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Microarchitectural attacks exploit the abstraction gap between the Instruction Set Architecture (ISA) and how instructions are actually executed by processors to compromise the confidentiality and integrity of a system. To secure systems against microarchitectural attacks, programmers need to reason about and program against these microarchitectural side-effects. However, we cannot -- and should not -- expect programmers to manually tailor programs for specific processors and their security guarantees. Instead, we could rely on compilers (and the secure compilation community), as they can play a prominent role in bridging this gap: compilers should target specific processors microarchitectural security guarantees and they should leverage these guarantees to produce secure code. To achieve this, we outline the idea of Contract-Aware Secure COmpilation (CASCO) where compilers are parametric with respect to a hardware/software security-contract, an abstraction capturing a processors security guarantees. That is, compilers will automatically leverage the guarantees formalized in the contract to ensure that program-level security properties are preserved at microarchitectural level.
This paper presents SAILFISH, a scalable system for automatically finding state-inconsistency bugs in smart contracts. To make the analysis tractable, we introduce a hybrid approach that includes (i) a light-weight exploration phase that dramatically
Secure applications implement software protections against side-channel and physical attacks. Such protections are meaningful at machine code or micro-architectural level, but they typically do not carry observable semantics at source level. To preve
This paper presents iBatch, a middleware system running on top of an operational Ethereum network to enable secure batching of smart-contract invocations against an untrusted relay server off-chain. iBatch does so at a low overhead by validating the
We present a model/executable specification of smart contract execution in Coq. Our formalization allows for inter-contract communication and generalizes existing work by allowing modelling of both depth-first execution blockchains (like Ethereum) an
Local Differential Privacy (LDP) is popularly used in practice for privacy-preserving data collection. Although existing LDP protocols offer high utility for large user populations (100,000 or more users), they perform poorly in scenarios with small