Virtualization is the backbone of cloud infrastructures. Its core subsystems include hypervisors and virtual machine monitors (VMMs). They ensure the isolation and security of co-existent virtual machines (VMs) running on the same physical machine. Traditionally, driver domains -- isolated VMs in a hypervisor such as Xen that run device drivers -- use general-purpose full-featured OSs (e.g., Linux), which has a large attack surface, evident by the increasing number of their common vulnerabilities and exposures (CVEs). We argue for using the unikernel operating system (OS) model for driver domains. In this model, a single application is statically compiled together with the minimum necessary kernel code and libraries to produce a single address-space image, reducing code size by as much as one order of magnitude, which yields security benefits. We develop a driver domain OS, called Kite, using NetBSD OS's rumprun unikernel. Since rumprun is directly based on NetBSD's code, it allows us to leverage NetBSD's large collection of device drivers, including highly specialized ones such as Amazon ENA. Kite's design overcomes several significant challenges including Xen's limited para-virtualization (PV) I/O support in rumprun, lack of Xen backend drivers which prevents rumprun from being used as a driver domain OS, and NetBSD's lack of support for running driver domains in Xen. We instantiate Kite for the two most widely used I/O devices, storage and network, by designing and implementing the storage backend and network backend drivers. Our evaluations reveal that Kite achieves competitive performance to a Linux-based driver domain while using 10x fewer system calls, mitigates a set of CVEs, and retains all the benefits of unikernels including a reduced number of return-oriented programming (ROP) gadgets and advanced gadget-related metrics. General-purpose VMMs include a large number of components that may not be used in many VM configurations, resulting in a large attack surface. In addition, they lack intra-VMM isolation, which degrades security: vulnerabilities in one VMM component can be exploited to compromise other components or that of the host OS and other VMs (by privilege escalation). To mitigate these security challenges, we develop principles for VMM compartmentalization and specialization. We construct a prototype, called Redwood, embodying those principles. Redwood is built by extending Cloud Hypervisor and compartmentalizes thirteen critical components (i.e., virtual I/O devices) using Intel MPK, a hardware primitive available in Intel CPUs. Redwood has fifteen fine-grained modules, each representing a single feature, which increases its configurability and flexibility. Our evaluations reveal that Redwood is as performant as the baseline Cloud Hypervisor, has a 50% smaller VMM image size and 50% fewer ROP gadgets, and is resilient to an array of CVEs. I/O acceleration architectures, such as Data Plane Development Kit (DPDK) enhance VM performance by moving the data plane from the VMM to a separate userspace application. Since the VMM must share its VMs' sensitive information with accelerated applications, it can potentially degrade security. The dissertation's final contribution is the compartmentalization of a VM's sensitive data within an accelerated application using the Intel MPK hardware primitive. Our evaluations reveal that the technique does not cause any degradation in I/O performance and mitigates potential attacks and a class of CVEs. / Doctor of Philosophy / Instead of using software on a local device like a laptop or a mobile phone, consumers can access the same services from a remote high-end computer through high-speed Internet. This paradigm shift in computing is enabled by a remote computing infrastructure known as the "cloud,'' wherein networked server computers are deployed to execute third-party applications, often untrusted. Multiple applications are consolidated on the same server to save computer resources, but this can compromise security: a malicious application can steal co-existent applications' sensitive data. To enable resource consolidation and mitigate security attacks, applications are executed using a virtual machine (VM) -- an abstract machine that runs its own operating system (OS). Multiple VMs run on a single physical machine using two software systems: hypervisor and virtual machine monitor (VMM). They ensure that VMs are spatially isolated from each other, localizing security attacks. This dissertation focuses on enhancing the security of hypervisors and VMMs. The hypervisor and VMM have multiple responsibilities toward supporting the OS running on the physical computer and VMs. The OS runs software called device drivers, which communicate with input-output (I/O) hardware such as network and storage devices. Device drivers, usually written by third-party and I/O device manufacturers, are highly vulnerable to security attacks. To mitigate such attacks, device drivers are often run inside special VMs, called driver domains. State-of-the-art driver domains use a general-purpose full-featured OS such as Linux, which has a large code base (in the tens of millions of lines of code) and thus, a large attack surface. To address this security challenge, the dissertation proposes using lightweight, single-purpose VMs called unikernels, as driver domain OSs. Their code size is smaller than that of full-featured OSs by as much as one order of magnitude, which yields security benefits. We design and develop a unikernel-based driver domain, called Kite, for network and storage I/O devices. Kite uses NetBSD OS's rumprun unikernel for creating a driver domain OS. Using rumprun unikernel as a driver domain OS requires overcoming many technical challenges including a lack of support in a popular hypervisor such as Xen for performing I/O operations and communicating with rumprun, among others. Kite's design overcomes these challenges. Our empirical studies reveal that Kite is ten times less likely to be affected by future attacks and ten times faster to start than existing solutions for driver domains. At the same time, Kite domains match the performance of state-of-the-art driver domain OSs such as Linux. The hypervisor and VMM are responsible for creating VMs and providing resources such as memory, processing power, and hardware device access. Existing VMMs are designed to be versatile. Thus, they include a large number of components that may not be used in many VM configurations, resulting in a large attack surface. In addition, VMM components are not well spatially separated from each other. Thus, vulnerabilities in one component can be exploited to compromise other components. To address these security challenges, the dissertation proposes a set of principles for i) customizing a VMM for each VM's needs, instead of using one VMM for all VMs, and ii) strongly isolating VMM components from each other. We realize these principles in a prototype implementation called Redwood. Redwood is highly configurable and separates critical I/O components from each other using a hardware primitive. Our evaluations reveal that Redwood significantly reduces the VMM's size and VMM's vulnerabilities while maintaining performance. To enhance VM performance, I/O acceleration software is often used that eliminates communication overheads in the VMM. To do so, the VMM must share VMs' sensitive information with accelerated applications, which can potentially degrade security. The dissertation's final contribution is a technique that strongly isolates and limits access to sensitive information in the application using a hardware primitive. Our evaluations reveal that the technique improves security by localizing attacks without sacrificing performance.

The thesis deals with the topic of complexity of current IT. As a result, the consolidation of servers using virtualization is the answer to permanently growing complexity of server infrastructure. The thesis summarizes the basic aspects of this issue, compares the contributions and tries to analyze problems which can emerge. Further, it points a way of consolidation journey, compares different types of virtualization and elaborates the contributions of virtualization for corporate IS/ICT and its flexibility of solution. It analyzes present state of the market with virtualization tools, describes and compares some products of the market key players and analyzes the new opportunities for virtualization, e. g. the virtual desktop infrastructure. At the end, it suggests an approach for consolidated project solution in practice and tries to show some basic steps which should not be omitted. Besides the complex view to the topic, the thesis also presents the contributions, risks and questions to be raised and, at least partly, answers these questions.

Camera-on-a-chip systems have tried to include carefully chosen signal processing units for better functionality, performance and also to broaden the applications they can be used for. Image processing sensors have been possible due advances in CMOS active pixel sensors (APS) and neuromorphic focal plane imagers. Some of the advantages of these systems are compact size, high speed and parallelism, low power dissipation, and dense system integration. One can envision using these chips for portable and inexpensive video cameras on hand-held devices like personal digital assistants (PDA) or cell-phones In neuromorphic modeling of the retina it would be very nice to have processing capabilities at the focal plane while retaining the density of typical APS imager designs. Unfortunately, these two goals have been mostly incompatible. We introduce our MAtrix Transform Imager Architecture (MATIA) that uses analog floating--gate devices to make it possible to have computational imagers with high pixel densities. The core imager performs computations at the pixel plane, but still has a fill-factor of 46 percent - comparable to the high fill-factors of APS imagers. The processing is performed continuously on the image via programmable matrix operations that can operate on the entire image or blocks within the image. The resulting data-flow architecture can directly perform all kinds of block matrix image transforms. Since the imager operates in the subthreshold region and thus has low power consumption, this architecture can be used as a low-power front end for any system that utilizes these computations. Various compression algorithms (e.g. JPEG), that use block matrix transforms, can be implemented using this architecture. Since MATIA can be used for gradient computations, cheap image tracking devices can be implemented using this architecture. Other applications of this architecture can range from stand-alone universal transform imager systems to systems that can compute stereoscopic depth.

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Memristor is a novel passive electronic device and a promising candidate for new generation non-volatile memory and analog computing. Analog computing based on memristors has been explored in this study. Due to the lack of commercial electrical testing instruments for those emerging devices and crossbar arrays, we have designed and built testing circuits to implement analog and parallel computing operations. With the setup developed in this study, we have successfully demonstrated image processing functions utilizing large memristor crossbar arrays. We further designed and experimentally demonstrated the first memristor based field programmable analog array (FPAA), which was successfully configured for audio equalizer and frequency classifier demonstration as exemplary applications of such memristive FPAA (memFPAA).