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Modern software architectures in cloud computing are highly reliant on interconnected local and remote services. Popular architectures, such as the service mesh, rely on the use of independent services or sidecars for a single application. While such modular approaches simplify application development and deployment, they also introduce significant communication overhead since now even local communication that is handled by the kernel becomes a performance bottleneck. This problem has been identified and partially solved for remote communication over fast NICs through the use of kernel-bypass data plane systems. However, existing kernel-bypass mechanisms challenge their practical deployment by either requiring code modification or supporting only a small subset of the network interface. In this paper, we propose Pegasus, a framework for transparent kernel bypass for local and remote communication. By transparently fusing multiple applications into a single process, Pegasus provides an in-process fast path to bypass the kernel for local communication. To accelerate remote communication over fast NICs, Pegasus uses DPDK to directly access the NIC. Pegasus supports transparent kernel bypass for unmodified binaries by implementing core OS services in user space, such as scheduling and memory management, thus removing the kernel from the critical path. Our experiments on a range of real-world applications show that, compared with Linux, Pegasus improves the throughput by 19% to 33% for local communication and 178% to 442% for remote communication, without application changes. Furthermore, Pegasus achieves 222% higher throughput than Linux for co-located, IO-intensive applications that require both local and remote communication, with each communication optimization contributing significantly. 

Pointer analysis techniques are crucial for many software security mitigation approaches. However, these techniques suffer from imprecision; hence, the reported points-to sets are a superset of the actual points-to sets that can possibly form during program execution. To improve the precision of pointer analysis techniques, we propose Kaleidoscope. By using an invariant-guided optimistic (IGO) pointer analysis approach, Kaleidoscope makes optimistic assumptions during the pointer analysis that it later validates at runtime. If these optimistic assumptions do not hold true at runtime, Kaleidoscope falls back to an imprecise baseline analysis, thus preserving soundness. We show that Kaleidoscope reduces the average points-to set size by 13.15× across a set of 9 applications over the current state-of-the-art pointer analysis framework. Furthermore, we demonstrate how Kaleidoscope can implement control flow integrity (CFI) to increase the security of traditional CFI policies. 

Isolating application components is crucial to limit the exposure of sensitive data and code to vulnerabilities in the untrusted components. Process-based isolation is the de facto isolation used in practice, e.g., web browsers. However, it incurs significant performance overhead and is typically infeasible when frequent switches between isolation domains are expected. To address this problem, many intra-process memory isolation techniques have been proposed using novel kernel abstractions, recent CPU extensions (e.g., Intel ® MPK), and software-based fault isolation (e.g., WebAssembly). However, these techniques insufficiently isolate kernel resources, such as file descriptors, or do so by incurring high overheads when resources are accessed. Other work virtualizes the kernel context inside a privileged user space domain, but this is ad-hoc, error-prone, and provides only limited kernel functionalities. We propose μSwitch, an efficient kernel context isolation mechanism with memory protection that addresses these limitations. We use a protected structure, shared by the kernel and the user space, for context switching and propose implicit context switching to improve its performance by deferring the kernel resource switch to the next system call. We apply μSWITCH to isolate libraries in the Firefox web browser and an HTTP server, and reduce the overhead of isolation by 32.7% to 98.4% compared with other isolation techniques.