Security, Performance and Energy Trade-offs of Hardware-assisted Memory Protection Mechanisms

The deployment of large-scale distributed systems, e.g., publish-subscribe platforms, that operate over sensitive data using the infrastructure of public cloud providers, is nowadays heavily hindered by the surging lack of trust toward the cloud operators. Although purely software-based solutions exist to protect the confidentiality of data and the processing itself, such as homomorphic encryption schemes, their performance is far from being practical under real-world workloads. The performance trade-offs of two novel hardware-assisted memory protection mechanisms, namely AMD SEV and Intel SGX - currently available on the market to tackle this problem, are described in this practical experience. Specifically, we implement and evaluate a publish/subscribe use-case and evaluate the impact of the memory protection mechanisms and the resulting performance. This paper reports on the experience gained while building this system, in particular when having to cope with the technical limitations imposed by SEV and SGX. Several trade-offs that provide valuable insights in terms of latency, throughput, processing time and energy requirements are exhibited by means of micro- and macro-benchmarks.Comment: European Commission Project: LEGaTO - Low Energy Toolset for Heterogeneous Computing (EC-H2020-780681

SoK: Confidential Quartet - Comparison of Platforms for Virtualization-Based Confidential Computing

Confidential computing allows processing sensitive workloads in securely isolated spaces. Following earlier adop- tion of process-based approaches to isolation, vendors are now enabling hardware and firmware support for virtualization-based confidential computing on several server platforms. Due to variations in the technology stack, threat model, implemen-tation and functionality, the available solutions offer somewhat different capabilities, trade-offs and security guarantees. In this paper we review, compare and contextualize four virtualization-based confidential computing technologies for enterprise server platforms - AMD SEV, ARM CCA, IBM PEF and Intel TDX

Application Memory Isolation on Ultra-Low-Power Mcus

The proliferation of applications that handle sensitive user data on wearable platforms generates a critical need for embedded systems that offer strong security without sacrificing flexibility and long battery life. To secure sensitive information, such as health data, ultra-low-power wearables must isolate applications from each other and protect the underlying system from errant or malicious application code. These platforms typically use microcontrollers that lack sophisticated Memory Management Units (MMU). Some include a Memory Protection Unit (MPU), but current MPUs are inadequate to the task, leading platform developers to software-based memory-protection solutions. In this paper, we present our memory isolation technique, which leverages compiler inserted code and MPU-hardware support to achieve better runtime performance than software-only counterparts

Repurposing Software Defenses with Specialized Hardware

Computer security has largely been the domain of software for the last few decades. Although this approach has been moderately successful during this period, its problems have started becoming more apparent recently because of one primary reason — performance. Software solutions typically exact a significant toll in terms of program slowdown, especially when applied to large, complex software. In the past, when chips became exponentially faster, this growing burden could be accommodated almost for free. But as Moore’s law winds down, security-related slowdowns become more apparent, increasingly intolerable, and subsequently abandoned. As a result, the community has started looking elsewhere for continued protection, as attacks continue to become progressively more sophisticated. One way to mitigate this problem is to complement these defenses in hardware. Despite lacking the semantic perspective of high-level software, specialized hardware typically is not only faster, but also more energy-efficient. However, hardware vendors also have to factor in the cost of integrating security solutions from the perspective of effectiveness, longevity, and cost of development, while allaying the customer’s concerns of performance. As a result, although numerous hardware solutions have been proposed in the past, the fact that so few of them have actually transitioned into practice implies that they were unable to strike an optimal balance of the above qualities. This dissertation proposes the thesis that it is possible to add hardware features that complement and improve program security, traditionally provided by software, without requiring extensive modifications to existing hardware microarchitecture. As such, it marries the collective concerns of not only users and software developers, who demand performant but secure products, but also that of hardware vendors, since implementation simplicity directly relates to reduction in time and cost of development and deployment. To support this thesis, this dissertation discusses two hardware security features aimed at securing program code and data separately and details their full system implementations, and a study of a negative result where the design was deemed practically infeasible, given its high implementation complexity. Firstly, the dissertation discusses code protection by reviving instruction set randomization (ISR), an idea originally proposed for countering code injection and considered impractical in the face of modern attack vectors that employ reuse of existing program code (also known as code reuse attacks). With Polyglot, we introduce ISR with strong AES encryption along with basic code randomization that disallows code decryption at runtime, thus countering most forms of state-of-the-art dynamic code reuse attacks, that read the code at runtime prior to building the code reuse payload. Through various optimizations and corner case workarounds, we show how Polyglot enables code execution with minimal hardware changes while maintaining a small attack surface and incurring nominal overheads even when the code is strongly encrypted in the binary and memory. Next, the dissertation presents REST, a hardware primitive that allows programs to mark memory regions invalid for regular memory accesses. This is achieved simply by storing a large, pre-determined random value at those locations with a special store instruction and then, detecting incoming values at the data cache for matches to the predetermined value. Subsequently, we show how this primitive can be used to protect data from common forms of spatial and temporal memory safety attacks. Notably, because of the simplicity of the primitive, REST requires trivial microarchitectural modifications and hence, is easy to implement, and exhibits negligible performance overheads. Additionally, we demonstrate how it is able to provide practical heap safety even for legacy binaries. For the above proposals, we also detail their hardware implementations on FPGAs, and discuss how each fits within a complete multiprocess system. This serves to give the reader an idea of usage and deployment challenges on a broader scale that goes beyond just the technique’s effectiveness within the context of a single program. Lastly, the dissertation discusses an alternative to the virtual address space, that randomizes the sequence of addresses in a manner invisible to even the program, thus achieving transparent randomization of the entire address space at a very fine granularity. The biggest challenge is to achieve this with minimal microarchitectural changes while accommodating linear data structures in the program (e.g., arrays, structs), both of which are fundamentally based on a linear address space. As a result, this modified address space subsumes the benefits of most other spatial randomization schemes, with the additional benefit of ideally making traversal from one data structure to another impossible. Our study of this idea concludes that although valuable, current memory safety techniques are cheaper to implement and secure enough, so that there are no perceivable use cases for this model of address space safety

DR.SGX: Hardening SGX Enclaves against Cache Attacks with Data Location Randomization

Recent research has demonstrated that Intel's SGX is vulnerable to various software-based side-channel attacks. In particular, attacks that monitor CPU caches shared between the victim enclave and untrusted software enable accurate leakage of secret enclave data. Known defenses assume developer assistance, require hardware changes, impose high overhead, or prevent only some of the known attacks. In this paper we propose data location randomization as a novel defensive approach to address the threat of side-channel attacks. Our main goal is to break the link between the cache observations by the privileged adversary and the actual data accesses by the victim. We design and implement a compiler-based tool called DR.SGX that instruments enclave code such that data locations are permuted at the granularity of cache lines. We realize the permutation with the CPU's cryptographic hardware-acceleration units providing secure randomization. To prevent correlation of repeated memory accesses we continuously re-randomize all enclave data during execution. Our solution effectively protects many (but not all) enclaves from cache attacks and provides a complementary enclave hardening technique that is especially useful against unpredictable information leakage