Is there an Oblivious RAM Lower Bound for Online Reads?

Oblivious RAM (ORAM), introduced by Goldreich and Ostrovsky (JACM 1996), can be used to read and write to memory in a way that hides which locations are being accessed. The best known ORAM schemes have an $O(\log n)$ overhead per access, where $n$ is the data size. The work of Goldreich and Ostrovsky gave a lower bound showing that this is optimal for ORAM schemes that operate in a ``balls and bins\u27\u27 model, where memory blocks can only be shuffled between different locations but not manipulated otherwise. The lower bound even extends to weaker settings such as offline ORAM, where all of the accesses to be performed need to be specified ahead of time, and read-only ORAM, which only allows reads but not writes. But can we get lower bounds for general ORAM, beyond ``balls and bins\u27\u27? The work of Boyle and Naor (ITCS \u2716) shows that this is unlikely in the offline setting. In particular, they construct an offline ORAM with $o(\log n)$ overhead assuming the existence of small sorting circuits. Although we do not have instantiations of the latter, ruling them out would require proving new circuit lower bounds. On the other hand, the recent work of Larsen and Nielsen (CRYPTO \u2718) shows that there indeed is an $\Omega(\log n)$ lower bound for general online ORAM. This still leaves the question open for online read-only ORAM or for read/write ORAM where we want very small overhead for the read operations. In this work, we show that a lower bound in these settings is also unlikely. In particular, our main result is a construction of online ORAM where reads (but not writes) have an $o(\log n)$ overhead, assuming the existence of small sorting circuits as well as very good locally decodable codes (LDCs). Although we do not have instantiations of either of these with the required parameters, ruling them out is beyond current lower bounds

Lower Bounds for Oblivious Near-Neighbor Search

We prove an $\Omega(d \lg n/ (\lg\lg n)^2)$ lower bound on the dynamic cell-probe complexity of statistically $\mathit{oblivious}$ approximate-near-neighbor search ($\mathsf{ANN}$) over the $d$-dimensional Hamming cube. For the natural setting of $d = \Theta(\log n)$, our result implies an $\tilde{\Omega}(\lg^2 n)$ lower bound, which is a quadratic improvement over the highest (non-oblivious) cell-probe lower bound for $\mathsf{ANN}$. This is the first super-logarithmic $\mathit{unconditional}$ lower bound for $\mathsf{ANN}$ against general (non black-box) data structures. We also show that any oblivious $\mathit{static}$ data structure for decomposable search problems (like $\mathsf{ANN}$) can be obliviously dynamized with $O(\log n)$ overhead in update and query time, strengthening a classic result of Bentley and Saxe (Algorithmica, 1980).Comment: 28 page

Lower Bounds for Multi-Server Oblivious RAMs

In this work, we consider the construction of 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

Two-server distributed ORAM with sublinear computation and constant rounds

First author draf

Random-Index Oblivious RAM

We study the notion of Random-index ORAM (RORAM), which is a weak form of ORAM where the Client is limited to asking for (and possibly modifying) random elements of the $N$-items memory, rather than specific ones. That is, whenever the client issues a request, it gets in return a pair $(r,x_r)$ where $r\in_R[N]$ is a random index and $x_r$ is the content of the $r$-th memory item. Then, the client can also modify the content to some new value $x\u27_r$. We first argue that the limited functionality of RORAM still suffices for certain applications. These include various applications of sampling (or sub-sampling), and in particular the very-large-scale MPC application in the setting of~ Benhamouda et al. (TCC 2020). Clearly, RORAM can be implemented using any ORAM scheme (by the Client selecting the random $r$\u27s by himself), but the hope is that the limited functionality of RORAM can make it faster and easier to implement than ORAM. Indeed, our main contributions are several RORAM schemes (both of the hierarchical-type and the tree-type) of lighter complexity than that of ORAM

Security-Efficiency Tradeoffs in Searchable Encryption -- Lower Bounds and Optimal Constructions

Besides their security, the efficiency of searchable encryption schemes is a major criteria when it comes to their adoption: in order to replace an unencrypted database by a more secure construction, it must scale to the systems which rely on it. Unfortunately, the relationship between the efficiency and the security of searchable encryption has not been widely studied, and the minimum cost of some crucial security properties is still unclear. In this paper, we present new lower bounds on the tradeoffs between the size of the client state, the efficiency and the security for searchable encryption schemes. These lower bounds target two kinds of schemes: schemes hiding the repetition of search queries, and forward-private dynamic schemes, for which updates are oblivious. We also show that these lower bounds are tight, by either constructing schemes matching them, or by showing that even a small increase in the amount of leaked information allows for constructing schemes breaking the lower bounds

SoK: Plausibly Deniable Storage

Data privacy is critical in instilling trust and empowering the societal pacts of modern technology-driven democracies. Unfortunately, it is under continuous attack by overreaching or outright oppressive governments, including some of the world\u27s oldest democracies. Increasingly-intrusive anti-encryption laws severely limit the ability of standard encryption to protect privacy. New defense mechanisms are needed. Plausible deniability (PD) is a powerful property, enabling users to hide the existence of sensitive information in a system under direct inspection by adversaries. Popular encrypted storage systems such as TrueCrypt and other research efforts have attempted to also provide plausible deniability. Unfortunately, these efforts have often operated under less well-defined assumptions and adversarial models. Careful analyses often uncover not only high overheads but also outright security compromise. Further, our understanding of adversaries, the underlying storage technologies, as well as the available plausible deniable solutions have evolved dramatically in the past two decades. The main goal of this work is to systematize this knowledge. It aims to: - identify key PD properties, requirements, and approaches; - present a direly-needed unified framework for evaluating security and performance; - explore the challenges arising from the critical interplay between PD and modern system layered stacks; - propose a new trace-oriented PD paradigm, able to decouple security guarantees from the underlying systems and thus ensure a higher level of flexibility and security independent of the technology stack. This work is meant also as a trusted guide for system and security practitioners around the major challenges in understanding, designing, and implementing plausible deniability into new or existing systems

Snapshot-Oblivious RAMs: Sub-Logarithmic Efficiency for Short Transcripts

Oblivious RAM (ORAM) is a powerful technique to prevent harmful data breaches. Despite tremendous progress in improving the concrete performance of ORAM, it remains too slow for use in many practical settings; recent breakthroughs in lower bounds indicate this inefficiency is inherent for ORAM and even some natural relaxations. This work introduces snapshot-oblivious RAMs, a new secure memory access primitive. Snapshot-oblivious RAMs bypass lower bounds by providing security only for transcripts whose length (call it c) is fixed and known ahead of time. Intuitively, snapshot-oblivious RAMs provide strong security for attacks of short duration, such as the snapshot attacks targeted by many encrypted databases. We give an ORAM-style definition of this new primitive, and present several constructions. The underlying design principle of our constructions is to store the history of recent operations in a data structure that can be accessed obliviously. We instantiate this paradigm with data structures that remain on the client, giving a snapshot-oblivious RAM with constant bandwidth overhead. We also show how these data structures can be stored on the server and accessed using oblivious memory primitives. Our most efficient instantiation achieves O(log c) bandwidth overhead. By extending recent ORAM lower bounds, we show this performance is asymptotically optimal. Along the way, we define a new hash queue data structure—essentially, a dictionary whose elements can be modified in a first-in-first-out fashion—which may be of independent interest