Searchable symmetric encryption (SSE) allows a client to encrypt its data in such a way that this data can still be searched. The most immediate application of SSE is to cloud storage, where it enables a client to securely outsource its data to an untrusted cloud provider without sacrificing the ability to search over it.

Proactive obfuscation is a new method for creating server replicas that are likely to have fewer shared vulnerabilities. It uses semantics-preserving code transformations to generate diverse executables, periodically restarting servers with these fresh versions. The periodic restarts help bound the number of compromised replicas that a service ever concurrently runs, and therefore proactive obfuscation makes an adversary's job harder. Proactive obfuscation was used in implementing two prototypes: a distributed firewall based on state-machine replication and a distributed storage service based on quorum systems. Costs intrinsic to supporting proactive obfuscation in replicated systems were evaluated by measuring the performance of these prototypes. The results show that employing proactive obfuscation adds little to the cost of replica-management protocols.

Cache-oblivious algorithms have been advanced as a way of circumventing some of the difficulties of optimizing applications to take advantage of the memory hierarchy of modern microprocessors. These algorithms are based on the divide-and-conquer paradigm -- each division step creates sub-problems of smaller size, and when the working set of a sub-problem fits in some level of the memory hierarchy, the computations in that sub-problem can be executed without suffering capacity misses at that level. In this way, divide-and-conquer algorithms adapt automatically to all levels of the memory hierarchy; in fact, for problems like matrix multiplication, matrix transpose, and FFT, these recursive algorithms are optimal to within constant factors for some theoretical models of the memory hierarchy.

Run-time conflicts can affect even the most rigorously tested software systems. A reliance on execution-based testing makes it prohibitively costly to test every possible interaction among potentially thousands of programs with complex configurations. In order to reduce configuration problems, detect developer errors, and reduce developer effort, we have created a new first class operating system abstraction, the application abstraction, which enables both online and offline reasoning about programs and their configuration requirements.We have implemented a subset of the application abstraction for device drivers in the Singularity operating system. Programmers use the application abstraction by placing declarative statements about hardware and communication requirements within their code. Our design enables Singularity to learn the input/output and interprocess communication requirements of drivers without executing driver code. By reasoning about this information within the domain of Singularity's strong software isolation architecture, the installer can execute a subset the system's resource management algorithm at install time to verify that a new driver will not conflict with existing software. This abstract representation also allows the system to run the full algorithm at driver start time to ensure that there are never resource conflicts between executing drivers, and that drivers never use undeclared resources.

In this paper, we describe the design and implementation of a distributed operating system for ad hoc networks. Our system simplifies the programming of ad hoc networks and extends total system lifetime by making the entire network appear as a single virtual machine. It automatically and transparently partitions applications into components and dynamically finds them a placement on nodes within the network to reduce energy consumption and to increase system longevity. This paper describes our programming model, outlines the design and implementation of our system and examines the energy efficiency of our approach through extensive simulations as well as validation of a deployment on a physical testbed. We evaluate practical, power-aware, general-purpose algorithms for component placement and migration, and demonstrate that they can significantly increase system longevity by effectively distributing energy consumption and avoiding hotspots.