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Filters: Author is Subramanyan, Pramod  [Clear All Filters]
2020-04-03
Cheang, Kevin, Rasmussen, Cameron, Seshia, Sanjit, Subramanyan, Pramod.  2019.  A Formal Approach to Secure Speculation. 2019 IEEE 32nd Computer Security Foundations Symposium (CSF). :288—28815.
Transient execution attacks like Spectre, Meltdown and Foreshadow have shown that combinations of microarchitectural side-channels can be synergistically exploited to create side-channel leaks that are greater than the sum of their parts. While both hardware and software mitigations have been proposed against these attacks, provable security has remained elusive. This paper introduces a formal methodology for enabling secure speculative execution on modern processors. We propose a new class of information flow security properties called trace property-dependent observational determinism (TPOD). We use this class to formulate a secure speculation property. Our formulation precisely characterises all transient execution vulnerabilities. We demonstrate its applicability by verifying secure speculation for several illustrative programs.
2018-02-21
Subramanyan, Pramod, Sinha, Rohit, Lebedev, Ilia, Devadas, Srinivas, Seshia, Sanjit A..  2017.  A Formal Foundation for Secure Remote Execution of Enclaves. Proceedings of the 2017 ACM SIGSAC Conference on Computer and Communications Security. :2435–2450.

Recent proposals for trusted hardware platforms, such as Intel SGX and the MIT Sanctum processor, offer compelling security features but lack formal guarantees. We introduce a verification methodology based on a trusted abstract platform (TAP), a formalization of idealized enclave platforms along with a parameterized adversary. We also formalize the notion of secure remote execution and present machine-checked proofs showing that the TAP satisfies the three key security properties that entail secure remote execution: integrity, confidentiality and secure measurement. We then present machine-checked proofs showing that SGX and Sanctum are refinements of the TAP under certain parameterizations of the adversary, demonstrating that these systems implement secure enclaves for the stated adversary models.