Combining behavioural types with security analysis

Today's software systems are highly distributed and interconnected, and they increasingly rely on communication to achieve their goals; due to their societal importance, security and trustworthiness are crucial aspects for the correctness of these systems. Behavioural types, which extend data types by describing also the structured behaviour of programs, are a widely studied approach to the enforcement of correctness properties in communicating systems. This paper offers a unified overview of proposals based on behavioural types which are aimed at the analysis of security properties

An Approach Toward Implementing Continuous Security In Agile Environment

Traditionally, developers design software to accomplish a set of functions and then later add—or do not add—security measures, especially after the prevalence of the agile software development model. Consequently, there is an increased risk of security vulnerabilities that are introduced into the software in various stages of development. To avoid security vulnerabilities, there are many secure software development efforts in the directions of secure software development lifecycle process. The purpose of this thesis is to propose a software security assurance methodology and integrate it into the Msg Life organization’s development lifecycle based on security best practices that fulfill their needs in building secure software applications. Ultimately, the objective adhered to increasing the security maturity level according to the suggested security assurance roadmap and implemented partly in the context of this thesis.Tradicionalmente, os desenvolvedores projetam o software para realizar um conjunto de funções e, posteriormente, adicionam - ou não - medidas de segurança, especialmente após a prevalência do modelo de desenvolvimento ágil de software. Consequentemente, há um risco aumentado de vulnerabilidades de segurança que são introduzidas no software em vários estágios de desenvolvimento. Para evitar vulnerabilidades de segurança, existem muitos esforços no desenvolvimento de software nas direções dos processos do ciclo de vida desse mesmo software. O objetivo desta tese é propor uma metodologia de garantia de segurança de software e integrá-la ao ciclo de vida de desenvolvimento da Msg Life Company, com base nas melhores práticas de segurança que atendem às suas necessidades na criação de aplicativos de software seguros. Por fim, o objetivo aderiu ao aumento do nível de maturidade da segurança de acordo com o roteiro sugerido de garantia de segurança e implementado parcialmente no contexto desta tese

ReCon: Revealing and Controlling PII Leaks in Mobile Network Traffic

It is well known that apps running on mobile devices extensively track and leak users' personally identifiable information (PII); however, these users have little visibility into PII leaked through the network traffic generated by their devices, and have poor control over how, when and where that traffic is sent and handled by third parties. In this paper, we present the design, implementation, and evaluation of ReCon: a cross-platform system that reveals PII leaks and gives users control over them without requiring any special privileges or custom OSes. ReCon leverages machine learning to reveal potential PII leaks by inspecting network traffic, and provides a visualization tool to empower users with the ability to control these leaks via blocking or substitution of PII. We evaluate ReCon's effectiveness with measurements from controlled experiments using leaks from the 100 most popular iOS, Android, and Windows Phone apps, and via an IRB-approved user study with 92 participants. We show that ReCon is accurate, efficient, and identifies a wider range of PII than previous approaches.Comment: Please use MobiSys version when referencing this work: http://dl.acm.org/citation.cfm?id=2906392. 18 pages, recon.meddle.mob

“And all the pieces matter...” Hybrid Testing Methods for Android App's Privacy Analysis

Smartphones have become inherent to the every day life of billions of people worldwide, and they are used to perform activities such as gaming, interacting with our peers or working. While extremely useful, smartphone apps also have drawbacks, as they can affect the security and privacy of users. Android devices hold a lot of personal data from users, including their social circles (e.g., contacts), usage patterns (e.g., app usage and visited websites) and their physical location. Like in most software products, Android apps often include third-party code (Software Development Kits or SDKs) to include functionality in the app without the need to develop it in-house. Android apps and third-party components embedded in them are often interested in accessing such data, as the online ecosystem is dominated by data-driven business models and revenue streams like advertising. The research community has developed many methods and techniques for analyzing the privacy and security risks of mobile apps, mostly relying on two techniques: static code analysis and dynamic runtime analysis. Static analysis analyzes the code and other resources of an app to detect potential app behaviors. While this makes static analysis easier to scale, it has other drawbacks such as missing app behaviors when developers obfuscate the app’s code to avoid scrutiny. Furthermore, since static analysis only shows potential app behavior, this needs to be confirmed as it can also report false positives due to dead or legacy code. Dynamic analysis analyzes the apps at runtime to provide actual evidence of their behavior. However, these techniques are harder to scale as they need to be run on an instrumented device to collect runtime data. Similarly, there is a need to stimulate the app, simulating real inputs to examine as many code-paths as possible. While there are some automatic techniques to generate synthetic inputs, they have been shown to be insufficient. In this thesis, we explore the benefits of combining static and dynamic analysis techniques to complement each other and reduce their limitations. While most previous work has often relied on using these techniques in isolation, we combine their strengths in different and novel ways that allow us to further study different privacy issues on the Android ecosystem. Namely, we demonstrate the potential of combining these complementary methods to study three inter-related issues: • A regulatory analysis of parental control apps. We use a novel methodology that relies on easy-to-scale static analysis techniques to pin-point potential privacy issues and violations of current legislation by Android apps and their embedded SDKs. We rely on the results from our static analysis to inform the way in which we manually exercise the apps, maximizing our ability to obtain real evidence of these misbehaviors. We study 46 publicly available apps and find instances of data collection and sharing without consent and insecure network transmissions containing personal data. We also see that these apps fail to properly disclose these practices in their privacy policy. • A security analysis of the unauthorized access to permission-protected data without user consent. We use a novel technique that combines the strengths of static and dynamic analysis, by first comparing the data sent by applications at runtime with the permissions granted to each app in order to find instances of potential unauthorized access to permission protected data. Once we have discovered the apps that are accessing personal data without permission, we statically analyze their code in order to discover covert- and side-channels used by apps and SDKs to circumvent the permission system. This methodology allows us to discover apps using the MAC address as a surrogate for location data, two SDKs using the external storage as a covert-channel to share unique identifiers and an app using picture metadata to gain unauthorized access to location data. • A novel SDK detection methodology that relies on obtaining signals observed both in the app’s code and static resources and during its runtime behavior. Then, we rely on a tree structure together with a confidence based system to accurately detect SDK presence without the need of any a priory knowledge and with the ability to discern whether a given SDK is part of legacy or dead code. We prove that this novel methodology can discover third-party SDKs with more accuracy than state-of-the-art tools both on a set of purpose-built ground-truth apps and on a dataset of 5k publicly available apps. With these three case studies, we are able to highlight the benefits of combining static and dynamic analysis techniques for the study of the privacy and security guarantees and risks of Android apps and third-party SDKs. The use of these techniques in isolation would not have allowed us to deeply investigate these privacy issues, as we would lack the ability to provide real evidence of potential breaches of legislation, to pin-point the specific way in which apps are leveraging cover and side channels to break Android’s permission system or we would be unable to adapt to an ever-changing ecosystem of Android third-party companies.The works presented in this thesis were partially funded within the framework of the following projects and grants: • European Union’s Horizon 2020 Innovation Action program (Grant Agreement No. 786741, SMOOTH Project and Grant Agreement No. 101021377, TRUST AWARE Project). • Spanish Government ODIO NºPID2019-111429RB-C21/PID2019-111429RBC22. • The Spanish Data Protection Agency (AEPD) • AppCensus Inc.This work has been supported by IMDEA Networks InstitutePrograma de Doctorado en Ingeniería Telemática por la Universidad Carlos III de MadridPresidente: Srdjan Matic.- Secretario: Guillermo Suárez-Tangil.- Vocal: Ben Stoc

Open-TEE - An Open Virtual Trusted Execution Environment

Hardware-based Trusted Execution Environments (TEEs) are widely deployed in mobile devices. Yet their use has been limited primarily to applications developed by the device vendors. Recent standardization of TEE interfaces by GlobalPlatform (GP) promises to partially address this problem by enabling GP-compliant trusted applications to run on TEEs from different vendors. Nevertheless ordinary developers wishing to develop trusted applications face significant challenges. Access to hardware TEE interfaces are difficult to obtain without support from vendors. Tools and software needed to develop and debug trusted applications may be expensive or non-existent. In this paper, we describe Open-TEE, a virtual, hardware-independent TEE implemented in software. Open-TEE conforms to GP specifications. It allows developers to develop and debug trusted applications with the same tools they use for developing software in general. Once a trusted application is fully debugged, it can be compiled for any actual hardware TEE. Through performance measurements and a user study we demonstrate that Open-TEE is efficient and easy to use. We have made Open- TEE freely available as open source.Comment: Author's version of article to appear in 14th IEEE International Conference on Trust, Security and Privacy in Computing and Communications, TrustCom 2015, Helsinki, Finland, August 20-22, 201

After Over-Privileged Permissions: Using Technology and Design to Create Legal Compliance

Consumers in the mobile ecosystem can putatively protect their privacy with the use of application permissions. However, this requires the mobile device owners to understand permissions and their privacy implications. Yet, few consumers appreciate the nature of permissions within the mobile ecosystem, often failing to appreciate the privacy permissions that are altered when updating an app. Even more concerning is the lack of understanding of the wide use of third-party libraries, most which are installed with automatic permissions, that is permissions that must be granted to allow the application to function appropriately. Unsurprisingly, many of these third-party permissions violate consumers’ privacy expectations and thereby, become “over-privileged” to the user. Consequently, an obscurity of privacy expectations between what is practiced by the private sector and what is deemed appropriate by the public sector is exhibited. Despite the growing attention given to privacy in the mobile ecosystem, legal literature has largely ignored the implications of mobile permissions. This article seeks to address this omission by analyzing the impacts of mobile permissions and the privacy harms experienced by consumers of mobile applications. The authors call for the review of industry self-regulation and the overreliance upon simple notice and consent. Instead, the authors set out a plan for greater attention to be paid to socio-technical solutions, focusing on better privacy protections and technology embedded within the automatic permission-based application ecosystem