Security-centric ranking algorithm and two privacy scores to mitigate intrusive apps

Smartphone users are constantly facing the risks of losing their private information to third-party mobile applications. Studies have revealed that the vast majority of users either do not pay attention to privacy or unable to comprehend privacy messages. Developers though have exploited this fact by asking users to grant their apps an enormous number of permissions. In this article, we propose and evaluate a new security-centric ranking algorithm built on top of the Elasticsearch engine to help users evade such apps. The algorithm calculates an intrusiveness score for an app based on its requested permissions, received system actions, and users' privacy preferences. As such, we further propose a new approach to capture these preferences. We evaluate the ranking algorithm using a million Android applications, contextual data and APK files, that we collect from the Google Play store. The results show that the scoring and reranking steps add minor overhead. Moreover, participants of the user studies gave positive feedback for the ranking algorithm and the privacy preferences solicitation approach. These results suggest that our proposed system would definitely protect the privacy of mobile users and pushes developers into requesting least amount of privileges. Still, there are many risks that endanger the users' privacy

Measuring and Characterizing (mis)compliance of the Android permission system

Within the Android mobile operating system, Android permissions act as a system of safeguards designed to restrict access to potentially sensitive data and privileged components. Multiple research studies indicate flaws and limitations of the Android permission system, prompting Google to implement a more regulated and fine-grained permission model. In spite of its newly-introduced complexity, misgranted permissions continue to present a significant risk to users. We present research on theoretical and practical misuse of permissions using our methodology that leverages unified permissions and call mappings. To guide the automated evaluation of permission use and compliance in Android apps, we develop PChecker, a tool that reports permissions requested by and granted to Android devices. We evaluate four versions of the Android Open Source Project code (major versions 10--13) and shed light on the prevalence of discrepancies between the official Android guidelines for permissions and their implementation in the Android platform source code. We use PChecker to analyze the permission use of 3,681 Android apps showing the common prevalence and occasional severity of non-compliance in real-world scenarios

A Software Vulnerabilities Odysseus: Analysis, Detection, and Mitigation

Programming has become central in the development of human activities while not being immune to defaults, or bugs. Developers have developed specific methods and sequences of tests that they implement to prevent these bugs from being deployed in releases. Nonetheless, not all cases can be thought through beforehand, and automation presents limits the community attempts to overcome. As a consequence, not all bugs can be caught. These defaults are causing particular concerns in case bugs can be exploited to breach the program’s security policy. They are then called vulnerabilities and provide specific actors with undesired access to the resources a program manages. It damages the trust in the program and in its developers, and may eventually impact the adoption of the program. Hence, to attribute a specific attention to vulnerabilities appears as a natural outcome. In this regard, this PhD work targets the following three challenges: (1) The research community references those vulnerabilities, categorises them, reports and ranks their impact. As a result, analysts can learn from past vulnerabilities in specific programs and figure out new ideas to counter them. Nonetheless, the resulting quality of the lessons and the usefulness of ensuing solutions depend on the quality and the consistency of the information provided in the reports. (2) New methods to detect vulnerabilities can emerge among the teachings this monitoring provides. With responsible reporting, these detection methods can provide hardening of the programs we rely on. Additionally, in a context of computer perfor- mance gain, machine learning algorithms are increasingly adopted, providing engaging promises. (3) If some of these promises can be fulfilled, not all are not reachable today. Therefore a complementary strategy needs to be adopted while vulnerabilities evade detection up to public releases. Instead of preventing their introduction, programs can be hardened to scale down their exploitability. Increasing the complexity to exploit or lowering the impact below specific thresholds makes the presence of vulnerabilities an affordable risk for the feature provided. The history of programming development encloses the experimentation and the adoption of so-called defence mechanisms. Their goals and performances can be diverse, but their implementation in worldwide adopted programs and systems (such as the Android Open Source Project) acknowledges their pivotal position. To face these challenges, we provide the following contributions: • We provide a manual categorisation of the vulnerabilities of the worldwide adopted Android Open Source Project up to June 2020. Clarifying to adopt a vulnera- bility analysis provides consistency in the resulting data set. It facilitates the explainability of the analyses and sets up for the updatability of the resulting set of vulnerabilities. Based on this analysis, we study the evolution of AOSP’s vulnerabilities. We explore the different temporal evolutions of the vulnerabilities affecting the system for their severity, the type of vulnerability, and we provide a focus on memory corruption-related vulnerabilities. • We undertake the replication of a machine-learning based detection algorithms that, besides being part of the state-of-the-art and referenced to by ensuing works, was not available. Named VCCFinder, this algorithm implements a Support- Vector Machine and bases its training on Vulnerability-Contributing Commits and related patches for C and C++ code. Not in capacity to achieve analogous performances to the original article, we explore parameters and algorithms, and attempt to overcome the challenge provided by the over-population of unlabeled entries in the data set. We provide the community with our code and results as a replicable baseline for further improvement. • We eventually list the defence mechanisms that the Android Open Source Project incrementally implements, and we discuss how it sometimes answers comments the community addressed to the project’s developers. We further verify the extent to which specific memory corruption defence mechanisms were implemented in the binaries of different versions of Android (from API-level 10 to 28). We eventually confront the evolution of memory corruption-related vulnerabilities with the implementation timeline of related defence mechanisms

Predicting App Intrusiveness Using LSTM Networks to Analyze App Descriptions

Mobile apps are at the center of everyone's daily lives and users give them access to their intimate personal data. Some apps collect more information than they need to perform their job. These apps are called intrusive, and can represent not only a privacy issue, but a security problem for their users. Therefore, it is important to develop methods for figuring out how much an app can detect and collect from its users, and whether that access is in line with their privacy expectations. Several methods have been devised to determine app intrusiveness, a measure that represents how much an app's data collection deviates from its basic needs. This number, called intrusiveness or privacy score, can guide a user in the process of identifying apps that gather too much personal information. Some of the methods to calculate intrusiveness include analysis of app descriptions and conformity with their programmed behavior. However, most of the existing approaches depend on static analysis that is quite challenging and mandates access to the binaries or source code. This thesis proposes a novel method to determine whether an app is intrusive based on its description, which can allow users to make decisions before downloading. More specifically, we used a Long Short-Term Memory (\ac{LSTM}) network to analyze the descriptions, along with a Multi-Layer Perceptron (\ac{MLP}) network to process metadata provided by other app features. The results show that this combined network structure achieved 79\% accuracy in training and 74\% accuracy for validation, with 840,000 samples and a 75/25 split between training and validation. Our findings indicate that not only it is possible to use the description and other information available from the app store to predict the intrusiveness of an app, but also that the network required to do the job is fairly small.Master of ScienceComputer ScienceUniversity of Michigan-Flinthttp://deepblue.lib.umich.edu/bitstream/2027.42/167243/1/Montenegro2021.pdfDescription of Montenegro2021.pdf : thesi

Proceedings of The Multi-Agent Logics, Languages, and Organisations Federated Workshops (MALLOW 2010)

http://ceur-ws.org/Vol-627/allproceedings.pdfInternational audienceMALLOW-2010 is a third edition of a series initiated in 2007 in Durham, and pursued in 2009 in Turin. The objective, as initially stated, is to "provide a venue where: the cost of participation was minimum; participants were able to attend various workshops, so fostering collaboration and cross-fertilization; there was a friendly atmosphere and plenty of time for networking, by maximizing the time participants spent together"

Open Source Law, Policy and Practice

This book examines various policies, including the legal and commercial aspects of the Open Source phenomenon. Here, ‘Open Source’ is adopted as convenient shorthand for a collection of diverse users and communities, whose differences can be as great as their similarities. The common thread is their reliance on, and use of, law and legal mechanisms to govern the source code they write, use, and distribute. The central fact of open source is that maintaining control over source code relies on the existence and efficacy of intellectual property (‘IP’) laws, particularly copyright law. Copyright law is the primary statutory tool that achieves the end of openness, although implemented through private law arrangements at varying points within the software supply chain. This dependent relationship is itself a cause of concern for some philosophically in favour of ‘open’, with some predicting (or hoping) that the free software movement will bring about the end of copyright as a means for protecting software

Open Source Law, Policy and Practice

This book examines various policies, including the legal and commercial aspects of the Open Source phenomenon. Here, ‘Open Source’ is adopted as convenient shorthand for a collection of diverse users and communities, whose differences can be as great as their similarities. The common thread is their reliance on, and use of, law and legal mechanisms to govern the source code they write, use, and distribute. The central fact of open source is that maintaining control over source code relies on the existence and efficacy of intellectual property (‘IP’) laws, particularly copyright law. Copyright law is the primary statutory tool that achieves the end of openness, although implemented through private law arrangements at varying points within the software supply chain. This dependent relationship is itself a cause of concern for some philosophically in favour of ‘open’, with some predicting (or hoping) that the free software movement will bring about the end of copyright as a means for protecting software

Combining SOA and BPM Technologies for Cross-System Process Automation

This paper summarizes the results of an industry case study that introduced a cross-system business process automation solution based on a combination of SOA and BPM standard technologies (i.e., BPMN, BPEL, WSDL). Besides discussing major weaknesses of the existing, custom-built, solution and comparing them against experiences with the developed prototype, the paper presents a course of action for transforming the current solution into the proposed solution. This includes a general approach, consisting of four distinct steps, as well as specific action items that are to be performed for every step. The discussion also covers language and tool support and challenges arising from the transformation