@inproceedings{193,
abstract = {We show attacks on five data-independent memory-hard functions (iMHF) that were submitted to the password hashing competition (PHC). Informally, an MHF is a function which cannot be evaluated on dedicated hardware, like ASICs, at significantly lower hardware and/or energy cost than evaluating a single instance on a standard single-core architecture. Data-independent means the memory access pattern of the function is independent of the input; this makes iMHFs harder to construct than data-dependent ones, but the latter can be attacked by various side-channel attacks. Following [Alwen-Blocki'16], we capture the evaluation of an iMHF as a directed acyclic graph (DAG). The cumulative parallel pebbling complexity of this DAG is a measure for the hardware cost of evaluating the iMHF on an ASIC. Ideally, one would like the complexity of a DAG underlying an iMHF to be as close to quadratic in the number of nodes of the graph as possible. Instead, we show that (the DAGs underlying) the following iMHFs are far from this bound: Rig.v2, TwoCats and Gambit each having an exponent no more than 1.75. Moreover, we show that the complexity of the iMHF modes of the PHC finalists Pomelo and Lyra2 have exponents at most 1.83 and 1.67 respectively. To show this we investigate a combinatorial property of each underlying DAG (called its depth-robustness. By establishing upper bounds on this property we are then able to apply the general technique of [Alwen-Block'16] for analyzing the hardware costs of an iMHF.},
author = {Alwen, Joel F and Gazi, Peter and Kamath Hosdurg, Chethan and Klein, Karen and Osang, Georg F and Pietrzak, Krzysztof Z and Reyzin, Lenoid and Rolinek, Michal and Rybar, Michal},
booktitle = {Proceedings of the 2018 on Asia Conference on Computer and Communication Security},
location = {Incheon, Republic of Korea},
pages = {51 -- 65},
publisher = {ACM},
title = {{On the memory hardness of data independent password hashing functions}},
doi = {10.1145/3196494.3196534},
year = {2018},
}
@inproceedings{6941,
abstract = {Bitcoin has become the most successful cryptocurrency ever deployed, and its most distinctive feature is that it is decentralized. Its underlying protocol (Nakamoto consensus) achieves this by using proof of work, which has the drawback that it causes the consumption of vast amounts of energy to maintain the ledger. Moreover, Bitcoin mining dynamics have become less distributed over time.
Towards addressing these issues, we propose SpaceMint, a cryptocurrency based on proofs of space instead of proofs of work. Miners in SpaceMint dedicate disk space rather than computation. We argue that SpaceMint’s design solves or alleviates several of Bitcoin’s issues: most notably, its large energy consumption. SpaceMint also rewards smaller miners fairly according to their contribution to the network, thus incentivizing more distributed participation.
This paper adapts proof of space to enable its use in cryptocurrency, studies the attacks that can arise against a Bitcoin-like blockchain that uses proof of space, and proposes a new blockchain format and transaction types to address these attacks. Our prototype shows that initializing 1 TB for mining takes about a day (a one-off setup cost), and miners spend on average just a fraction of a second per block mined. Finally, we provide a game-theoretic analysis modeling SpaceMint as an extensive game (the canonical game-theoretic notion for games that take place over time) and show that this stylized game satisfies a strong equilibrium notion, thereby arguing for SpaceMint ’s stability and consensus.},
author = {Park, Sunoo and Kwon, Albert and Fuchsbauer, Georg and Gazi, Peter and Alwen, Joel F and Pietrzak, Krzysztof Z},
booktitle = {22nd International Conference on Financial Cryptography and Data Security},
isbn = {9783662583869},
issn = {0302-9743},
location = {Nieuwpoort, Curacao},
pages = {480--499},
publisher = {Springer Nature},
title = {{SpaceMint: A cryptocurrency based on proofs of space}},
doi = {10.1007/978-3-662-58387-6_26},
volume = {10957},
year = {2018},
}
@inproceedings{298,
abstract = {Memory-hard functions (MHF) are functions whose evaluation cost is dominated by memory cost. MHFs are egalitarian, in the sense that evaluating them on dedicated hardware (like FPGAs or ASICs) is not much cheaper than on off-the-shelf hardware (like x86 CPUs). MHFs have interesting cryptographic applications, most notably to password hashing and securing blockchains.
Alwen and Serbinenko [STOC’15] define the cumulative memory complexity (cmc) of a function as the sum (over all time-steps) of the amount of memory required to compute the function. They advocate that a good MHF must have high cmc. Unlike previous notions, cmc takes into account that dedicated hardware might exploit amortization and parallelism. Still, cmc has been critizised as insufficient, as it fails to capture possible time-memory trade-offs; as memory cost doesn’t scale linearly, functions with the same cmc could still have very different actual hardware cost.
In this work we address this problem, and introduce the notion of sustained-memory complexity, which requires that any algorithm evaluating the function must use a large amount of memory for many steps. We construct functions (in the parallel random oracle model) whose sustained-memory complexity is almost optimal: our function can be evaluated using n steps and O(n/log(n)) memory, in each step making one query to the (fixed-input length) random oracle, while any algorithm that can make arbitrary many parallel queries to the random oracle, still needs Ω(n/log(n)) memory for Ω(n) steps.
As has been done for various notions (including cmc) before, we reduce the task of constructing an MHFs with high sustained-memory complexity to proving pebbling lower bounds on DAGs. Our main technical contribution is the construction is a family of DAGs on n nodes with constant indegree with high “sustained-space complexity”, meaning that any parallel black-pebbling strategy requires Ω(n/log(n)) pebbles for at least Ω(n) steps.
Along the way we construct a family of maximally “depth-robust” DAGs with maximum indegree O(logn) , improving upon the construction of Mahmoody et al. [ITCS’13] which had maximum indegree O(log2n⋅},
author = {Alwen, Joel F and Blocki, Jeremiah and Pietrzak, Krzysztof Z},
location = {Tel Aviv, Israel},
pages = {99 -- 130},
publisher = {Springer},
title = {{Sustained space complexity}},
doi = {10.1007/978-3-319-78375-8_4},
volume = {10821},
year = {2018},
}
@inproceedings{6527,
abstract = {A memory-hard function (MHF) ƒn with parameter n can be computed in sequential time and space n. Simultaneously, a high amortized parallel area-time complexity (aAT) is incurred per evaluation. In practice, MHFs are used to limit the rate at which an adversary (using a custom computational device) can evaluate a security sensitive function that still occasionally needs to be evaluated by honest users (using an off-the-shelf general purpose device). The most prevalent examples of such sensitive functions are Key Derivation Functions (KDFs) and password hashing algorithms where rate limits help mitigate off-line dictionary attacks. As the honest users' inputs to these functions are often (low-entropy) passwords special attention is given to a class of side-channel resistant MHFs called iMHFs.
Essentially all iMHFs can be viewed as some mode of operation (making n calls to some round function) given by a directed acyclic graph (DAG) with very low indegree. Recently, a combinatorial property of a DAG has been identified (called "depth-robustness") which results in good provable security for an iMHF based on that DAG. Depth-robust DAGs have also proven useful in other cryptographic applications. Unfortunately, up till now, all known very depth-robust DAGs are impractically complicated and little is known about their exact (i.e. non-asymptotic) depth-robustness both in theory and in practice.
In this work we build and analyze (both formally and empirically) several exceedingly simple and efficient to navigate practical DAGs for use in iMHFs and other applications. For each DAG we:
*Prove that their depth-robustness is asymptotically maximal.
*Prove bounds of at least 3 orders of magnitude better on their exact depth-robustness compared to known bounds for other practical iMHF.
*Implement and empirically evaluate their depth-robustness and aAT against a variety of state-of-the art (and several new) depth-reduction and low aAT attacks.
We find that, against all attacks, the new DAGs perform significantly better in practice than Argon2i, the most widely deployed iMHF in practice.
Along the way we also improve the best known empirical attacks on the aAT of Argon2i by implementing and testing several heuristic versions of a (hitherto purely theoretical) depth-reduction attack. Finally, we demonstrate practicality of our constructions by modifying the Argon2i code base to use one of the new high aAT DAGs. Experimental benchmarks on a standard off-the-shelf CPU show that the new modifications do not adversely affect the impressive throughput of Argon2i (despite seemingly enjoying significantly higher aAT).
},
author = {Alwen, Joel F and Blocki, Jeremiah and Harsha, Ben},
booktitle = {Proceedings of the 2017 ACM SIGSAC Conference on Computer and Communications Security},
isbn = {9781450349468},
location = {Dallas, TX, USA},
pages = {1001--1017},
publisher = {ACM Press},
title = {{Practical graphs for optimal side-channel resistant memory-hard functions}},
doi = {10.1145/3133956.3134031},
year = {2017},
}
@inproceedings{559,
abstract = {Proofs of space (PoS) were suggested as more ecological and economical alternative to proofs of work, which are currently used in blockchain designs like Bitcoin. The existing PoS are based on rather sophisticated graph pebbling lower bounds. Much simpler and in several aspects more efficient schemes based on inverting random functions have been suggested, but they don’t give meaningful security guarantees due to existing time-memory trade-offs. In particular, Hellman showed that any permutation over a domain of size N can be inverted in time T by an algorithm that is given S bits of auxiliary information whenever (Formula presented). For functions Hellman gives a weaker attack with S2· T≈ N2 (e.g., S= T≈ N2/3). To prove lower bounds, one considers an adversary who has access to an oracle f: [ N] → [N] and can make T oracle queries. The best known lower bound is S· T∈ Ω(N) and holds for random functions and permutations. We construct functions that provably require more time and/or space to invert. Specifically, for any constant k we construct a function [N] → [N] that cannot be inverted unless Sk· T∈ Ω(Nk) (in particular, S= T≈ (Formula presented). Our construction does not contradict Hellman’s time-memory trade-off, because it cannot be efficiently evaluated in forward direction. However, its entire function table can be computed in time quasilinear in N, which is sufficient for the PoS application. Our simplest construction is built from a random function oracle g: [N] × [N] → [ N] and a random permutation oracle f: [N] → N] and is defined as h(x) = g(x, x′) where f(x) = π(f(x′)) with π being any involution without a fixed point, e.g. flipping all the bits. For this function we prove that any adversary who gets S bits of auxiliary information, makes at most T oracle queries, and inverts h on an ϵ fraction of outputs must satisfy S2· T∈ Ω(ϵ2N2).},
author = {Abusalah, Hamza M and Alwen, Joel F and Cohen, Bram and Khilko, Danylo and Pietrzak, Krzysztof Z and Reyzin, Leonid},
isbn = {978-331970696-2},
location = {Hong Kong, China},
pages = {357 -- 379},
publisher = {Springer},
title = {{Beyond Hellman’s time-memory trade-offs with applications to proofs of space}},
doi = {10.1007/978-3-319-70697-9_13},
volume = {10625},
year = {2017},
}
@inproceedings{1175,
abstract = {We study space complexity and time-space trade-offs with a focus not on peak memory usage but on overall memory consumption throughout the computation. Such a cumulative space measure was introduced for the computational model of parallel black pebbling by [Alwen and Serbinenko ’15] as a tool for obtaining results in cryptography. We consider instead the non- deterministic black-white pebble game and prove optimal cumulative space lower bounds and trade-offs, where in order to minimize pebbling time the space has to remain large during a significant fraction of the pebbling. We also initiate the study of cumulative space in proof complexity, an area where other space complexity measures have been extensively studied during the last 10–15 years. Using and extending the connection between proof complexity and pebble games in [Ben-Sasson and Nordström ’08, ’11] we obtain several strong cumulative space results for (even parallel versions of) the resolution proof system, and outline some possible future directions of study of this, in our opinion, natural and interesting space measure.},
author = {Alwen, Joel F and De Rezende, Susanna and Nordstrom, Jakob and Vinyals, Marc},
editor = {Papadimitriou, Christos},
issn = {18688969},
location = {Berkeley, CA, United States},
pages = {38:1--38--21},
publisher = {Schloss Dagstuhl - Leibniz-Zentrum für Informatik},
title = {{Cumulative space in black-white pebbling and resolution}},
doi = {10.4230/LIPIcs.ITCS.2017.38},
volume = {67},
year = {2017},
}
@inproceedings{640,
abstract = {Data-independent Memory Hard Functions (iMHFS) are finding a growing number of applications in security; especially in the domain of password hashing. An important property of a concrete iMHF is specified by fixing a directed acyclic graph (DAG) Gn on n nodes. The quality of that iMHF is then captured by the following two pebbling complexities of Gn: – The parallel cumulative pebbling complexity Π∥cc(Gn) must be as high as possible (to ensure that the amortized cost of computing the function on dedicated hardware is dominated by the cost of memory). – The sequential space-time pebbling complexity Πst(Gn) should be as close as possible to Π∥cc(Gn) (to ensure that using many cores in parallel and amortizing over many instances does not give much of an advantage). In this paper we construct a family of DAGs with best possible parameters in an asymptotic sense, i.e., where Π∥cc(Gn) = Ω(n2/ log(n)) (which matches a known upper bound) and Πst(Gn) is within a constant factor of Π∥cc(Gn). Our analysis relies on a new connection between the pebbling complexity of a DAG and its depth-robustness (DR) – a well studied combinatorial property. We show that high DR is sufficient for high Π∥cc. Alwen and Blocki (CRYPTO’16) showed that high DR is necessary and so, together, these results fully characterize DAGs with high Π∥cc in terms of DR. Complementing these results, we provide new upper and lower bounds on the Π∥cc of several important candidate iMHFs from the literature. We give the first lower bounds on the memory hardness of the Catena and Balloon Hashing functions in a parallel model of computation and we give the first lower bounds of any kind for (a version) of Argon2i. Finally we describe a new class of pebbling attacks improving on those of Alwen and Blocki (CRYPTO’16). By instantiating these attacks we upperbound the Π∥cc of the Password Hashing Competition winner Argon2i and one of the Balloon Hashing functions by O (n1.71). We also show an upper bound of O(n1.625) for the Catena functions and the two remaining Balloon Hashing functions.},
author = {Alwen, Joel F and Blocki, Jeremiah and Pietrzak, Krzysztof Z},
editor = {Coron, Jean-Sébastien and Buus Nielsen, Jesper},
isbn = {978-331956616-0},
location = {Paris, France},
pages = {3 -- 32},
publisher = {Springer},
title = {{Depth-robust graphs and their cumulative memory complexity}},
doi = {10.1007/978-3-319-56617-7_1},
volume = {10212},
year = {2017},
}
@inproceedings{1176,
abstract = {The algorithm Argon2i-B of Biryukov, Dinu and Khovratovich is currently being considered by the IRTF (Internet Research Task Force) as a new de-facto standard for password hashing. An older version (Argon2i-A) of the same algorithm was chosen as the winner of the recent Password Hashing Competition. An important competitor to Argon2i-B is the recently introduced Balloon Hashing (BH) algorithm of Corrigan-Gibs, Boneh and Schechter. A key security desiderata for any such algorithm is that evaluating it (even using a custom device) requires a large amount of memory amortized across multiple instances. Alwen and Blocki (CRYPTO 2016) introduced a class of theoretical attacks against Argon2i-A and BH. While these attacks yield large asymptotic reductions in the amount of memory, it was not, a priori, clear if (1) they can be extended to the newer Argon2i-B, (2) the attacks are effective on any algorithm for practical parameter ranges (e.g., 1GB of memory) and (3) if they can be effectively instantiated against any algorithm under realistic hardware constrains. In this work we answer all three of these questions in the affirmative for all three algorithms. This is also the first work to analyze the security of Argon2i-B. In more detail, we extend the theoretical attacks of Alwen and Blocki (CRYPTO 2016) to the recent Argon2i-B proposal demonstrating severe asymptotic deficiencies in its security. Next we introduce several novel heuristics for improving the attack's concrete memory efficiency even when on-chip memory bandwidth is bounded. We then simulate our attacks on randomly sampled Argon2i-A, Argon2i-B and BH instances and measure the resulting memory consumption for various practical parameter ranges and for a variety of upperbounds on the amount of parallelism available to the attacker. Finally we describe, implement, and test a new heuristic for applying the Alwen-Blocki attack to functions employing a technique developed by Corrigan-Gibs et al. for improving concrete security of memory-hard functions. We analyze the collected data and show the effects various parameters have on the memory consumption of the attack. In particular, we can draw several interesting conclusions about the level of security provided by these functions. · For the Alwen-Blocki attack to fail against practical memory parameters, Argon2i-B must be instantiated with more than 10 passes on memory - beyond the "paranoid" parameter setting in the current IRTF proposal. · The technique of Corrigan-Gibs for improving security can also be overcome by the Alwen-Blocki attack under realistic hardware constraints. · On a positive note, both the asymptotic and concrete security of Argon2i-B seem to improve on that of Argon2i-A.},
author = {Alwen, Joel F and Blocki, Jeremiah},
isbn = {978-150905761-0},
location = {Paris, France},
publisher = {IEEE},
title = {{Towards practical attacks on Argon2i and balloon hashing}},
doi = {10.1109/EuroSP.2017.47},
year = {2017},
}
@inproceedings{609,
abstract = {Several cryptographic schemes and applications are based on functions that are both reasonably efficient to compute and moderately hard to invert, including client puzzles for Denial-of-Service protection, password protection via salted hashes, or recent proof-of-work blockchain systems. Despite their wide use, a definition of this concept has not yet been distilled and formalized explicitly. Instead, either the applications are proven directly based on the assumptions underlying the function, or some property of the function is proven, but the security of the application is argued only informally. The goal of this work is to provide a (universal) definition that decouples the efforts of designing new moderately hard functions and of building protocols based on them, serving as an interface between the two. On a technical level, beyond the mentioned definitions, we instantiate the model for four different notions of hardness. We extend the work of Alwen and Serbinenko (STOC 2015) by providing a general tool for proving security for the first notion of memory-hard functions that allows for provably secure applications. The tool allows us to recover all of the graph-theoretic techniques developed for proving security under the older, non-composable, notion of security used by Alwen and Serbinenko. As an application of our definition of moderately hard functions, we prove the security of two different schemes for proofs of effort (PoE). We also formalize and instantiate the concept of a non-interactive proof of effort (niPoE), in which the proof is not bound to a particular communication context but rather any bit-string chosen by the prover.},
author = {Alwen, Joel F and Tackmann, Björn},
editor = {Kalai, Yael and Reyzin, Leonid},
isbn = {978-331970499-9},
location = {Baltimore, MD, United States},
pages = {493 -- 526},
publisher = {Springer},
title = {{Moderately hard functions: Definition, instantiations, and applications}},
doi = {10.1007/978-3-319-70500-2_17},
volume = {10677},
year = {2017},
}
@inproceedings{635,
abstract = {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 Ω(n2w), 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’15) which implies high memory cost even for adversaries who can amortize 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’16) who proved a weaker lower bound of Ω(n2w/ log2 n) for a restricted class of adversaries.},
author = {Alwen, Joel F and Chen, Binchi and Pietrzak, Krzysztof Z and Reyzin, Leonid and Tessaro, Stefano},
editor = {Coron, Jean-Sébastien and Buus Nielsen, Jesper},
isbn = {978-331956616-0},
location = {Paris, France},
pages = {33 -- 62},
publisher = {Springer},
title = {{Scrypt is maximally memory hard}},
doi = {10.1007/978-3-319-56617-7_2},
volume = {10212},
year = {2017},
}
@inproceedings{1231,
abstract = {We study the time-and memory-complexities of the problem of computing labels of (multiple) randomly selected challenge-nodes in a directed acyclic graph. The w-bit label of a node is the hash of the labels of its parents, and the hash function is modeled as a random oracle. Specific instances of this problem underlie both proofs of space [Dziembowski et al. CRYPTO’15] as well as popular memory-hard functions like scrypt. As our main tool, we introduce the new notion of a probabilistic parallel entangled pebbling game, a new type of combinatorial pebbling game on a graph, which is closely related to the labeling game on the same graph. As a first application of our framework, we prove that for scrypt, when the underlying hash function is invoked n times, the cumulative memory complexity (CMC) (a notion recently introduced by Alwen and Serbinenko (STOC’15) to capture amortized memory-hardness for parallel adversaries) is at least Ω(w · (n/ log(n))2). This bound holds for adversaries that can store many natural functions of the labels (e.g., linear combinations), but still not arbitrary functions thereof. We then introduce and study a combinatorial quantity, and show how a sufficiently small upper bound on it (which we conjecture) extends our CMC bound for scrypt to hold against arbitrary adversaries. We also show that such an upper bound solves the main open problem for proofs-of-space protocols: namely, establishing that the 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 black pebbling on the same graph (given an initial k-node pebbling).},
author = {Alwen, Joel F and Chen, Binyi and Kamath Hosdurg, Chethan and Kolmogorov, Vladimir and Pietrzak, Krzysztof Z and Tessaro, Stefano},
location = {Vienna, Austria},
pages = {358 -- 387},
publisher = {Springer},
title = {{On the complexity of scrypt and proofs of space in the parallel random oracle model}},
doi = {10.1007/978-3-662-49896-5_13},
volume = {9666},
year = {2016},
}
@inproceedings{1365,
abstract = {A memory-hard function (MHF) f is equipped with a space cost σ and time cost τ parameter such that repeatedly computing fσ,τ on an application specific integrated circuit (ASIC) is not economically advantageous relative to a general purpose computer. Technically we would like that any (generalized) circuit for evaluating an iMHF fσ,τ has area × time (AT) complexity at Θ(σ2 ∗ τ). A data-independent MHF (iMHF) has the added property that it can be computed with almost optimal memory and time complexity by an algorithm which accesses memory in a pattern independent of the input value. Such functions can be specified by fixing a directed acyclic graph (DAG) G on n = Θ(σ ∗ τ) nodes representing its computation graph. In this work we develop new tools for analyzing iMHFs. First we define and motivate a new complexity measure capturing the amount of energy (i.e. electricity) required to compute a function. We argue that, in practice, this measure is at least as important as the more traditional AT-complexity. Next we describe an algorithm A for repeatedly evaluating an iMHF based on an arbitrary DAG G. We upperbound both its energy and AT complexities per instance evaluated in terms of a certain combinatorial property of G. Next we instantiate our attack for several general classes of DAGs which include those underlying many of the most important iMHF candidates in the literature. In particular, we obtain the following results which hold for all choices of parameters σ and τ (and thread-count) such that n = σ ∗ τ. -The Catena-Dragonfly function of [FLW13] has AT and energy complexities O(n1.67). -The Catena-Butterfly function of [FLW13] has complexities is O(n1.67). -The Double-Buffer and the Linear functions of [CGBS16] both have complexities in O(n1.67). -The Argon2i function of [BDK15] (winner of the Password Hashing Competition [PHC]) has complexities O(n7/4 log(n)). -The Single-Buffer function of [CGBS16] has complexities O(n7/4 log(n)). -Any iMHF can be computed by an algorithm with complexities O(n2/ log1 −ε(n)) for all ε > 0. In particular when τ = 1 this shows that the goal of constructing an iMHF with AT-complexity Θ(σ2 ∗ τ ) is unachievable. Along the way we prove a lemma upper-bounding the depth-robustness of any DAG which may prove to be of independent interest.},
author = {Alwen, Joel F and Blocki, Jeremiah},
location = {Santa Barbara, CA, USA},
pages = {241 -- 271},
publisher = {Springer},
title = {{Efficiently computing data-independent memory-hard functions}},
doi = {10.1007/978-3-662-53008-5_9},
volume = {9815},
year = {2016},
}
@inproceedings{1652,
abstract = {We develop new theoretical tools for proving lower-bounds on the (amortized) complexity of certain functions in models of parallel computation. We apply the tools to construct a class of functions with high amortized memory complexity in the parallel Random Oracle Model (pROM); a variant of the standard ROM allowing for batches of simultaneous queries. In particular we obtain a new, more robust, type of Memory-Hard Functions (MHF); a security primitive which has recently been gaining acceptance in practice as an effective means of countering brute-force attacks on security relevant functions. Along the way we also demonstrate an important shortcoming of previous definitions of MHFs and give a new definition addressing the problem. The tools we develop represent an adaptation of the powerful pebbling paradigm (initially introduced by Hewitt and Paterson [HP70] and Cook [Coo73]) to a simple and intuitive parallel setting. We define a simple pebbling game Gp over graphs which aims to abstract parallel computation in an intuitive way. As a conceptual contribution we define a measure of pebbling complexity for graphs called cumulative complexity (CC) and show how it overcomes a crucial shortcoming (in the parallel setting) exhibited by more traditional complexity measures used in the past. As a main technical contribution we give an explicit construction of a constant in-degree family of graphs whose CC in Gp approaches maximality to within a polylogarithmic factor for any graph of equal size (analogous to the graphs of Tarjan et. al. [PTC76, LT82] for sequential pebbling games). Finally, for a given graph G and related function fG, we derive a lower-bound on the amortized memory complexity of fG in the pROM in terms of the CC of G in the game Gp.},
author = {Alwen, Joel F and Serbinenko, Vladimir},
booktitle = {Proceedings of the 47th annual ACM symposium on Theory of computing},
location = {Portland, OR, United States},
pages = {595 -- 603},
publisher = {ACM},
title = {{High parallel complexity graphs and memory-hard functions}},
doi = {10.1145/2746539.2746622},
year = {2015},
}
@inproceedings{1672,
abstract = {Composable notions of incoercibility aim to forbid a coercer from using anything beyond the coerced parties’ inputs and outputs to catch them when they try to deceive him. Existing definitions are restricted to weak coercion types, and/or are not universally composable. Furthermore, they often make too strong assumptions on the knowledge of coerced parties—e.g., they assume they known the identities and/or the strategies of other coerced parties, or those of corrupted parties— which makes them unsuitable for applications of incoercibility such as e-voting, where colluding adversarial parties may attempt to coerce honest voters, e.g., by offering them money for a promised vote, and use their own view to check that the voter keeps his end of the bargain. In this work we put forward the first universally composable notion of incoercible multi-party computation, which satisfies the above intuition and does not assume collusions among coerced parties or knowledge of the corrupted set. We define natural notions of UC incoercibility corresponding to standard coercion-types, i.e., receipt-freeness and resistance to full-active coercion. Importantly, our suggested notion has the unique property that it builds on top of the well studied UC framework by Canetti instead of modifying it. This guarantees backwards compatibility, and allows us to inherit results from the rich UC literature. We then present MPC protocols which realize our notions of UC incoercibility given access to an arguably minimal setup—namely honestly generate tamper-proof hardware performing a very simple cryptographic operation—e.g., a smart card. This is, to our knowledge, the first proposed construction of an MPC protocol (for more than two parties) that is incoercibly secure and universally composable, and therefore the first construction of a universally composable receipt-free e-voting protocol.},
author = {Alwen, Joel F and Ostrovsky, Rafail and Zhou, Hongsheng and Zikas, Vassilis},
location = {Santa Barbara, CA, United States},
pages = {763 -- 780},
publisher = {Springer},
title = {{Incoercible multi-party computation and universally composable receipt-free voting}},
doi = {10.1007/978-3-662-48000-7_37},
volume = {9216},
year = {2015},
}
@inproceedings{2259,
abstract = {The learning with rounding (LWR) problem, introduced by Banerjee, Peikert and Rosen at EUROCRYPT ’12, is a variant of learning with errors (LWE), where one replaces random errors with deterministic rounding. The LWR problem was shown to be as hard as LWE for a setting of parameters where the modulus and modulus-to-error ratio are super-polynomial. In this work we resolve the main open problem and give a new reduction that works for a larger range of parameters, allowing for a polynomial modulus and modulus-to-error ratio. In particular, a smaller modulus gives us greater efficiency, and a smaller modulus-to-error ratio gives us greater security, which now follows from the worst-case hardness of GapSVP with polynomial (rather than super-polynomial) approximation factors.
As a tool in the reduction, we show that there is a “lossy mode” for the LWR problem, in which LWR samples only reveal partial information about the secret. This property gives us several interesting new applications, including a proof that LWR remains secure with weakly random secrets of sufficient min-entropy, and very simple constructions of deterministic encryption, lossy trapdoor functions and reusable extractors.
Our approach is inspired by a technique of Goldwasser et al. from ICS ’10, which implicitly showed the existence of a “lossy mode” for LWE. By refining this technique, we also improve on the parameters of that work to only requiring a polynomial (instead of super-polynomial) modulus and modulus-to-error ratio.
},
author = {Alwen, Joel F and Krenn, Stephan and Pietrzak, Krzysztof Z and Wichs, Daniel},
location = {Santa Barbara, CA, United States},
number = {1},
pages = {57 -- 74},
publisher = {Springer},
title = {{Learning with rounding, revisited: New reduction properties and applications}},
doi = {10.1007/978-3-642-40041-4_4},
volume = {8042},
year = {2013},
}