On the Complexity of Scrypt and Proofs of Space in the Parallel Random Oracle Model

We investigate lower bounds in terms of time and memory on the {\em parallel} complexity of an adversary $\cal A$ computing labels of randomly selected challenge nodes in direct acyclic graphs, where the $w$-bit label of a node is the hash $H(.)$ (modelled as a random oracle with $w$-bit output) of the labels of its parents. Specific instances of this general problem underlie both proofs-of-space protocols [Dziembowski et al. CRYPTO\u2715] as well as memory-hardness proofs including {\sf scrypt}, a widely deployed password hashing and key-derivation function which is e.g. used within Proofs-of-Work for digital currencies like Litecoin. Current lower bound proofs for these problems only consider {\em restricted} algorithms $\cal A$ which perform only a single $H(.)$ query at a time and which only store individual labels (but not arbitrary functions thereof). This paper substantially improves this state of affairs; Our first set of results shows that even when allowing multiple parallel \hash queries, the ``cumulative memory complexity\u27\u27 (CMC), as recently considered by Alwen and Serbinenko [STOC \u2715], of ${\sf scrypt}$ is at least $w \cdot (n/\log(n))^2$, when ${\sf scrypt}$ invokes $H(.)$ $n$ times. Our lower bound holds for adversaries which can store (1) Arbitrary labels (i.e., random oracle outputs) and (2) Certain natural functions of these labels, e.g., linear combinations. The exact power of such adversaries is captured via the combinatorial abstraction of parallel ``entangled\u27\u27 pebbling games on graphs, which we introduce and study. We introduce a combinatorial quantity $\gamma_n$ and under the conjecture that it is upper bounded by some constant, we show that the above lower bound on the CMC also holds for arbitrary algorithms $\cal A$, storing in particular arbitrary functions of their labels. We also show that under the same conjecture, the {\em time complexity} of computing the label of a random node in a graph on $n$ nodes (given an initial $kw$-bit state) reduces tightly to the time complexity for entangled pebbling on the same graph (given an initial $k$-node pebbling). Under the conjecture, this solves the main open problem from the work of Dziembowski et al. In fact, we note that every non-trivial upper bound on $\gamma_n$ will lead to the first non-trivial bounds for general adversaries for this problem

LIPIcs

Proofs of space (PoS) [Dziembowski et al., CRYPTO'15] are proof systems where a prover can convince a verifier that he "wastes" disk space. PoS were introduced as a more ecological and economical replacement for proofs of work which are currently used to secure blockchains like Bitcoin. In this work we investigate extensions of PoS which allow the prover to embed useful data into the dedicated space, which later can be recovered. Our first contribution is a security proof for the original PoS from CRYPTO'15 in the random oracle model (the original proof only applied to a restricted class of adversaries which can store a subset of the data an honest prover would store). When this PoS is instantiated with recent constructions of maximally depth robust graphs, our proof implies basically optimal security. As a second contribution we show three different extensions of this PoS where useful data can be embedded into the space required by the prover. Our security proof for the PoS extends (non-trivially) to these constructions. We discuss how some of these variants can be used as proofs of catalytic space (PoCS), a notion we put forward in this work, and which basically is a PoS where most of the space required by the prover can be used to backup useful data. Finally we discuss how one of the extensions is a candidate construction for a proof of replication (PoR), a proof system recently suggested in the Filecoin whitepaper

Balloon Hashing: A Memory-Hard Function Providing Provable Protection Against Sequential Attacks

We present the Balloon password-hashing algorithm. This is the first practical cryptographic hash function that: (i) has proven memory-hardness properties in the random-oracle model, (ii) uses a password-independent access pattern, and (iii) meets or exceeds the performance of the best heuristically secure password-hashing algorithms. Memory-hard functions require a large amount of working space to evaluate efficiently and when used for password hashing, they dramatically increase the cost of offline dictionary attacks. In this work, we leverage a previously unstudied property of a certain class of graphs (“random sandwich graphs”) to analyze the memory-hardness of the Balloon algorithm. The techniques we develop are general: we also use them to give a proof of security of the scrypt and Argon2i password-hashing functions in the random-oracle model. Our security analysis uses a sequential model of computation, which essentially captures attacks that run on single-core machines. Recent work shows how to use massively parallel special-purpose machines (e.g., with hundreds of cores) to attack Balloon and other memory-hard functions. We discuss these important attacks, which are outside of our adversary model, and propose practical defenses against them. To motivate the need for security proofs in the area of password hashing, we demonstrate and implement a practical attack against Argon2i that successfully evaluates the function with less space than was previously claimed possible. Finally, we use experimental results to compare the performance of the Balloon hashing algorithm to other memory-hard functions

Computationally Data-Independent Memory Hard Functions

Memory hard functions (MHFs) are an important cryptographic primitive that are used to design egalitarian proofs of work and in the construction of moderately expensive key-derivation functions resistant to brute-force attacks. Broadly speaking, MHFs can be divided into two categories: data-dependent memory hard functions (dMHFs) and data-independent memory hard functions (iMHFs). iMHFs are resistant to certain side-channel attacks as the memory access pattern induced by the honest evaluation algorithm is independent of the potentially sensitive input e.g., password. While dMHFs are potentially vulnerable to side-channel attacks (the induced memory access pattern might leak useful information to a brute-force attacker), they can achieve higher cumulative memory complexity (CMC) in comparison than an iMHF. In particular, any iMHF that can be evaluated in N steps on a sequential machine has CMC at most ?((N^2 log log N)/log N). By contrast, the dMHF scrypt achieves maximal CMC ?(N^2) - though the CMC of scrypt would be reduced to just ?(N) after a side-channel attack. In this paper, we introduce the notion of computationally data-independent memory hard functions (ciMHFs). Intuitively, we require that memory access pattern induced by the (randomized) ciMHF evaluation algorithm appears to be independent from the standpoint of a computationally bounded eavesdropping attacker - even if the attacker selects the initial input. We then ask whether it is possible to circumvent known upper bound for iMHFs and build a ciMHF with CMC ?(N^2). Surprisingly, we answer the question in the affirmative when the ciMHF evaluation algorithm is executed on a two-tiered memory architecture (RAM/Cache). We introduce the notion of a k-restricted dynamic graph to quantify the continuum between unrestricted dMHFs (k=n) and iMHFs (k=1). For any ? > 0 we show how to construct a k-restricted dynamic graph with k=?(N^(1-?)) that provably achieves maximum cumulative pebbling cost ?(N^2). We can use k-restricted dynamic graphs to build a ciMHF provided that cache is large enough to hold k hash outputs and the dynamic graph satisfies a certain property that we call "amenable to shuffling". In particular, we prove that the induced memory access pattern is indistinguishable to a polynomial time attacker who can monitor the locations of read/write requests to RAM, but not cache. We also show that when k=o(N^(1/log log N))then any k-restricted graph with constant indegree has cumulative pebbling cost o(N^2). Our results almost completely characterize the spectrum of k-restricted dynamic graphs

Scrypt is Maximally Memory-Hard

Memory-hard functions (MHFs) are hash algorithms whose evaluation cost is dominated by memory cost. As memory, unlike computation, costs about the same across different platforms, MHFs cannot be evaluated at significantly lower cost on dedicated hardware like ASICs. MHFs have found widespread applications including password hashing, key derivation, and proofs-of-work. This paper focuses on scrypt, a simple candidate MHF designed by Percival, and described in RFC 7914. It has been used within a number of cryptocurrencies (e.g., Litecoin and Dogecoin) and has been an inspiration for Argon2d, one of the winners of the recent password-hashing competition. Despite its popularity, no rigorous lower bounds on its memory complexity are known. We prove that scrypt is optimally memory hard, i.e., its cumulative memory complexity (cmc) in the parallel random oracle model is $\Omega(n^2 w)$, where $w$ and $n$ are the output length and number of invocations of the underlying hash function, respectively. High cmc is a strong security target for MHFs introduced by Alwen and Serbinenko (STOC \u2715) which implies high memory cost even for adversaries who can amortise the cost over many evaluations and evaluate the underlying hash functions many times in parallel. Our proof is the first showing optimal memory hardness for any MHF. Our result improves both quantitatively and qualitatively upon the recent work by Alwen et al. (EUROCRYPT \u2716) who proved a weaker lower bound of $\Omega(n^2 w /\log^2 n)$ for a restricted class of adversaries

Foundations, Properties, and Security Applications of Puzzles: A Survey

Cryptographic algorithms have been used not only to create robust ciphertexts but also to generate cryptograms that, contrary to the classic goal of cryptography, are meant to be broken. These cryptograms, generally called puzzles, require the use of a certain amount of resources to be solved, hence introducing a cost that is often regarded as a time delay---though it could involve other metrics as well, such as bandwidth. These powerful features have made puzzles the core of many security protocols, acquiring increasing importance in the IT security landscape. The concept of a puzzle has subsequently been extended to other types of schemes that do not use cryptographic functions, such as CAPTCHAs, which are used to discriminate humans from machines. Overall, puzzles have experienced a renewed interest with the advent of Bitcoin, which uses a CPU-intensive puzzle as proof of work. In this paper, we provide a comprehensive study of the most important puzzle construction schemes available in the literature, categorizing them according to several attributes, such as resource type, verification type, and applications. We have redefined the term puzzle by collecting and integrating the scattered notions used in different works, to cover all the existing applications. Moreover, we provide an overview of the possible applications, identifying key requirements and different design approaches. Finally, we highlight the features and limitations of each approach, providing a useful guide for the future development of new puzzle schemes.Comment: This article has been accepted for publication in ACM Computing Survey

Bandwidth Hard Functions for ASIC Resistance

Cryptographic hash functions have wide applications including password hashing, pricing functions for spam and denial-of-service countermeasures and proof of work in cryptocurrencies. Recent progress on ASIC (Application Specific Integrated Circuit) hash engines raise concerns about the security of the above applications. This leads to a growing interest in ASIC resistant hash function and ASIC resistant proof of work schemes, i.e., those that do not give ASICs a huge advantage. The standard approach towards ASIC resistance today is through memory hard functions or memory hard proof of work schemes. However, we observe that the memory hardness approach is an incomplete solution. It only attempts to provide resistance to an ASIC\u27s area advantage but overlooks the more important energy advantage. In this paper, we propose the notion of bandwidth hard functions to reduce an ASIC\u27s energy advantage. CPUs cannot compete with ASICs for energy efficiency in computation, but we can rely on memory accesses to reduce an ASIC\u27s energy advantage because energy costs of memory accesses are comparable for ASICs and CPUs. We propose a model for hardware energy cost that has sound foundations in practice. We then analyze the bandwidth hardness property of ASIC resistant candidates. We find scrypt, Catena-BRG and Balloon are bandwidth hard with suitable parameters. Lastly, we observe that a capacity hard function is not necessarily bandwidth hard, with a stacked double butterfly graph being a counterexample

On Locally Decodable Codes in Resource Bounded Channels

Constructions of locally decodable codes (LDCs) have one of two undesirable properties: low rate or high locality (polynomial in the length of the message). In settings where the encoder/decoder have already exchanged cryptographic keys and the channel is a probabilistic polynomial time (PPT) algorithm, it is possible to circumvent these barriers and design LDCs with constant rate and small locality. However, the assumption that the encoder/decoder have exchanged cryptographic keys is often prohibitive. We thus consider the problem of designing explicit and efficient LDCs in settings where the channel is slightly more constrained than the encoder/decoder with respect to some resource e.g., space or (sequential) time. Given an explicit function f that the channel cannot compute, we show how the encoder can transmit a random secret key to the local decoder using f(?) and a random oracle ?(?). We then bootstrap the private key LDC construction of Ostrovsky, Pandey and Sahai (ICALP, 2007), thereby answering an open question posed by Guruswami and Smith (FOCS 2010) of whether such bootstrapping techniques are applicable to LDCs in channel models weaker than just PPT algorithms. Specifically, in the random oracle model we show how to construct explicit constant rate LDCs with locality of polylog in the security parameter against various resource constrained channels

PURED: A unified framework for resource-hard functions

Algorithm hardness can be described by 5 categories: hardness in computation, in sequential computation, in memory, in energy consumption (or bandwidth), in code size. Similarly, hardness can be a concern for solving or for verifying, depending on the context, and can depend on a secret trapdoor or be universally hard. Two main lines of research investigated such problems: cryptographic puzzles, that gained popularity thanks to blockchain consensus systems (where solving must be moderately hard, and verification either public or private), and white box cryptography (where solving must be hard without knowledge of the secret key). In this work, we improve upon the classification framework proposed by Biryukov and Perrin in Asiacypt 2017 and offer a united hardness framework, PURED, that can be used for measuring all these kinds of hardness, both in solving and verifying. We also propose three new constructions that fill gaps previously uncovered by the literature (namely, trapdoor proof of CMC, trapdoor proof of code, and a hard challenge in sequential time trapdoored in verification), and analyse their hardness in the PURED framework