## CryptoDB

### Kasper Green Larsen

#### Publications

Year
Venue
Title
2020
TCC
In this work, we consider oblivious RAMs (ORAM) in a setting with multiple servers and the adversary may corrupt a subset of the servers. We present an $\Omega(log n)$ overhead lower bound for any k-server ORAM that limits any PPT adversary to distinguishing advantage at most $1/4k$ when only one server is corrupted. In other words, if one insists on negligible distinguishing advantage, then multi-server ORAMs cannot be faster than single-server ORAMs even with polynomially many servers of which only one unknown server is corrupted. Our results apply to ORAMs that may err with probability at most 1/128 as well as scenarios where the adversary corrupts larger subsets of servers. We also extend our lower bounds to other important data structures including oblivious stacks, queues, deques, priority queues and search trees.
2019
CRYPTO
We prove a lower bound on the communication complexity of unconditionally secure multiparty computation, both in the standard model with $n=2t+1$ parties of which t are corrupted, and in the preprocessing model with $n=t+1$ . In both cases, we show that for any $g \in \mathbb {N}$ there exists a Boolean circuit C with g gates, where any secure protocol implementing C must communicate $\varOmega (n g)$ bits, even if only passive and statistical security is required. The results easily extends to constructing similar circuits over any fixed finite field. This shows that for all sizes of circuits, the O(n) overhead of all known protocols when t is maximal is inherent. It also shows that security comes at a price: the circuit we consider could namely be computed among n parties with communication only O(g) bits if no security was required. Our results extend to the case where the threshold t is suboptimal. For the honest majority case, this shows that the known optimizations via packed secret-sharing can only be obtained if one accepts that the threshold is $t= (1/2 - c)n$ for a constant c. For the honest majority case, we also show an upper bound that matches the lower bound up to a constant factor (existing upper bounds are a factor $\lg n$ off for Boolean circuits).
2018
CRYPTO
An Oblivious RAM (ORAM) introduced by Goldreich and Ostrovsky [JACM’96] is a (possibly randomized) RAM, for which the memory access pattern reveals no information about the operations performed. The main performance metric of an ORAM is the bandwidth overhead, i.e., the multiplicative factor extra memory blocks that must be accessed to hide the operation sequence. In their seminal paper introducing the ORAM, Goldreich and Ostrovsky proved an amortized $\varOmega (\lg n)$ bandwidth overhead lower bound for ORAMs with memory size n. Their lower bound is very strong in the sense that it applies to the “offline” setting in which the ORAM knows the entire sequence of operations ahead of time.However, as pointed out by Boyle and Naor [ITCS’16] in the paper “Is there an oblivious RAM lower bound?”, there are two caveats with the lower bound of Goldreich and Ostrovsky: (1) it only applies to “balls in bins” algorithms, i.e., algorithms where the ORAM may only shuffle blocks around and not apply any sophisticated encoding of the data, and (2), it only applies to statistically secure constructions. Boyle and Naor showed that removing the “balls in bins” assumption would result in super linear lower bounds for sorting circuits, a long standing open problem in circuit complexity. As a way to circumventing this barrier, they also proposed a notion of an “online” ORAM, which is an ORAM that remains secure even if the operations arrive in an online manner. They argued that most known ORAM constructions work in the online setting as well.Our contribution is an $\varOmega (\lg n)$ lower bound on the bandwidth overhead of any online ORAM, even if we require only computational security and allow arbitrary representations of data, thus greatly strengthening the lower bound of Goldreich and Ostrovsky in the online setting. Our lower bound applies to ORAMs with memory size n and any word size $r \ge 1$ . The bound therefore asymptotically matches the known upper bounds when $r = \varOmega (\lg ^2 n)$ .
2016
CRYPTO

#### Coauthors

Carsten Baum (1)
Ivan Damgård (2)
Michael Nielsen (1)
Jesper Buus Nielsen (2)
Mark Simkin (1)
Kevin Yeo (1)