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This article surveys the landscape of security verification approaches and techniques for computer systems at various levels: from a software-application level all the way to the physical hardware level. Different existing projects are compared, based on the tools used and security aspects being examined. Since many systems require both hardware and software components to work together to provide the system’s promised security protections, it is not sufficient to verify just the software levels or just the hardware levels in a mutually exclusive fashion. This survey especially highlights system levels that are verified by the different existing projects and presents to the readers the state of the art in hardware and software system security verification. Few approaches come close to providing full-system verification, and there is still much room for improvement.

 

Provides a detailed characterization of MPC based NLP model inference. 

Transient execution attacks, also known as speculative execution attacks, have drawn much interest in the last few years as they can cause critical data leakage. Since the first disclosure of Spectre and Meltdown attacks in January 2018, a number of new transient execution attack types have been demonstrated targeting different processors. A transient execution attack consists of two main components: transient execution itself and a covert channel that is used to actually exfiltrate the information.Transient execution is a result of the fundamental features of modern processors that are designed to boost performance and efficiency, while covert channels are unintended information leakage channels that result from temporal and spatial sharing of the micro-architectural components. Given the severity of the transient execution attacks, they have motivated computer architects in both industry and academia to rethink the design of the processors and to propose hardware defenses. To help understand the transient execution attacks, this survey summarizes the phases of the attacks and the security boundaries across which the information is leaked in different attacks.This survey further analyzes the causes of transient execution as well as the different types of covert channels and presents a taxonomy of the attacks based on the causes and types. This survey in addition presents metrics for comparing different aspects of the transient execution attacks and uses them to evaluate the feasibility of the different attacks. This survey especially considers both existing attacks and potential new attacks suggested by our analysis. This survey finishes by discussing different mitigations that have so far been proposed at the micro-architecture level and discusses their benefits and limitations. 

Public cloud infrastructures allow for easy, on-demand access to FPGA resources. However, the low-level, direct access to the FPGA hardware exposes the infrastructure providers to new types of attacks. Prior work has shown that it is possible to uniquely identify the underlying hardware by creating fingerprints of the different FPGA instances that users rent from a cloud provider, but such work was not able to actually map the cloud FPGA infrastructure itself. Meanwhile, this paper demonstrates that it is possible to reverse-engineer the co-location of FPGA boards inside a cloud FPGA server using PCIe contention. Specifically, this work deduces the Non-Uniform Memory Access (NUMA) locality of FPGA boards within a server by analyzing their mutual PCIe contention during simultaneous use of the PCIe bus. In addition, experiments conducted in data centers located in several geographic regions and repeated at different times are used to calculate the probability that cloud providers allocate FPGA boards co-located in the same server to a user. This paper thus shows that it is possible to map cloud FPGA infrastructures, and learn how FPGA instances are physically co-located within a server. Consequently, this paper also highlights the importance of mitigating these novel avenues for reverse-engineering and mapping of cloud FPGA setups, as they can reveal insights about the cloud infrastructure itself, or assist other single- and multi-tenant attacks.