We present a flexible architecture for trusted computing, called Terra, that allows applications with a wide range of security requirements to run simultaneously on commodity hardware. Applications on Terra enjoy the semantics of running on a separate, dedicated, tamper-resistant hardware platform, while retaining the ability to run side-by-side with normal applications on a generalpurpose computing platform. Terra achieves this synthesis by use of a trusted virtual machine monitor (TVMM) that partitions a tamper-resistant hardware platform into multiple, isolated virtual machines (VM), providing the appearance of multiple boxes on a single, general-purpose platform. To each VM, the TVMM provides the semantics of either an “open box, ” i.e. a general-purpose hardware platform like today’s PCs and workstations, or a “closed box, ” an opaque special-purpose platform that protects the privacy and integrity of its contents like today’s game consoles and cellular phones. The software stack in each VM can be tailored from the hardware interface up to meet the security requirements of its application(s). The hardware and TVMM can act as a trusted party to allow closed-box VMs to cryptographically identify the software they run, i.e. what is in the box, to remote parties. We explore the strengths and limitations of this architecture by describing our prototype implementation and several applications that we developed for it.

Trusting a computer for a security-sensitive task (such as checking email or banking online) requires the user to know something about the computer’s state. We examine research on securely capturing a computer’s state, and consider the utility of this information both for improving security on the local computer (e.g., to convince the user that her computer is not infected with malware) and for communicating a remote computer’s state (e.g., to enable the user to check that a web server will adequately protect her data). Although the recent “Trusted Computing ” initiative has drawn both positive and negative attention to this area, we consider the older and broader topic of bootstrapping trust in a computer. We cover issues ranging from the wide collection of secure hardware that can serve as a foundation for trust, to the usability issues that arise when trying to convey computer state information to humans. This approach unifies disparate research efforts and highlights opportunities for additional work that can guide real-world improvements in computer security. 1

the Grants No. (NSC95-main) and No. (NSC95-org), and by gifts from AMD and Intel.

As society rushes to digitize sensitive information and services, it is imperative to adopt adequate security protections. However, such protections fundamentally conflict with the benefits we expect from commodity computers. In other words, consumers and businesses value commodity computers because they provide good performance and an abundance of features at relatively low costs. Meanwhile, attempts to build secure systems from the ground up typically abandon such goals, and hence are seldom adopted [8, 72, 104]. In this dissertation, I argue that we can resolve the tension between security and features by leveraging the trust a user has in one device to enable her to securely use another commodity device or service, without sacricing the performance and features expected ofcommodity systems. At a high level, we support this premise by developing techniques to allow a user to employ a small, trusted, portable device to securely learn what code is executing on her local computer. Rather than entrusting her data to the mountain of buggy code likely running on her computer, we construct an on-demand secure execution environment which can perform security-sensitive tasks and handle private data in complete isolation from all other softŸware (and most hardware) on the system. Meanwhile, non-security-sensitive soŸftware retains the same abundance of features and performance it enjoys today. Having established an environment for secure code execution on an individual computer, we then show how to extend trust in this environment to network elements in a secure and effi›cient manner. This allows us to reexamine the design of network protocols and defenses, since we can now execute code on endhosts and trust the results within the network. Lastly, we extend the user’s trust one more step to encompass computations performed on a remote host (e.g., in the cloud). We design, analyze, and prove secure a protocol that allows a user to outsource arbitrary computations to commodity computers run by an untrusted remote party (or parties) who may subject the computers to both soŸware and hardware attacks. Our protocol guarantees that the user can both verify that the results returned are indeed the correct results of the specified computations on the inputs provided, and protect the secrecy of both the inputs and outputs of the computations. These guarantees are provided in a non-interactive, asymptotically optimal (with respect to CPU and bandwidth) manner. Thus, extending a user’s trust, via softŸware, hardware, and cryptographic techniques, allows us to provide strong security protections for both local and remote computations on sensitive data, while still preserving the performance and features of commodity computers.