Doctor of Philosophy

dissertationA modern software system is a composition of parts that are themselves highly complex: operating systems, middleware, libraries, servers, and so on. In principle, compositionality of interfaces means that we can understand any given module independently of the internal workings of other parts. In practice, however, abstractions are leaky, and with every generation, modern software systems grow in complexity. Traditional ways of understanding failures, explaining anomalous executions, and analyzing performance are reaching their limits in the face of emergent behavior, unrepeatability, cross-component execution, software aging, and adversarial changes to the system at run time. Deterministic systems analysis has a potential to change the way we analyze and debug software systems. Recorded once, the execution of the system becomes an independent artifact, which can be analyzed offline. The availability of the complete system state, the guaranteed behavior of re-execution, and the absence of limitations on the run-time complexity of analysis collectively enable the deep, iterative, and automatic exploration of the dynamic properties of the system. This work creates a foundation for making deterministic replay a ubiquitous system analysis tool. It defines design and engineering principles for building fast and practical replay machines capable of capturing complete execution of the entire operating system with an overhead of several percents, on a realistic workload, and with minimal installation costs. To enable an intuitive interface of constructing replay analysis tools, this work implements a powerful virtual machine introspection layer that enables an analysis algorithm to be programmed against the state of the recorded system through familiar terms of source-level variable and type names. To support performance analysis, the replay engine provides a faithful performance model of the original execution during replay

High-Fidelity Provenance:Exploring the Intersection of Provenance and Security

In the past 25 years, the World Wide Web has disrupted the way news are disseminated and consumed. However, the euphoria for the democratization of news publishing was soon followed by scepticism, as a new phenomenon emerged: fake news. With no gatekeepers to vouch for it, the veracity of the information served over the World Wide Web became a major public concern. The Reuters Digital News Report 2020 cites that in at least half of the EU member countries, 50% or more of the population is concerned about online fake news. To help address the problem of trust on information communi- cated over the World Wide Web, it has been proposed to also make available the provenance metadata of the information. Similar to artwork provenance, this would include a detailed track of how the information was created, updated and propagated to produce the result we read, as well as what agents—human or software—were involved in the process. However, keeping track of provenance information is a non-trivial task. Current approaches, are often of limited scope and may require modifying existing applications to also generate provenance information along with thei regular output. This thesis explores how provenance can be automatically tracked in an application-agnostic manner, without having to modify the individual applications. We frame provenance capture as a data flow analysis problem and explore the use of dynamic taint analysis in this context. Our work shows that this appoach improves on the quality of provenance captured compared to traditonal approaches, yielding what we term as high-fidelity provenance. We explore the performance cost of this approach and use deterministic record and replay to bring it down to a more practical level. Furthermore, we create and present the tooling necessary for the expanding the use of using deterministic record and replay for provenance analysis. The thesis concludes with an application of high-fidelity provenance as a tool for state-of-the art offensive security analysis, based on the intuition that software too can be misguided by "fake news". This demonstrates that the potential uses of high-fidelity provenance for security extend beyond traditional forensics analysis

TOWARDS GENERIC SYSTEM OBSERVATION MANAGEMENT

Едно от най-големите предизвикателства на информатиката е да създава правилно работещи компютърни системи. За да се гарантира коректността на една система, по време на дизайн могат де се прилагат формални методи за моделиране и валидация. Този подход е за съжаление труден и скъп за приложение при мнозинството компютърни системи. Алтернативният подход е да се наблюдава и анализира поведението на системата по време на изпълнение след нейното създаване. В този доклад представям научната си работа по въпроса за наблюдение на копютърните системи. Предлагам един общ поглед на три основни страни на проблема: как трябва да се наблюдават компютърните системи, как се използват наблюденията при недетерминистични системи и как се работи по отворен, гъвкав и възпроизводим начин с наблюдения.One of the biggest challenges in computer science is to produce correct computer systems. One way of ensuring system correction is to use formal techniques to validate the system during its design. This approach is compulsory for critical systems but difficult and expensive for most computer systems. The alternative consists in observing and analyzing systems' behavior during execution. In this thesis, I present my research on system observation. I describe my contributions on generic observation mechanisms, on the use of observations for debugging nondeterministic systems and on the definition of an open, flexible and reproducible management of observations.Un des plus grands défis de l'informatique est de produire des systèmes corrects. Une manière d'assurer la correction des systèmes est d'utiliser des méthodes formelles de modélisation et de validation.Obligatoire dans le domaine des systèmes critiques, cette approche est difficile et coûteuse à mettre en place dans la plupart des systèmes informatiques.L'alternative est de vérifier le comportement des systèmes déjà développés en observant et analysant leur comportement à l'exécution.Ce mémoire présente mes contributions autour de l'observation des systèmes. Il discute de la définition de mécanismes génériques d'observation, de l'exploitation des observations pour le débogage de systèmes non déterministes et de la gestion ouverte, flexible et reproductible d'observations

New Container Architectures for Mobile, Drone, and Cloud Computing

Containers are increasingly used across many different types of computing to isolate and control apps while efficiently sharing computing resources. By using lightweight operating system virtualization, they can provide apps with a virtual computing abstraction while imposing minimal hardware requirements and a small footprint. My thesis is that new container architectures can provide additional functionality, better resource utilization, and stronger security for mobile, drone, and cloud computing. To demonstrate this, we introduce three new container architectures that enable new mobile app migration functionality, a new notion of virtual drones and efficient utilization of drone hardware, and stronger security for cloud computing by protecting containers against untrusted operating systems. First, we introduce Flux to support multi-surface apps, apps that seamlessly run across multiple user devices, through app migration. Flux introduces two key mechanisms to overcome device heterogeneity and residual dependencies associated with app migration to enable app migration. Selective Record/Adaptive Replay to record just those device-agnostic app calls that lead to the generation of app-specific device-dependent state in services and replay them on the target. Checkpoint/Restore in Android (CRIA) to transition an app into a state in which device-specific information the app contains can be safely discarded before checkpointing and restoring the app within a containerized environment on the new device. Second, we introduce AnDrone, a drone-as-a-service solution that makes drones accessible in the cloud. AnDrone provides a drone virtualization architecture to leverage the fact that computational costs are cheap compared to the operational and energy costs of putting a drone in the air. This enables multiple virtual drones to run simultaneously on the same physical drone at very little additional cost. To enable multiple virtual drones to run in an isolated and secure manner, each virtual drone runs its own containerized operating system instance. AnDrone introduces a new device container architecture, providing virtual drones with secure access to a full range of drone hardware devices, including sensors such as cameras and geofenced flight control. Finally, we introduce BlackBox, a new container architecture that provides fine-grain protection of application data confidentiality and integrity without the need to trust the operating system. BlackBox introduces a container security monitor, a small trusted computing base that creates separate and independent physical address spaces for each container, such that there is no direct information flow from container to operating system or other container physical address spaces. Containerized apps do not need to be modified, can still make full use of operating system services via system calls, yet their CPU and memory state are isolated and protected from other containers and the operating system

Circuits and Systems Advances in Near Threshold Computing

Modern society is witnessing a sea change in ubiquitous computing, in which people have embraced computing systems as an indispensable part of day-to-day existence. Computation, storage, and communication abilities of smartphones, for example, have undergone monumental changes over the past decade. However, global emphasis on creating and sustaining green environments is leading to a rapid and ongoing proliferation of edge computing systems and applications. As a broad spectrum of healthcare, home, and transport applications shift to the edge of the network, near-threshold computing (NTC) is emerging as one of the promising low-power computing platforms. An NTC device sets its supply voltage close to its threshold voltage, dramatically reducing the energy consumption. Despite showing substantial promise in terms of energy efficiency, NTC is yet to see widescale commercial adoption. This is because circuits and systems operating with NTC suffer from several problems, including increased sensitivity to process variation, reliability problems, performance degradation, and security vulnerabilities, to name a few. To realize its potential, we need designs, techniques, and solutions to overcome these challenges associated with NTC circuits and systems. The readers of this book will be able to familiarize themselves with recent advances in electronics systems, focusing on near-threshold computing

Virtualization with Limited Hardware Support

<p>In recent years, as mobile devices started to become an essential part of everyday computing, virtualization on mobile devices has begun to emerge as a solution for supporting multiple profiles on the same device. However, virtualization on mobile and embedded systems, and to a greater extent, on systems with limited hardware support for virtualization, often face different hardware environment than x86 platforms.</p><p>First of all, these platforms were usually equipped with CPUs that did not have hardware virtualization support. We propose a transparent and portable CPU virtualization solution for all types of CPUs that have hardware breakpoint functionality. We use a combination of the hardware breakpoint support and guest kernel control flow graph analysis to trap and emulate sensitive instructions.</p><p>Second, the traditional way of implementing record and replay which is an important feature of virtualization, cannot be implemented the same way on CPUs without hardware branch counters. We propose a record and replay implementation without using hardware branch counters on paravirtualized guests. We inspect guest virtual machine internal states to carefully rearrange recorded instructions during replay to achieve the same end result without having to literally repeat the same stream of instructions.</p><p>Third, these platforms are often equipped with storage systems with distinct I/O characteristics. SD card, for example, is a prevalent storage media on smartphones. We discuss the mismatch of I/O characteristics between SD card write speed characteristics and guest virtual machine workload characteristics using VMware Mobile Virtualization Platform as an example. We then propose a solution to bridge the gap and achieve efficient guest I/O when storing guest virtual disk images on SD cards.</p><p>This dissertation shows that it is possible to efficiently virtualize and provide advanced virtualization functionality to a range of systems without relying on x86 and PC specific virtualization technologies.</p>Dissertatio

SimuBoost: Scalable Parallelization of Functional System Simulation

Für das Sammeln detaillierter Laufzeitinformationen, wie Speicherzugriffsmustern, wird in der Betriebssystem- und Sicherheitsforschung häufig auf die funktionale Systemsimulation zurückgegriffen. Der Simulator führt dabei die zu untersuchende Arbeitslast in einer virtuellen Maschine (VM) aus, indem er schrittweise Instruktionen interpretiert oder derart übersetzt, sodass diese auf dem Zustand der VM arbeiten. Dieser Prozess ermöglicht es, eine umfangreiche Instrumentierung durchzuführen und so an Informationen zum Laufzeitverhalten zu gelangen, die auf einer physischen Maschine nicht zugänglich sind. Obwohl die funktionale Systemsimulation als mächtiges Werkzeug gilt, stellt die durch die Interpretation oder Übersetzung resultierende immense Ausführungsverlangsamung eine substanzielle Einschränkung des Verfahrens dar. Im Vergleich zu einer nativen Ausführung messen wir für QEMU eine 30-fache Verlangsamung, wobei die Aufzeichnung von Speicherzugriffen diesen Faktor verdoppelt. Mit Simulatoren, die umfangreichere Instrumentierungsmöglichkeiten mitbringen als QEMU, kann die Verlangsamung um eine Größenordnung höher ausfallen. Dies macht die funktionale Simulation für lang laufende, vernetzte oder interaktive Arbeitslasten uninteressant. Darüber hinaus erzeugt die Verlangsamung ein unrealistisches Zeitverhalten, sobald Aktivitäten außerhalb der VM (z. B. Ein-/Ausgabe) involviert sind. In dieser Arbeit stellen wir SimuBoost vor, eine Methode zur drastischen Beschleunigung funktionaler Systemsimulation. SimuBoost führt die zu untersuchende Arbeitslast zunächst in einer schnellen hardwaregestützten virtuellen Maschine aus. Dies ermöglicht volle Interaktivität mit Benutzern und Netzwerkgeräten. Während der Ausführung erstellt SimuBoost periodisch Abbilder der VM (engl. Checkpoints). Diese dienen als Ausgangspunkt für eine parallele Simulation, bei der jedes Intervall unabhängig simuliert und analysiert wird. Eine heterogene deterministische Wiederholung (engl. heterogeneous deterministic Replay) garantiert, dass in dieser Phase die vorherige hardwaregestützte Ausführung jedes Intervalls exakt reproduziert wird, einschließlich Interaktionen und realistischem Zeitverhalten. Unser Prototyp ist in der Lage, die Laufzeit einer funktionalen Systemsimulation deutlich zu reduzieren. Während mit herkömmlichen Verfahren für die Simulation des Bauprozesses eines modernen Linux über 5 Stunden benötigt werden, schließt SimuBoost die Simulation in nur 15 Minuten ab. Dies sind lediglich 16% mehr Zeit, als der Bau in einer schnellen hardwaregestützten VM in Anspruch nimmt. SimuBoost ist imstande, diese Geschwindigkeit auch bei voller Instrumentierung zur Aufzeichnung von Speicherzugriffen beizubehalten. Die vorliegende Arbeit ist das erste Projekt, welches das Konzept der Partitionierung und Parallelisierung der Ausführungszeit auf die interaktive Systemvirtualisierung in einer Weise anwendet, die eine sofortige parallele funktionale Simulation gestattet. Wir ergänzen die praktische Umsetzung mit einem mathematischen Modell zur formalen Beschreibung der Beschleunigungseigenschaften. Dies erlaubt es, für ein gegebenes Szenario die voraussichtliche parallele Simulationszeit zu prognostizieren und gibt eine Orientierung zur Wahl der optimalen Intervalllänge. Im Gegensatz zu bisherigen Arbeiten legt SimuBoost einen starken Fokus auf die Skalierbarkeit über die Grenzen eines einzelnen physischen Systems hinaus. Ein zentraler Schlüssel hierzu ist der Einsatz moderner Checkpointing-Technologien. Im Rahmen dieser Arbeit präsentieren wir zwei neuartige Methoden zur effizienten und effektiven Kompression von periodischen Systemabbildern

Record and vPlay: Problem Determination with Virtual Replay Across Heterogeneous Systems

Application down time is one of the major reasons for revenue loss in the modern enterprise. While aggressive release schedules cause frail software to be released, application failures occurring in the field cost millions to the technical support organizations in personnel time. Since developers usually don't have direct access to the field environment for a variety of privacy and security reasons, problems are reproduced, analyzed and fixed in very different lab environments. However, the complexity and diversity of application environments make it difficult to accurately replicate the production environment. The indiscriminate collection of data provided by the bug reports often overwhelm or even mislead the developer. A typical issue requires time consuming rounds of clarifications and interactions with the end user, even after which the issue may not manifest. This dissertation introduces vPlay, a software problem determination system which captures software bugs as they occur in the field into small and self-contained recordings, and allows them to be deterministically reproduced across different operating systems and heterogeneous environments. vPlay makes two key advances over the state of the art. First, the recorded bug can be reproduced in a completely different operating system environment without any kind of dependency on the source. vPlay packages up every piece of data necessary to correctly reproduce the bug on any stateless target machine in the developer environment, without the application, its binaries, and other support data. Second, the data captured by vPlay is small, typically amounting to a few megabytes. vPlay achieves this without requiring changes to the applications, base kernel or hardware. vPlay employs a recording mechanism which provides data level independence between the application and its source environment by adopting a state machine model of the application to capture every piece of state accessed by the application. vPlay minimizes the size of the recording through a new technique called partial checkpointing, to efficiently capture the partial intermediate state of the application required to replay just the last few moments of its execution prior to the failure. The recorded state is saved as a partial checkpoint along with metadata representing the information specific to the source environment, such as call- ing convention used for the system calls on the source system, to make it portable across operating systems. A partial checkpoint is loaded by a partial checkpoint loader, which itself is designed to be portable across different operating systems. Partial checkpointing is combined with a logging mechanism, which monitors the application to identify and record relevant accessed state for root cause analysis and to record application's nondeterministic events. vPlay introduces a new type of virtualization abstraction called vPlay Container, to natively replay an application built for one operating system on another. vPlay Container relies on the self-contained recording produced by vPlay to decouple the application from the target operating system environment in three key areas. The application is decoupled from (1) the address space and its content by transparently fulfilling its memory accesses, (2) the instructions and the processor MMU structures such as segment descriptor tables through a binary translation technique designed specifically for user application code, (3) the operating system interface and its services by abstracting the system call interface through emulation and replay. To facilitate root cause analysis, vPlay Container integrates with a standard debugger to enable the user to set breakpoints and single step the replayed execution of the application to examine the contents of variables and other program state at each source line. We have implemented a vPlay prototype which can record unmodified Linux applications and natively replay them on different versions of Linux as well as Windows. Experiments with several applications including Apache and MySQL show that vPlay can reproduce real bugs and be used in production with modest recording overhead