the many features that are unique to the platform. This book also explores more powerful mobile UX patterns that are commonly used on the iOS and Android platforms. When you finish reading Migrating to Android for iOS Developers, youll be an Android developer as well as an iOS developer. And, you will be fully convinced you can do everything in Android that you can do in iOS. What youll learn How to maximize your existing iOS mobile knowledge to learn Android programming skills How to use the Android integrated development environment with the Eclipse ADT plugin How to translate your existing iOS code to Android with the following common mobile topics: Common mobile screen navigation patterns User interface components and UI animations Storing data Networking and using remote services Using system apps Maps and location awareness Mobile search frameworks Mobile analyticsWho this book is for This book is for iOS app developerslike youwho want to port their native iOS app to become an Android app. Also, if you are not an iOS developer, but already familiar with mobile apps, then this book can also help you understand Android development with step-by-step instructions and tutorial projects.

As the number of android applications (apps) available in the market are increasing rapidly, various types of security attacks using the android apps are also increasing with the same pace. The ransomware attack is one of these kind of security attacks in which the attackers locks the user's phone, encrypts user's data or blocks the user's access to their own data and threatens the user to pay a ransom to gain the access back. This cyber-threat is terrorizing the world from many years as it performs mimicry attacks i. e. combination of encryption & locking attacks. Android devices are more prone to these ransomware attacks compared to Windows and IOS devices. RansomwareElite is an android application which detects the presence of ransomware in the apps installed on an android device by checking the presence of any threatening text in app code or by verifying the permissions requested by the app from the user. In this paper, we focused on improving the performance of RansomwareElite app by extending its features. Now, the RansomwareElite app also searches the presence of any threatening image or file containing threatening text by analyzing the Android Package Kit(APK) file of android app. Moreover, it also detects some specific methods and classes in the code of the APK which could be used for locking the device and checks some specific permissions requested, for uninstalled apps now. Further, it maintains a database on the online server for the records of all the suspicious and ransomware apps detected by RansomwareElite. We have tested RansomwareElite with 9 Test Apps which are manually created based on the features of ransomware family and on 48 android devices. After analyzing the test results, we have found that the performance of RansomwareElite is improved after incorporating the new features and RansomwareElite app detects the presence of ransomware in installed as well as uninstalled apps present on an android's device in an efficient manner.

Android apps are daily installed by billions of users worldwide, who grant access to an extensive set of sensitive personal data. Different techniques have been developed over the years to understand how apps protect or harm their users’ privacy. However, these results have been produced in different research domains and addressing privacy from different perspectives, resulting in a growing but scattered body of knowledge. To bridge this gap, we have carried out a systematic mapping study to provide practitioners and researchers with an overview of the state-of-the-art technique, published between 2016 and 2020, to assess privacy in Android apps. In this paper, we highlight the most relevant findings, identify and analyse the most pressing gaps, and discuss the promising research directions.

PurposeFocusing on the Indian context, with the increase in the amount of data and its analysis in health-care knowledge management (KM), the privacy concerns rise which results in loss of trust of an individual in e-health-care systems. Privacy issues in health care, specific to India, are caused by prevalent complacency, culture, politics, budget limitations, large population and infrastructures. Because of these factors, data security requires a backseat that allows easy access to confidential information. Furthermore, the prevalent culture affects health-care disclosure in India. In many cultures, disclosing sensitive personal health-care data is considered ill mannered. This leads to discrepancies in the recorded health-care data and a decrease in the level of treatment meted out. The results and statistics of treatments given do not match the records because of inaccurate data reporting. With the significant rise in the analysis and use of technology in health-care KM systems, it is important to understand the perception of KM in terms of its use and awareness about data sharing in the KM system. The purpose of the paper is to measure the perception of privacy issues in the context of Indian healthcare management systems.Design/methodology/approachTo measure the perception of the use of the KM system, a set of 20 questions was circulated with a sample size of 337 which includes health-care researchers, doctors, practitioners and patients. The questions focused upon the use, share the sensitive health data in the KM platform. All the demographic information such as age, sex, religion, occupation is recorded. The privacy of the individual is maintained while circulating the questionnaire. The usage of health KM system and its privacy is measured through means and t-test.FindingsThe results of the t-test were found positive. This research study finds that the privacy factor is important among the Indians to share the information with the KM repository. It is also found that medical practitioners or data custodians are not much serious about sensitive data is being stored for analysis. From the statistical perception of usage of KM and its privacy, new architecture and privacy guidelines were suggested which can be considered in future research.Research limitations/implicationsFrom the literature review, the questionnaire has developed which can help policymakers and hospital administrators collect information about KM processes in health-care organizations, and this can result in higher performance of health organizations. The privacy factor can also be included in typical health KM architecture ensure that while knowledge acquisition process, privacy of individual or organization can be maintained.Social implicationsKM enhances the value of corporations and business industries through knowledge production, distribution and provides reliable access to the knowledge resources. KM in health care can comprise a confluence of formal methodologies and techniques to facilitate the creation, identification, acquisition, development, preservation, dissemination and finally the utilization of the various facets of a health-care enterprise’s knowledge assets. According to IBM Global executive report in the year 2012, the entire health-care system has changed from diseases-centric to patient-centric. India is emerging in terms of revenue and employment in the health-care field. The advances of information and communication technology help the health-care sector streamline for data structure and access and health analytics.Originality/valueIn India, the KM is frequently used in health-care industries majorly by health-care practitioners and professionals. As health-care data and knowledge are considered to be sensitive, the privacy of an individual while using the data cannot be compromised. The proposed empirical work will provide a solution in determining the main barriers of implementing privacy policies that need to be solved first and to ensure effective implementation of KM in the health care of India.