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intelligence_src_e53adb99e40ae66258
observed · 2026-10-12 16:25:04 UTC
ePrint Report: Optimal Statistical Oblivious RAM and Search Tree in the External-Memory Model Andrew Krapivin, Elaine Shi Oblivious RAM (ORAM) allows a trusted client to access (encrypted) data stored in untrusted memory, such that the access patterns reveal nothing about the data or the queries. It is well-known that any ORAM scheme must suffer from a logarithmic overhead. More precisely stated, each request must incur $\Omega(\log_B N)$ block transfers on average, where $N$ is the size of the logical memory and $B$ is the block size of the oblivious implementation. Moreover, the same lower bound extends to oblivious Search Trees (ST). For upper bounds, however, we have been long stuck with a $(\log_B N)^2$ curse on two fronts: (1) Log-squared curse for statistically secure ORAMs: although optimality is known for computationally secure ORAMs for $B = \Theta(1)$ or $B \geq \log^{1+\epsilon} N$ (where $\epsilon > 0$ is an arbitrarily small constant), progress has been stagnant when it comes to statistical security. (2) Log-squared curse for oblivious search trees: for search trees, we do not know how to
Fingerprint: 51894facd80a3f04d3983b40b6de9831864888cfca7fe792b1f093bb005abcaa
intelligence_src_e53adb99e40ae66258
observed · 2026-10-12 16:25:03 UTC
available
Fingerprint: 366cb966e32414edc1db353849a1ee8d6b8462b83786e04001881ba6594765ad