On Low-End Obfuscation and Learning

Most recent works on cryptographic obfuscation focus on the high-end regime of obfuscating general circuits while guaranteeing computational indistinguishability between functionally equivalent circuits. Motivated by the goals of simplicity and efficiency, we initiate a systematic study of "low-end" obfuscation, focusing on simpler representation models and information-theoretic notions of security. We obtain the following results. - Positive results via "white-box" learning. We present a general technique for obtaining perfect indistinguishability obfuscation from exact learning algorithms that are given restricted access to the representation of the input function. We demonstrate the usefulness of this approach by obtaining simple obfuscation for decision trees and multilinear read-k arithmetic formulas. - Negative results via PAC learning. A proper obfuscation scheme obfuscates programs from a class C by programs from the same class. Assuming the existence of one-way functions, we show that there is no proper indistinguishability obfuscation scheme for k-CNF formulas for any constant k ? 3; in fact, even obfuscating 3-CNF by k-CNF is impossible. This result applies even to computationally secure obfuscation, and makes an unexpected use of PAC learning in the context of negative results for obfuscation. - Separations. We study the relations between different information-theoretic notions of indistinguishability obfuscation, giving cryptographic evidence for separations between them

More Practical and Secure History-Independent Hash Tables

Direct-recording electronic (DRE) voting systems have been used in several countries including United States, India, and the Netherlands to name a few. In the majority of those cases, researchers discovered several security flaws in the implementation and architecture of the voting system. A common property of the machines inspected was that the votes were stored sequentially according to the time they were cast, which allows an attacker to break the anonymity of the voters using some side-channel information. Subsequent research (Molnar et al. Oakland’06, Bethencourt et al. NDSS’07, Moran et al. ICALP’07) pointed out the connection between vote storage and history-independence, a privacy property that guarantees that the system does not reveal the sequence of operations that led to the current state. There are two flavors of history-independence. In a weakly history-independent data structure, every possible sequence of operations consistent with the current set of items is equally likely to have occurred. In a strongly history-independent data structure, items must be stored in a canonical way, i.e., for any set of items, there is only one possible memory representation. Strong history- independence implies weak history-independence but considerably constrains the design choices of the data structures. In this work, we present and analyze an efficient hash table data structure that simultaneously achieves the following properties: • It is based on the classic linear probing collision-handling scheme. • It is weakly history-independent. • It is secure against collision-timing attacks. That is, we consider adversaries that can measure the time for an update operation, but cannot observe data values, and we show that those adversaries cannot learn information about the items in the table. • All operations are significantly faster in practice (in particular, almost 2x faster for high load factors) than those of the commonly used strongly history-independent linear probing method proposed by Blelloch and Golovin (FOCS’07), which is not secure against collision-timing attacks. The first property is desirable for ease of implementation. The second property is desirable for the sake of maximizing privacy in scenarios where the memory of the hash table is exposed, such as post-election audit of DRE voting machines or direct memory access (DMA) attacks. The third property is desirable for maximizing privacy against adversaries who do not have access to memory but nevertheless are capable of accurately measuring the execution times of data structure operations. To our knowledge, our hash table construction is the first data structure that combines history-independence and protection against a form of timing attacks

Deterministic History-Independent Strategies for Storing Information on Write-Once Memories

Motivated by the challenging task of designing ``secure\u27\u27 vote storage mechanisms, we study information storage mechanisms that operate in extremely hostile environments. In such environments, the majority of existing techniques for information storage and for security are susceptible to powerful adversarial attacks. We propose a mechanism for storing a set of at most $K$ elements from a large universe of size $N$ on write-once memories in a manner that does not reveal the insertion order of the elements. We consider a standard model for write-once memories, in which the memory is initialized to the all $0$\u27s state, and the only operation allowed is flipping bits from $0$ to $1$. Whereas previously known constructions were either inefficient (required $\Theta(K^2)$ memory), randomized, or employed cryptographic techniques which are unlikely to be available in hostile environments, we eliminate each of these undesirable properties. The total amount of memory used by the mechanism is linear in the number of stored elements and poly-logarithmic in the size of the universe of elements. We also demonstrate a connection between secure vote storage mechanisms and one of the classical distributed computing problems: conflict resolution in multiple-access channels. By establishing a tight connection with the basic building block of our mechanism, we construct the first deterministic and non-adaptive conflict resolution algorithm whose running time is optimal up to poly-logarithmic factors

A Practical Oblivious Map Data Structure with Secure Deletion and History Independence

We present a new oblivious RAM that supports variable-sized storage blocks (vORAM), which is the first ORAM to allow varying block sizes without trivial padding. We also present a new history-independent data structure (a HIRB tree) that can be stored within a vORAM. Together, this construction provides an efficient and practical oblivious data structure (ODS) for a key/value map, and goes further to provide an additional privacy guarantee as compared to prior ODS maps: even upon client compromise, deleted data and the history of old operations remain hidden to the attacker. We implement and measure the performance of our system using Amazon Web Services, and the single-operation time for a realistic database (up to $2^{18}$ entries) is less than 1 second. This represents a 100x speed-up compared to the current best oblivious map data structure (which provides neither secure deletion nor history independence) by Wang et al. (CCS 14)

Cuckoo Hashing in Cryptography: Optimal Parameters, Robustness and Applications

Cuckoo hashing is a powerful primitive that enables storing items using small space with efficient querying. At a high level, cuckoo hashing maps $n$ items into $b$ entries storing at most $\ell$ items such that each item is placed into one of $k$ randomly chosen entries. Additionally, there is an overflow stash that can store at most $s$ items. Many cryptographic primitives rely upon cuckoo hashing to privately embed and query data where it is integral to ensure small failure probability when constructing cuckoo hashing tables as it directly relates to the privacy guarantees. As our main result, we present a more query-efficient cuckoo hashing construction using more hash functions. For construction failure probability $\epsilon$, the query overhead of our scheme is $O(1 + \sqrt{\log(1/\epsilon)/\log n})$. Our scheme has quadratically smaller query overhead than prior works for any target failure probability $\epsilon$. We also prove lower bounds matching our construction. Our improvements come from a new understanding of the locality of cuckoo hashing failures for small sets of items. We also initiate the study of robust cuckoo hashing where the input set may be chosen with knowledge of the hash functions. We present a cuckoo hashing scheme using more hash functions with query overhead $\tilde{O}(\log \lambda)$ that is robust against poly$(\lambda)$ adversaries. Furthermore, we present lower bounds showing that this construction is tight and that extending previous approaches of large stashes or entries cannot obtain robustness except with $\Omega(n)$ query overhead. As applications of our results, we obtain improved constructions for batch codes and PIR. In particular, we present the most efficient explicit batch code and blackbox reduction from single-query PIR to batch PIR