A Compiler and Runtime Infrastructure for Automatic Program Distribution

This paper presents the design and the implementation of a compiler and runtime infrastructure for automatic program distribution. We are building a research infrastructure that enables experimentation with various program partitioning and mapping strategies and the study of automatic distribution's effect on resource consumption (e.g., CPU, memory, communication). Since many optimization techniques are faced with conflicting optimization targets (e.g., memory and communication), we believe that it is important to be able to study their interaction. We present a set of techniques that enable flexible resource modeling and program distribution. These are: dependence analysis, weighted graph partitioning, code and communication generation, and profiling. We have developed these ideas in the context of the Java language. We present in detail the design and implementation of each of the techniques as part of our compiler and runtime infrastructure. Then, we evaluate our design and present preliminary experimental data for each component, as well as for the entire system

JooFlux: Hijacking Java 7 InvokeDynamic To Support Live Code Modifications

Changing functional and non-functional software implementation at runtime is useful and even sometimes critical both in development and production environments. JooFlux is a JVM agent that allows both the dynamic replacement of method implementations and the application of aspect advices. It works by doing bytecode transformation to take advantage of the new invokedynamic instruction added in Java SE 7 to help implementing dynamic languages for the JVM. JooFlux can be managed using a JMX agent so as to operate dynamic modifications at runtime, without resorting to a dedicated domain-specific language. We compared JooFlux with existing AOP platforms and dynamic languages. Results demonstrate that JooFlux performances are close to the Java ones --- with most of the time a marginal overhead, and sometimes a gain --- where AOP platforms and dynamic languages present significant overheads. This paves the way for interesting future evolutions and applications of JooFlux

Towards Principled Dynamic Analysis on Android

The vast amount of information and services accessible through mobile handsets running the Android operating system has led to the tight integration of such devices into our daily routines. However, their capability to capture and operate upon user data provides an unprecedented insight into our private lives that needs to be properly protected, which demands for comprehensive analysis and thorough testing. While dynamic analysis has been applied to these problems in the past, the corresponding literature consists of scattered work that often specializes on sub-problems and keeps on re-inventing the wheel, thus lacking a structured approach. To overcome this unsatisfactory situation, this dissertation introduces two major systems that advance the state-of-the-art of dynamically analyzing the Android platform. First, we introduce a novel, fine-grained and non-intrusive compiler-based instrumentation framework that allows for precise and high-performance modification of Android apps and system components. Second, we present a unifying dynamic analysis platform with a special focus on Android’s middleware in order to overcome the common challenges we identified from related work. Together, these two systems allow for a more principled approach for dynamic analysis on Android that enables comparability and composability of both existing and future work.Die enorme Menge an Informationen und Diensten, die durch mobile Endgeräte mit dem Android Betriebssystem zugänglich gemacht werden, hat zu einer verstärkten Einbindung dieser Geräte in unseren Alltag geführt. Gleichzeitig erlauben die dabei verarbeiteten Benutzerdaten einen beispiellosen Einblick in unser Privatleben. Diese Informationen müssen adäquat geschützt werden, was umfassender Analysen und gründlicher Prüfung bedarf. Dynamische Analysetechniken, die in der Vergangenheit hier bereits angewandt wurden, fokussieren sich oftmals auf Teilprobleme und reimplementieren regelmäßig bereits existierende Komponenten statt einen strukturierten Ansatz zu verfolgen. Zur Überwindung dieser unbefriedigenden Situation stellt diese Dissertation zwei Systeme vor, die den Stand der Technik dynamischer Analyse der Android Plattform erweitern. Zunächst präsentieren wir ein compilerbasiertes, feingranulares und nur geringfügig eingreifendes Instrumentierungsframework für präzises und performantes Modifizieren von Android Apps und Systemkomponenten. Anschließend führen wir eine auf die Android Middleware spezialisierte Plattform zur Vereinheitlichung von dynamischer Analyse ein, um die aus existierenden Arbeiten extrahierten, gemeinsamen Herausforderungen in diesem Gebiet zu überwinden. Zusammen erlauben diese beiden Systeme einen prinzipienorientierten Ansatz zur dynamischen Analyse, welcher den Vergleich und die Zusammenführung existierender und zukünftiger Arbeiten ermöglicht

Fast dynamic deployment adaptation for mobile devices

Mobile devices that are limited in terms of CPU power, memory or battery power are only capable of executing simple applications. To be able to run advanced applications we introduce a framework to split up the application and execute parts on a remote server. In order to dynamically adapt the deployment at runtime, techniques are presented to keep the migration time as low as possible and to prevent performance loss while migrating. Also methods are presented and evaluated to cope with applications generating a variable load, which can lead to an unstable system

Retrofitting privacy controls to stock Android

Android ist nicht nur das beliebteste Betriebssystem für mobile Endgeräte, sondern auch ein ein attraktives Ziel für Angreifer. Um diesen zu begegnen, nutzt Androids Sicherheitskonzept App-Isolation und Zugangskontrolle zu kritischen Systemressourcen. Nutzer haben dabei aber nur wenige Optionen, App-Berechtigungen gemäß ihrer Bedürfnisse einzuschränken, sondern die Entwickler entscheiden über zu gewährende Berechtigungen. Androids Sicherheitsmodell kann zudem nicht durch Dritte angepasst werden, so dass Nutzer zum Schutz ihrer Privatsphäre auf die Gerätehersteller angewiesen sind. Diese Dissertation präsentiert einen Ansatz, Android mit umfassenden Privatsphäreeinstellungen nachzurüsten. Dabei geht es konkret um Techniken, die ohne Modifikationen des Betriebssystems oder Zugriff auf Root-Rechte auf regulären Android-Geräten eingesetzt werden können. Der erste Teil dieser Arbeit etabliert Techniken zur Durchsetzung von Sicherheitsrichtlinien für Apps mithilfe von inlined reference monitors. Dieser Ansatz wird durch eine neue Technik für dynamic method hook injection in Androids Java VM erweitert. Schließlich wird ein System eingeführt, das prozessbasierte privilege separation nutzt, um eine virtualisierte App-Umgebung zu schaffen, um auch komplexe Sicherheitsrichtlinien durchzusetzen. Eine systematische Evaluation unseres Ansatzes konnte seine praktische Anwendbarkeit nachweisen und mehr als eine Million Downloads unserer Lösung zeigen den Bedarf an praxisgerechten Werkzeugen zum Schutz der Privatsphäre.Android is the most popular operating system for mobile devices, making it a prime target for attackers. To counter these, Android’s security concept uses app isolation and access control to critical system resources. However, Android gives users only limited options to restrict app permissions according to their privacy preferences but instead lets developers dictate the permissions users must grant. Moreover, Android’s security model is not designed to be customizable by third-party developers, forcing users to rely on device manufacturers to address their privacy concerns. This thesis presents a line of work that retrofits comprehensive privacy controls to the Android OS to put the user back in charge of their device. It focuses on developing techniques that can be deployed to stock Android devices without firmware modifications or root privileges. The first part of this dissertation establishes fundamental policy enforcement on thirdparty apps using inlined reference monitors to enhance Android’s permission system. This approach is then refined by introducing a novel technique for dynamic method hook injection on Android’s Java VM. Finally, we present a system that leverages process-based privilege separation to provide a virtualized application environment that supports the enforcement of complex security policies. A systematic evaluation of our approach demonstrates its practical applicability, and over one million downloads of our solution confirm user demand for privacy-enhancing tools

SensorCloud: Towards the Interdisciplinary Development of a Trustworthy Platform for Globally Interconnected Sensors and Actuators

Although Cloud Computing promises to lower IT costs and increase users' productivity in everyday life, the unattractive aspect of this new technology is that the user no longer owns all the devices which process personal data. To lower scepticism, the project SensorCloud investigates techniques to understand and compensate these adoption barriers in a scenario consisting of cloud applications that utilize sensors and actuators placed in private places. This work provides an interdisciplinary overview of the social and technical core research challenges for the trustworthy integration of sensor and actuator devices with the Cloud Computing paradigm. Most importantly, these challenges include i) ease of development, ii) security and privacy, and iii) social dimensions of a cloud-based system which integrates into private life. When these challenges are tackled in the development of future cloud systems, the attractiveness of new use cases in a sensor-enabled world will considerably be increased for users who currently do not trust the Cloud.Comment: 14 pages, 3 figures, published as technical report of the Department of Computer Science of RWTH Aachen Universit