Caches and hash trees for efficient memory integrity verification

By Blaise Gassend, G. Suh, Dwaine E. Clarke, Marten van Dijk, Srini Devadas. The Ninth International Symposium on High-Performance Computer Architecture, 2003. HPCA-9 2003. Proceedings., 2003

296 citations recorded by the source corpus.

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Scalable Zero Knowledge Via Cycles of Elliptic Curves (2014, background): “Memory checking techniques have found numerous practical applications for securing untrusted storages [58,59,65,77,78].”
Shielding Applications from an Untrusted Cloud with Haven (2014, background): “Like other systems [16, 17, 26, 36, 62], a Merkle tree [42] protects the integrity of the overall disk.”
AEGIS: architecture for tamper-evident and tamper-resistant processing (2003, background): “For a more detailed discussion of memory integrity verification, see [ 8 ] and [22].”
Efficient memory integrity verification and encryption for secure processors (2003, methodology): “[ 9 ] shows how caching of internal nodes of the tree can significantly improve the performance of the scheme.”
Improving Cost, Performance, and Security of Memory Encryption and Authentication (2006, background): “[4] employs authentication in which instructions are allowed to commit even before their data is completely authenticated [4].”
Intel SGX Explained (2016, methodology): “Aegis was the first secure processor not vulnerable to physical replay attacks, as it uses a Merkle tree construction [57] to guarantee DRAM freshness.”
Verifying computations with state (2013, methodology): “First, Pantry relies on Merkle trees [53] to authenticate a large untrusted memory, an idea used in theory [17] and in practice (for smartcards [30], databases [27, 49, 52], file systems [34, 43], etc.”