Android applications collecting data from users must protect it according to the current legal frameworks. Such data protection has become even more important since in 2018 the European Union rolled out the General Data Protection Regulation (GDPR). Since app developers are not legal experts, they find it difficult to integrate privacy-aware practices into source code development. Despite these legal obligations, developers have limited tool support to reason about data protection throughout their app development process.
This paper explores the use of static program slicing and software visualization to analyze privacy-relevant data flows in Android apps. We introduce SliceViz, a web tool that analyzes an Android app by slicing all privacy-relevant data sources detected in the source code on the back-end. It then helps developers by visualizing these privacy-relevant program slices.
We conducted a user study with 12 participants demonstrating that SliceViz effectively aids developers in identifying privacy-relevant properties in Android apps.
Our findings indicate that program slicing can be employed to identify and reason about privacy-relevant data flows in Android applications. With further usability improvements, developers can be better equipped to handle privacy-sensitive information.
Android applications may leak privacy data carelessly or maliciously. In this work we perform inter-component data-flow analysis to detect privacy leaks between components of Android applications. Unlike all current approaches, our tool, called IccTA, propagates the context between the components, which improves the precision of the analysis. IccTA outperforms all other available tools by reaching a precision of 95.0% and a recall of 82.6% on DroidBench. Our approach detects 147 inter-component based privacy leaks in 14 applications in a set of 3000 real-world applications with a precision of …
Context: Post-release user feedback plays an integral role in improving software quality and informing new features. Given its growing importance, feedback concerning security enhancements is particularly noteworthy. In considering the rapid uptake of Android we have examined the scale and severity of Android security threats as reported by its stakeholders. Objective: We systematically mine Android issue logs to derive insights into stakeholder perceptions and experiences in relation to certain Android security issues. Method: We employed contextual analysis techniques to study issues raised …
In this paper we claim that an efficient and readily applicable means to improve privacy of Android applications is: 1) to perform runtime monitoring by instrumenting the application bytecode and 2) in-vivo, i.e. directly on the smartphone. We present a tool chain to do this and present experimental results showing that this tool chain can run on smartphones in a reasonable amount of time and with a realistic effort. Our findings also identify challenges to be addressed before running powerful runtime monitoring and instrumentations directly on smartphones. We implemented two use-cases leverag…
Many Android applications collect data from users. When they do, they must protect this collected data according to the current legal frameworks. Such data protection has become even more important since the European Union rolled out the General Data Protection Regulation (GDPR). App developers have limited tool support to reason about data protection throughout their app development process. Although many Android applications state a privacy policy, privacy policy compliance checks are currently manual, expensive, and prone to error. One of the major challenges in privacy audits is the signif…
China is currently the country with the largest number of Android smartphone users. We use a combination of static and dynamic code analysis techniques to study the data transmitted by the preinstalled system apps on Android smartphones from three of the most popular vendors in China. We find that an alarming number of preinstalled system, vendor and third-party apps are granted dangerous privileges. Through traffic analysis, we find these packages transmit to many third-party domains privacy sensitive information related to the user's device (persistent identifiers), geolocation (GPS coordina…
Access to privacy-sensitive information on Android is a growing concern in the mobile community. Albeit Google Play recently introduced some privacy guidelines, it is still an open problem to soundly verify whether apps actually comply with such rules. To this aim, in this paper, we discuss a novel methodology based on a fruitful combination of static analysis, dynamic analysis, and machine learning techniques, which allows assessing such compliance. More in detail, our methodology checks whether each app i) contains a privacy policy that complies with the Google Play privacy guidelines, and i…
Android devices are equipped with many pre-installed applications which have the capability of tracking and monitoring users. Although applications coming pre-installed pose a great danger to user security and privacy, they have received little attention so far among researchers in the field. In this study, we collect a dataset comprising such applications and make it publicly available. Using this dataset, we analyze tracker SDKs, manifest files and the use of cloud services and report our results. We also conduct a user survey to understand concerns and perceptions of users. Last but not lea…
The purpose of the General Data Protection Regulation (GDPR) is to provide improved privacy protection. If an app controls personal data from users, it needs to be compliant with GDPR. However, GDPR lists general rules rather than exact step-by-step guidelines about how to develop an app that fulfills the requirements. Therefore, there may exist GDPR compliance violations in existing apps, which would pose severe privacy threats to app users. In this paper, we take mobile health applications (mHealth apps) as a peephole to examine the status quo of GDPR compliance in Android apps. We first pro…
We evaluate the power of simple networks side-channels to violate user privacy on Android devices. Specifically, we show that, using blackbox network metadata alone (i.e., traffic statistics such as transmission time and size of packets) it is possible to infer several elements of a user's location and also identify their web browsing history (i.e, which sites they visited). We do this with relatively simple learning and classification methods and basic network statistics. For most Android phones currently on the market, such process-level traffic statistics are available for any running proce…
We present the design and design rationale for the user interfaces for Privacy Enhancements for Android (PE for Android). These UIs are built around two core ideas, namely that developers should explicitly declare the purpose of why sensitive data is being used, and these permission-purpose pairs should be split by first party and third party uses. We also present a taxonomy of purposes and ways of how these ideas can be deployed in the existing Android ecosystem.
The transparency and privacy behavior of mobile browsers has remained widely unexplored by the research community. In fact, as opposed to regular Android apps, mobile browsers may present contradicting privacy behaviors. On the one end, they can have access to (and can expose) a unique combination of sensitive user data, from users' browsing history to permission-protected personally identifiable information (PII) such as unique identifiers and geolocation. However, on the other end, they also are in a unique position to protect users' privacy by limiting data sharing with other parties by imp…
Mobile applications (hereafter, apps) collect a plethora of information regarding the user behavior and his device through third-party analytics libraries. However, the collection and usage of such data raised several privacy concerns, mainly because the end-user - i.e., the actual owner of the data - is out of the loop in this collection process. Also, the existing privacy-enhanced solutions that emerged in the last years follow an "all or nothing" approach, leaving the user the sole option to accept or completely deny the access to privacy-related data. This work has the two-fold objective o…
With mobile applications and associated services becoming increasingly popular, concerns are being raised about private data leakages have raised. Previous solutions to this well-known set of problems have approached it from the ground up but required rewriting the operating system which is unnecessary and burdensome. In this work, a framework we proposed to overcome these issues by applying a pseudo data technique and cloud-based decision-making system to identify potential privacy leakages.
Privacy concerns have long been expressed around smart devices, and the concerns around Android apps have been studied by many past works. Over the past 10 years, we have crawled and scraped data for almost 1.9 million apps, and also stored the APKs for 135,536 of them. In this paper, we examine the trends in how Android apps have changed over time with respect to privacy and look at it from two perspectives: (1) how privacy behavior in apps have changed as they are updated over time, (2) how these changes can be accounted for when comparing third-party libraries and the app's own internals. T…
Smartphones, the devices we carry everywhere with us, are being heavily tracked and have undoubtedly become a major threat to our privacy. As "tracking the trackers" has become a necessity, various static and dynamic analysis tools have been developed in the past. However, today, we still lack suitable tools to detect, measure and compare the ongoing tracking across mobile OSs. To this end, we propose MobileAppScrutinator, based on a simple yet efficient dynamic analysis approach, that works on both Android and iOS (the two most popular OSs today). To demonstrate the current trend in tracking,…
Contemporary mobile applications (apps) are designed to track, use, and share users' data, often without their consent, which results in potential privacy and transparency issues. To investigate whether mobile apps have always been (non-)transparent regarding how they collect information about users, we perform a longitudinal analysis of the historical versions of 268 Android apps. These apps comprise 5,240 app releases or versions between 2008 and 2016. We detect inconsistencies between apps' behaviors and the stated use of data collection in privacy policies to reveal compliance issues. We u…
Nowadays privacy in the connected world is a big user's concern. The ubiquity of mobile devices permits billions of users browse the web at anytime, anywhere. Near Field Communication (NFC) appeared as a seamlessly and simply communication protocol between devices. Commercial services such as Android Pay, and Apple Pay offer contactless payment methods that are spreading in more and more scenarios. However, we take risks while using NFC on Android devices, we can be hacked, and our privacy can be affected. In this paper we study the current vulnerabilities in the NFC-Android ecosystem. We cond…
The Android unrestricted application market, being of open source nature, has made it a popular platform for third-party applications reaching millions of smart devices in the world. This tremendous increase in applications with an extensive API that includes access to phone hardware, settings, and user data raises concerns regarding users privacy, as the information collected from the apps could be used for profiling purposes. In this respect, this paper focuses on the geolocation data and analyses five GPS applications to identify the privacy risks if no appropriate safeguards are present. O…
While many studies have looked at privacy properties of the Android and Google Play app ecosystem, comparatively much less is known about iOS and the Apple App Store, the most widely used ecosystem in the US. At the same time, there is increasing competition around privacy between these smartphone operating system providers. In this paper, we present a study of 24k Android and iOS apps from 2020 along several dimensions relating to user privacy. We find that third-party tracking and the sharing of unique user identifiers was widespread in apps from both ecosystems, even in apps aimed at childr…
In the age of ubiquitous technologies, security- and privacy-focused choices have turned out to be a significant concern for individuals and organizations. Risks of such pervasive technologies are extensive and often misaligned with user risk perception, thus failing to help users in taking privacy-aware decisions. Researchers usually try to find solutions for coherently extending trust into our often inscrutable electronic networked environment. To enable security- and privacy-focused decision-making, we mainly focused on the realm of the mobile marketplace, examining how risk indicators can …
Android users are increasingly concerned with the privacy of their data and security of their devices. To improve the security awareness of users, recent automatic techniques produce security-centric descriptions by performing program analysis. However, the generated text does not always address users' concerns as they are generally too technical to be understood by ordinary users. Moreover, different users have varied linguistic preferences, which do not match the text. Motivated by this challenge, we develop an innovative scheme to help users avoid malware and privacy-breaching apps by gener…
As privacy features in Android operating system improve, privacy-invasive apps may gradually shift their focus to non-standard and covert channels for leaking private user/device information. Such leaks also remain largely undetected by state-of-the-art privacy analysis tools, which are very effective in uncovering privacy exposures via regular HTTP and HTTPS channels. In this study, we design and implement, ThirdEye, to significantly extend the visibility of current privacy analysis tools, in terms of the exposures that happen across various non-standard and covert channels, i.e., via any pro…
The world is under an ongoing pandemic, COVID-19, of a scale last seen a century ago. Contact tracing is one of the most critical and highly effective tools for containing and breaking the chain of infections especially in the case of infectious respiratory diseases like COVID-19. Thanks to the technological progress in our times, we now have digital mobile applications like the Corona-Warn-App for digital contact tracing. However, due to the invasive nature of contact tracing, it is very important to preserve the privacy of the users. Privacy preservation is important for increasing trust in …
Apps on mobile phones manipulate all sorts of data, including sensitive data, leading to privacy-related concerns. Recent regulations like the European GDPR provide rules for the processing of personal and sensitive data, like that no such data may be leaked without the consent of the user. Researchers have proposed sophisticated approaches to track sensitive data within mobile apps, all of which rely on specific lists of sensitive source and sink API methods. The data flow analysis results greatly depend on these lists' quality. Previous approaches either used incomplete hand-written lists th…
Organizations often collect private data and release aggregate statistics for the public's benefit. If no steps toward preserving privacy are taken, adversaries may use released statistics to deduce unauthorized information about the individuals described in the private dataset. Differentially private algorithms address this challenge by slightly perturbing underlying statistics with noise, thereby mathematically limiting the amount of information that may be deduced from each data release. Properly calibrating these algorithms -- and in turn the disclosure risk for people described in the dat…
The number of Android smartphone and tablet users has experienced a rapid growth in the past few years and it raises users' awareness on the privacy and security of their mobile devices. The features of openness and extensibility make Android unique, attractive and competitive but meanwhile vulnerable to malicious attack. There are lots of users rooting their Android devices for some useful functions, which are not originally provided to developers and users, such as backup and taking screenshot. However, after observing the danger of rooting devices, the developers begin to look for other non…
Botnets have become a serious security threat not only to the Internet but also to the devices connected to it. Factors like the exponential growth of IoT, the COVID-19 pandemic that's sweeping the planet, and the ever-larger number of cyber-criminals who now have access to or have developed increasingly more sophisticated tools are incentivizing the growth of botnets in this domain. The recent outbreak of botnets like Dark Nexus (derived from Qbot and Mirai), Mukashi, LeetHozer, Hoaxcalls, etc. shows the alarming rate at which this threat is converging. The botnets have attributes that make t…
Ruhr University Bochum（波鸿鲁尔大学）；imec-COSIC KU Leuven（鲁汶大学imec-COSIC研究中心）
In this paper we present LiM ("Less is More"), a malware classification framework that leverages Federated Learning to detect and classify malicious apps in a privacy-respecting manner. Information about newly installed apps is kept locally on users' devices, so that the provider cannot infer which apps were installed by users. At the same time, input from all users is taken into account in the federated learning process and they all benefit from better classification performance. A key challenge of this setting is that users do not have access to the ground truth (i.e. they cannot correctly i…
The recent privacy leakage incidences and the more strict policy regulations demand a much higher standard of compliance for companies and mobile apps. However, such obligations also impose significant challenges on app developers for complying with these regulations that contain various perspectives, activities, and roles, especially for small companies and developers who are less experienced in this matter or with limited resources. To address these hurdles, we develop an automatic tool, NL2GDPR, which can generate policies from natural language descriptions from the developer while also ens…
Building automation systems (BAS) are interlinked networks of hardware and software, which monitor and control events in the buildings. One of the data communication protocols used in BAS is Building Automation and Control networking protocol (BACnet) which is an internationally adopted ISO standard for the communication between BAS devices. Although BAS focus on providing safety for inhabitants, decreasing the energy consumption of buildings and reducing their operational cost, their security suffers due to the inherent complexity of the modern day systems. The issues such as monitoring of BA…
The open-source nature of the Android OS makes it possible for manufacturers to ship custom versions of the OS along with a set of pre-installed apps, often for product differentiation. Some device vendors have recently come under scrutiny for potentially invasive private data collection practices and other potentially harmful or unwanted behavior of the pre-installed apps on their devices. Yet, the landscape of pre-installed software in Android has largely remained unexplored, particularly in terms of the security and privacy implications of such customizations. In this paper, we present the …
In recent years the PC has been replaced by mobile devices for many security sensitive operations, both from a privacy and a financial standpoint. While security mechanisms are deployed at various levels, these are frequently put under strain by previously unseen malware. An additional protection layer capable of novelty detection is therefore needed. In this work we propose SpotCheck, an anomaly detector intended to run on Android devices. It samples app executions and submits suspicious apps to more thorough processing by malware sandboxes. We compare Kernel Principal Component Analysis (KPC…
Virtualization is frequently used to isolate untrusted processes and control their access to sensitive resources. However, isolation usually carries a price in terms of less resource sharing and reduced inter-process communication. In an open architecture such as Android, this price and its impact on performance, usability, and transparency must be carefully considered. Although previous efforts in developing general-purpose isolation solutions have shown that some of these negative side effects can be mitigated, doing so involves overcoming significant design challenges by incorporating numer…
Hacettepe University（哈塞特佩大学）；Research Institute of Information and Language Processing（信息与语言处理研究所）；University of Wolverhampton（伍尔弗汉普顿大学）
Android is among the most targeted platform by attackers. While attackers are improving their techniques, traditional solutions based on static and dynamic analysis have been also evolving. In addition to the application code, Android applications have some metadata that could be useful for security analysis of applications. Unlike traditional application distribution mechanisms, Android applications are distributed centrally in mobile markets. Therefore, beside application packages, such markets contain app information provided by app developers and app users. The availability of such useful …
