Search for: All records

This paper introduces nonblocking transaction composition (NBTC), a new methodology for atomic composition of nonblocking operations on concurrent data structures. Unlike previous software transactional memory (STM) approaches, NBTC leverages the linearizability of existing nonblocking structures, reducing the number of memory accesses that must be executed together, atomically, to only one per operation in most cases (these are typically the linearizing instructions of the constituent operations). Our obstruction-free implementation of NBTC, which we call Medley, makes it easy to transform most nonblocking data structures into transactional counterparts while preserving their liveness and high concurrency. In our experiments, Medley outperforms Lock-Free Transactional Transform (LFTT), the fastest prior competing methodology, by 40--170%. The marginal overhead of Medley's transactional composition, relative to separate operations performed in succession, is roughly 2.2x. For persistent data structures, we observe that failure atomicity for transactions can be achieved "almost for free'' with epoch-based periodic persistence. Toward that end, we integrate Medley with nbMontage, a general system for periodically persistent data structures. The resulting txMontage provides ACID transactions and achieves throughput up to two orders of magnitude higher than that of the OneFile persistent STM system. 

Temporal memory safety bugs, especially use-after-free and double free bugs, pose a major security threat to C programs. Real-world exploits utilizing these bugs enable attackers to read and write arbitrary memory locations, causing disastrous violations of confidentiality, integrity, and availability. Many previous solutions retrofit temporal memory safety to C, but they all either incur high performance overhead and/or miss detecting certain types of temporal memory safety bugs.

In this paper, we propose a temporal memory safety solution that is both efficient and comprehensive. Specifically, we extend Checked C, a spatially-safe extension to C, with temporally-safe pointers. These are implemented by combining two techniques: fat pointers and dynamic key-lock checks. We show that the fat-pointer solution significantly improves running time and memory overhead compared to the disjoint-metadata approach that provides the same level of protection. With empirical program data and hands-on experience porting real-world applications, we also show that our solution is practical in terms of backward compatibility---one of the major complaints about fat pointers.

 

We introduce nonblocking transaction composition (NBTC), a new methodology for atomic composition of nonblocking operations on concurrent data structures. Unlike previous software transactional memory (STM) approaches, NBTC leverages the linearizability of existing nonblocking structures, reducing the number of memory accesses that must be executed together, atomically, to only one per operation in most cases (these are typically the linearizing instructions of the constituent operations). Our obstruction-free implementation of NBTC, which we call Medley, makes it easy to transform most nonblocking data structures into transactional counterparts while preserving their nonblocking liveness and high concurrency. In our experiments, Medley outperforms Lock-Free Transactional Transform (LFTT), the fastest prior competing methodology, by 40--170%. The marginal overhead of Medley's transactional composition, relative to separate operations performed in succession, is roughly 2.2×. For persistent memory, we observe that failure atomicity for transactions can be achieved "almost for free" with epoch-based periodic persistence. Toward that end, we integrate Medley with nbMontage, a general system for periodically persistent data structures. The resulting txMontage provides ACID transactions and achieves throughput up to two orders of magnitude higher than that of the OneFile persistent STM system. 

Internet-of-Things devices such as autonomous vehicular sensors, medical devices, and industrial cyber-physical systems commonly rely on small, resource-constrained microcontrollers (MCUs). MCU software is typically written in C and is prone to memory safety vulnerabilities that are exploitable by remote attackers to launch code reuse attacks and code/control data leakage attacks. We present Randezvous, a highly performant diversification-based mitigation to such attacks and their brute force variants on ARM MCUs. Atop code/data layout randomization and an efficient execute-only code approach, Randezvous creates decoy pointers to camouflage control data in memory; code pointers in the stack are then protected by a diversified shadow stack, local-to-global variable promotion, and return address nullification. Moreover, Randezvous adds a novel delayed reboot mechanism to slow down persistent attacks and mitigates control data spraying attacks via global guards. We demonstrate Randezvous’s security by statistically modeling leakage-equipped brute force attacks under Randezvous, crafting a proof-of-concept exploit that shows Randezvous’s efficacy, and studying a real-world CVE. Our evaluation of Randezvous shows low overhead on three benchmark suites and two applications. 

This paper presents Kage: a system that protects the control data of both application and kernel code on microcontroller-based embedded systems. Kage consists of a Kage-compliant embedded OS that stores all control data in separate memory regions from untrusted data, a compiler that transforms code to protect these memory regions efficiently and to add forward-edge control-flow integrity checks, and a secure API that allows safe updates to the protected data. We implemented Kage as an extension to FreeRTOS, an embedded real-time operating system. We evaluated Kage’s performance using the CoreMark benchmark. Kage incurred a 5.2% average run-time overhead and 49.8% code size overhead. Furthermore, the code size overhead was only 14.2% when compared to baseline FreeRTOS with the MPU enabled. We also evaluated Kage’s security guarantees by measuring and analyzing reachable code-reuse gadgets. Compared to FreeRTOS, Kage reduces the number of reachable gadgets from 2,276 to 27, and the remaining 27 gadgets cannot be stitched together to launch a practical attack. 

Salerno, Italy 

San Diego, CA 

The kernels of operating systems such as Windows, Linux, and MacOS are vulnerable to control-flow hijacking. Defenses exist, but many require efficient intra-address-space isolation. Execute-only memory, for example, requires read protection on code segments, and shadow stacks require protection from buffer overwrites. Intel’s Protection Keys for Userspace (PKU) could, in principle, provide the intra-kernel isolation needed by such defenses, but, when used as designed, it applies only to user-mode application code. This paper presents an unconventional approach to memory pro- tection, allowing PKU to be used within the operating system kernel on existing Intel hardware, replacing the traditional user/supervisor isolation mechanism and, simultaneously, enabling efficient intra- kernel isolation. We call the resulting mechanism Protection Keys for Kernelspace (PKK). To demonstrate its utility and efficiency, we present a system we call IskiOS: a Linux variant featuring execute-only memory (XOM) and the first-ever race-free shadow stacks for x86-64. Experiments with the LMBench kernel microbenchmarks display a geometric mean overhead of about 11% for PKK and no additional overhead for XOM. IskiOS’s shadow stacks bring the total to 22%. For full applications, experiments with the system benchmarks of the Phoronix test suite display negligible overhead for PKK and XOM, and less than 5% geometric mean overhead for shadow stacks. 

We present a fully lock-free variant of our recent Montage system for persistent data structures. The variant, nbMontage, adds persistence to almost any nonblocking concurrent structure without introducing significant overhead or blocking of any kind. Like its predecessor, nbMontage is buffered durably linearizable: it guarantees that the state recovered in the wake of a crash will represent a consistent prefix of pre-crash execution. Unlike its predecessor, nbMontage ensures wait-free progress of the persistence frontier, thereby bounding the number of recent updates that may be lost on a crash, and allowing a thread to force an update of the frontier (i.e., to perform a sync operation) without the risk of blocking. As an extra benefit, the helping mechanism employed by our wait-free sync significantly reduces its latency. Performance results for nonblocking queues, skip lists, trees, and hash tables rival custom data structures in the literature – dramatically faster than achieved with prior general-purpose systems, and generally within 50% of equivalent non-persistent structures placed in DRAM. 

The emergence of fast, dense, nonvolatile main memory suggests that certain long-lived data might remain in their natural pointerrich format across program runs and hardware reboots. Operations on such data must currently be instrumented with explicit writeback and fence instructions to ensure consistency in the wake of a crash. Techniques to minimize the cost of this instrumentation are an active topic of research. We present what we believe to be the first general-purpose approach to building buffered persistent data structures, and a system, Montage, to support that approach. Montage is built on top of the Ralloc nonblocking persistent allocator. It employs a millisecondgranularity epoch clock, and ensures that no operation appears to span an epoch boundary. It also arranges to persist only that data minimally required to reconstruct the structure after a crash. If a crash occurs in epoch e, all work performed in epochs e and e − 1 is lost, but work from prior epochs is preserved, consistently. As in traditional file and database systems, a sync operation can be used to flush buffers on demand; the Montage sync is extremely fast. We describe the implementation of Montage, argue its correctness, and report unprecedented throughput for persistent queues, sets/mappings, and general graphs.