Cryptographic Assumptions: a Position Paper
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The Strongish Planted Clique Hypothesis and Its Consequences
The Strongish Planted Clique Hypothesis and Its Consequences Pasin Manurangsi Google Research, Mountain View, CA, USA [email protected] Aviad Rubinstein Stanford University, CA, USA [email protected] Tselil Schramm Stanford University, CA, USA [email protected] Abstract We formulate a new hardness assumption, the Strongish Planted Clique Hypothesis (SPCH), which postulates that any algorithm for planted clique must run in time nΩ(log n) (so that the state-of-the-art running time of nO(log n) is optimal up to a constant in the exponent). We provide two sets of applications of the new hypothesis. First, we show that SPCH implies (nearly) tight inapproximability results for the following well-studied problems in terms of the parameter k: Densest k-Subgraph, Smallest k-Edge Subgraph, Densest k-Subhypergraph, Steiner k-Forest, and Directed Steiner Network with k terminal pairs. For example, we show, under SPCH, that no polynomial time algorithm achieves o(k)-approximation for Densest k-Subgraph. This inapproximability ratio improves upon the previous best ko(1) factor from (Chalermsook et al., FOCS 2017). Furthermore, our lower bounds hold even against fixed-parameter tractable algorithms with parameter k. Our second application focuses on the complexity of graph pattern detection. For both induced and non-induced graph pattern detection, we prove hardness results under SPCH, improving the running time lower bounds obtained by (Dalirrooyfard et al., STOC 2019) under the Exponential Time Hypothesis. 2012 ACM Subject Classification Theory of computation → Problems, reductions and completeness; Theory of computation → Fixed parameter tractability Keywords and phrases Planted Clique, Densest k-Subgraph, Hardness of Approximation Digital Object Identifier 10.4230/LIPIcs.ITCS.2021.10 Related Version A full version of the paper is available at https://arxiv.org/abs/2011.05555. -
Concurrent Non-Malleable Zero Knowledge Proofs
Concurrent Non-Malleable Zero Knowledge Proofs Huijia Lin?, Rafael Pass??, Wei-Lung Dustin Tseng???, and Muthuramakrishnan Venkitasubramaniam Cornell University, {huijia,rafael,wdtseng,vmuthu}@cs.cornell.edu Abstract. Concurrent non-malleable zero-knowledge (NMZK) consid- ers the concurrent execution of zero-knowledge protocols in a setting where the attacker can simultaneously corrupt multiple provers and ver- ifiers. Barak, Prabhakaran and Sahai (FOCS’06) recently provided the first construction of a concurrent NMZK protocol without any set-up assumptions. Their protocol, however, is only computationally sound (a.k.a., a concurrent NMZK argument). In this work we present the first construction of a concurrent NMZK proof without any set-up assump- tions. Our protocol requires poly(n) rounds assuming one-way functions, or O~(log n) rounds assuming collision-resistant hash functions. As an additional contribution, we improve the round complexity of con- current NMZK arguments based on one-way functions (from poly(n) to O~(log n)), and achieve a near linear (instead of cubic) security reduc- tions. Taken together, our results close the gap between concurrent ZK protocols and concurrent NMZK protocols (in terms of feasibility, round complexity, hardness assumptions, and tightness of the security reduc- tion). 1 Introduction Zero-knowledge (ZK) interactive proofs [GMR89] are fundamental constructs that allow the Prover to convince the Verifier of the validity of a mathematical statement x 2 L, while providing zero additional knowledge to the Verifier. Con- current ZK, first introduced and achieved by Dwork, Naor and Sahai [DNS04], considers the execution of zero-knowledge protocols in an asynchronous and con- current setting. -
FOCS 2005 Program SUNDAY October 23, 2005
FOCS 2005 Program SUNDAY October 23, 2005 Talks in Grand Ballroom, 17th floor Session 1: 8:50am – 10:10am Chair: Eva´ Tardos 8:50 Agnostically Learning Halfspaces Adam Kalai, Adam Klivans, Yishay Mansour and Rocco Servedio 9:10 Noise stability of functions with low influences: invari- ance and optimality The 46th Annual IEEE Symposium on Elchanan Mossel, Ryan O’Donnell and Krzysztof Foundations of Computer Science Oleszkiewicz October 22-25, 2005 Omni William Penn Hotel, 9:30 Every decision tree has an influential variable Pittsburgh, PA Ryan O’Donnell, Michael Saks, Oded Schramm and Rocco Servedio Sponsored by the IEEE Computer Society Technical Committee on Mathematical Foundations of Computing 9:50 Lower Bounds for the Noisy Broadcast Problem In cooperation with ACM SIGACT Navin Goyal, Guy Kindler and Michael Saks Break 10:10am – 10:30am FOCS ’05 gratefully acknowledges financial support from Microsoft Research, Yahoo! Research, and the CMU Aladdin center Session 2: 10:30am – 12:10pm Chair: Satish Rao SATURDAY October 22, 2005 10:30 The Unique Games Conjecture, Integrality Gap for Cut Problems and Embeddability of Negative Type Metrics Tutorials held at CMU University Center into `1 [Best paper award] Reception at Omni William Penn Hotel, Monongahela Room, Subhash Khot and Nisheeth Vishnoi 17th floor 10:50 The Closest Substring problem with small distances Tutorial 1: 1:30pm – 3:30pm Daniel Marx (McConomy Auditorium) Chair: Irit Dinur 11:10 Fitting tree metrics: Hierarchical clustering and Phy- logeny Subhash Khot Nir Ailon and Moses Charikar On the Unique Games Conjecture 11:30 Metric Embeddings with Relaxed Guarantees Break 3:30pm – 4:00pm Ittai Abraham, Yair Bartal, T-H. -
Garbled Protocols and Two-Round MPC from Bilinear Maps
58th Annual IEEE Symposium on Foundations of Computer Science Garbled Protocols and Two-Round MPC from Bilinear Maps Sanjam Garg Akshayaram Srinivasan Dept. of Computer Science Dept. of Computer Science University of California, Berkeley University of California, Berkeley Berkeley, USA Berkeley, USA Email: [email protected] Email: [email protected] Abstract—In this paper, we initiate the study of garbled (OT) protocol [57], [2], [51], [40] gives an easy solution to protocols — a generalization of Yao’s garbled circuits construc- the problem of (semi-honest) two-round secure computation tion to distributed protocols. More specifically, in a garbled in the two-party setting. However, the same problem for protocol construction, each party can independently generate a garbled protocol component along with pairs of input the multiparty setting turns out to be much harder. Beaver, labels. Additionally, it generates an encoding of its input. The Micali and Rogaway [7] show that garbled circuits can be evaluation procedure takes as input the set of all garbled used to realize a constant round multi-party computation protocol components and the labels corresponding to the input protocol. However, unlike the two-party case, this protocol encodings of all parties and outputs the entire transcript of the is not two rounds. distributed protocol. We provide constructions for garbling arbitrary protocols A. Garbled Protocols based on standard computational assumptions on bilinear maps (in the common random string model). Next, using In this paper, we introduce a generalization of Yao’s garbled protocols we obtain a general compiler that compresses construction from circuits to distributed protocols. We next any arbitrary round multiparty secure computation protocol elaborate on (i) what it means to garble a protocol, (ii) why into a two-round UC secure protocol. -
Onyx: New Encryption and Signature Schemes with Multivariate Public Key in Degree 3
Onyx: New Encryption and Signature Schemes with Multivariate Public Key in Degree 3 Gilles Macario-Rat1 and Jacques Patarin2 1 Orange, Orange Gardens, 46 avenue de la R´epublique,F-92320 Ch^atillon,France [email protected] 2 Versailles Laboratory of Mathematics, UVSQ, CNRS, University of Paris-Saclay [email protected] Abstract. In this paper, we present a new secret trapdoor function for the design of multivariate schemes that we call \Onyx", suitable for en- cryption and signature. It has been inspired by the schemes presented in [19,20]. From this idea, we present some efficient encryption and signa- ture multivariate schemes with explicit parameters that resist all known attacks. In particular they resist the two main (and often very power- ful) attacks in this area: the Gr¨obner attacks (to compute a solution of the system derived from the public key) and the MinRank attacks (to recover the secret key). Specific attacks due to the properties of the function and its differential are also addressed in this paper. The \Onyx" schemes have public key equations of degree 3. Despite this, the size of the public key may still be reasonable since we can use larger fields and smaller extension degrees. Onyx signatures can be as short as the \birth- day paradox" allows, i.e. twice the security level, or even shorter thanks to the Feistel-Patarin construction, like many other signatures schemes based on multivariate equations. Keywords: public-key cryptography, post-quantum multivariate cryptography, UOV, HFE, Gr¨obnerbasis, MinRank problem, differential attacks. 1 Introduction Many schemes in Multivariate cryptography have been broken. -
Magic Adversaries Versus Individual Reduction: Science Wins Either Way ?
Magic Adversaries Versus Individual Reduction: Science Wins Either Way ? Yi Deng1;2 1 SKLOIS, Institute of Information Engineering, CAS, Beijing, P.R.China 2 State Key Laboratory of Cryptology, P. O. Box 5159, Beijing ,100878,China [email protected] Abstract. We prove that, assuming there exists an injective one-way function f, at least one of the following statements is true: – (Infinitely-often) Non-uniform public-key encryption and key agreement exist; – The Feige-Shamir protocol instantiated with f is distributional concurrent zero knowledge for a large class of distributions over any OR NP-relations with small distinguishability gap. The questions of whether we can achieve these goals are known to be subject to black-box lim- itations. Our win-win result also establishes an unexpected connection between the complexity of public-key encryption and the round-complexity of concurrent zero knowledge. As the main technical contribution, we introduce a dissection procedure for concurrent ad- versaries, which enables us to transform a magic concurrent adversary that breaks the distribu- tional concurrent zero knowledge of the Feige-Shamir protocol into non-black-box construc- tions of (infinitely-often) public-key encryption and key agreement. This dissection of complex algorithms gives insight into the fundamental gap between the known universal security reductions/simulations, in which a single reduction algorithm or simu- lator works for all adversaries, and the natural security definitions (that are sufficient for almost all cryptographic primitives/protocols), which switch the order of qualifiers and only require that for every adversary there exists an individual reduction or simulator. 1 Introduction The seminal work of Impagliazzo and Rudich [IR89] provides a methodology for studying the lim- itations of black-box reductions. -
Approximating Cumulative Pebbling Cost Is Unique Games Hard
Approximating Cumulative Pebbling Cost Is Unique Games Hard Jeremiah Blocki Department of Computer Science, Purdue University, West Lafayette, IN, USA https://www.cs.purdue.edu/homes/jblocki [email protected] Seunghoon Lee Department of Computer Science, Purdue University, West Lafayette, IN, USA https://www.cs.purdue.edu/homes/lee2856 [email protected] Samson Zhou School of Computer Science, Carnegie Mellon University, Pittsburgh, PA, USA https://samsonzhou.github.io/ [email protected] Abstract P The cumulative pebbling complexity of a directed acyclic graph G is defined as cc(G) = minP i |Pi|, where the minimum is taken over all legal (parallel) black pebblings of G and |Pi| denotes the number of pebbles on the graph during round i. Intuitively, cc(G) captures the amortized Space-Time complexity of pebbling m copies of G in parallel. The cumulative pebbling complexity of a graph G is of particular interest in the field of cryptography as cc(G) is tightly related to the amortized Area-Time complexity of the Data-Independent Memory-Hard Function (iMHF) fG,H [7] defined using a constant indegree directed acyclic graph (DAG) G and a random oracle H(·). A secure iMHF should have amortized Space-Time complexity as high as possible, e.g., to deter brute-force password attacker who wants to find x such that fG,H (x) = h. Thus, to analyze the (in)security of a candidate iMHF fG,H , it is crucial to estimate the value cc(G) but currently, upper and lower bounds for leading iMHF candidates differ by several orders of magnitude. Blocki and Zhou recently showed that it is NP-Hard to compute cc(G), but their techniques do not even rule out an efficient (1 + ε)-approximation algorithm for any constant ε > 0. -
A New Point of NP-Hardness for Unique Games
A new point of NP-hardness for Unique Games Ryan O'Donnell∗ John Wrighty September 30, 2012 Abstract 1 3 We show that distinguishing 2 -satisfiable Unique-Games instances from ( 8 + )-satisfiable instances is NP-hard (for all > 0). A consequence is that we match or improve the best known c vs. s NP-hardness result for Unique-Games for all values of c (except for c very close to 0). For these c, ours is the first hardness result showing that it helps to take the alphabet size larger than 2. Our NP-hardness reductions are quasilinear-size and thus show nearly full exponential time is required, assuming the ETH. ∗Department of Computer Science, Carnegie Mellon University. Supported by NSF grants CCF-0747250 and CCF-0915893, and by a Sloan fellowship. Some of this research performed while the author was a von Neumann Fellow at the Institute for Advanced Study, supported by NSF grants DMS-083537 and CCF-0832797. yDepartment of Computer Science, Carnegie Mellon University. 1 Introduction Thanks largely to the groundbreaking work of H˚astad[H˚as01], we have optimal NP-hardness of approximation results for several constraint satisfaction problems (CSPs), including 3Lin(Z2) and 3Sat. But for many others | including most interesting CSPs with 2-variable constraints | we lack matching algorithmic and NP-hardness results. Take the 2Lin(Z2) problem for example, in which there are Boolean variables with constraints of the form \xi = xj" and \xi 6= xj". The largest approximation ratio known to be achievable in polynomial time is roughly :878 [GW95], whereas it 11 is only known that achieving ratios above 12 ≈ :917 is NP-hard [H˚as01, TSSW00]. -
Data Structures Meet Cryptography: 3SUM with Preprocessing
Data Structures Meet Cryptography: 3SUM with Preprocessing Alexander Golovnev Siyao Guo Thibaut Horel Harvard NYU Shanghai MIT [email protected] [email protected] [email protected] Sunoo Park Vinod Vaikuntanathan MIT & Harvard MIT [email protected] [email protected] Abstract This paper shows several connections between data structure problems and cryptography against preprocessing attacks. Our results span data structure upper bounds, cryptographic applications, and data structure lower bounds, as summarized next. First, we apply Fiat–Naor inversion, a technique with cryptographic origins, to obtain a data structure upper bound. In particular, our technique yields a suite of algorithms with space S and (online) time T for a preprocessing version of the N-input 3SUM problem where S3 T = O(N 6). This disproves a strong conjecture (Goldstein et al., WADS 2017) that there is no data· structure − − that solves this problem for S = N 2 δ and T = N 1 δ for any constant δ > 0. e Secondly, we show equivalence between lower bounds for a broad class of (static) data struc- ture problems and one-way functions in the random oracle model that resist a very strong form of preprocessing attack. Concretely, given a random function F :[N] [N] (accessed as an oracle) we show how to compile it into a function GF :[N 2] [N 2] which→ resists S-bit prepro- cessing attacks that run in query time T where ST = O(N 2−→ε) (assuming a corresponding data structure lower bound on 3SUM). In contrast, a classical result of Hellman tells us that F itself can be more easily inverted, say with N 2/3-bit preprocessing in N 2/3 time. -
CURRICULUM VITAE Rafail Ostrovsky
last updated: December 26, 2020 CURRICULUM VITAE Rafail Ostrovsky Distinguished Professor of Computer Science and Mathematics, UCLA http://www.cs.ucla.edu/∼rafail/ mailing address: Contact information: UCLA Computer Science Department Phone: (310) 206-5283 475 ENGINEERING VI, E-mail: [email protected] Los Angeles, CA, 90095-1596 Research • Cryptography and Computer Security; Interests • Streaming Algorithms; Routing and Network Algorithms; • Search and Classification Problems on High-Dimensional Data. Education NSF Mathematical Sciences Postdoctoral Research Fellow Conducted at U.C. Berkeley 1992-95. Host: Prof. Manuel Blum. Ph.D. in Computer Science, Massachusetts Institute of Technology, 1989-92. • Thesis titled: \Software Protection and Simulation on Oblivious RAMs", Ph.D. advisor: Prof. Silvio Micali. Final version appeared in Journal of ACM, 1996. Practical applications of thesis work appeared in U.S. Patent No.5,123,045. • Minor: \Management and Technology", M.I.T. Sloan School of Management. M.S. in Computer Science, Boston University, 1985-87. B.A. Magna Cum Laude in Mathematics, State University of New York at Buffalo, 1980-84. Department of Mathematics Graduation Honors: With highest distinction. Personal • U.S. citizen, naturalized in Boston, MA, 1986. Data Appointments UCLA Computer Science Department (2003 { present): Distinguished Professor of Computer Science. Recruited in 2003 as a Full Professor with Tenure. UCLA School of Engineering (2003 { present): Director, Center for Information and Computation Security. (See http://www.cs.ucla.edu/security/.) UCLA Department of Mathematics (2006 { present): Distinguished Professor of Mathematics (by courtesy). 1 Appointments Bell Communications Research (Bellcore) (cont.) (1999 { 2003): Senior Research Scientist; (1995 { 1999): Research Scientist, Mathematics and Cryptography Research Group, Applied Research. -
Research Statement
RESEARCH STATEMENT SAM HOPKINS Introduction The last decade has seen enormous improvements in the practice, prevalence, and usefulness of machine learning. Deep nets give our phones ears; matrix completion gives our televisions good taste. Data-driven articial intelligence has become capable of the dicult—driving a car on a highway—and the nearly impossible—distinguishing cat pictures without human intervention [18]. This is the stu of science ction. But we are far behind in explaining why many algorithms— even now-commonplace ones for relatively elementary tasks—work so stunningly well as they do in the wild. In general, we can prove very little about the performance of these algorithms; in many cases provable performance guarantees for them appear to be beyond attack by our best proof techniques. This means that our current-best explanations for how such algorithms can be so successful resort eventually to (intelligent) guesswork and heuristic analysis. This is not only a problem for our intellectual honesty. As machine learning shows up in more and more mission- critical applications it is essential that we understand the guarantees and limits of our approaches with the certainty aorded only by rigorous mathematical analysis. The theory-of-computing community is only beginning to equip itself with the tools to make rigorous attacks on learning problems. The sophisticated learning pipelines used in practice are built layer-by-layer from simpler fundamental statistical inference algorithms. We can address these statistical inference problems rigorously, but only by rst landing on tractable problem de- nitions. In their traditional theory-of-computing formulations, many of these inference problems have intractable worst-case instances. -
Adversarial Robustness of Streaming Algorithms Through Importance Sampling
Adversarial Robustness of Streaming Algorithms through Importance Sampling Vladimir Braverman Avinatan Hassidim Yossi Matias Mariano Schain Google∗ Googley Googlez Googlex Sandeep Silwal Samson Zhou MITO CMU{ June 30, 2021 Abstract Robustness against adversarial attacks has recently been at the forefront of algorithmic design for machine learning tasks. In the adversarial streaming model, an adversary gives an algorithm a sequence of adaptively chosen updates u1; : : : ; un as a data stream. The goal of the algorithm is to compute or approximate some predetermined function for every prefix of the adversarial stream, but the adversary may generate future updates based on previous outputs of the algorithm. In particular, the adversary may gradually learn the random bits internally used by an algorithm to manipulate dependencies in the input. This is especially problematic as many important problems in the streaming model require randomized algorithms, as they are known to not admit any deterministic algorithms that use sublinear space. In this paper, we introduce adversarially robust streaming algorithms for central machine learning and algorithmic tasks, such as regression and clustering, as well as their more general counterparts, subspace embedding, low-rank approximation, and coreset construction. For regression and other numerical linear algebra related tasks, we consider the row arrival streaming model. Our results are based on a simple, but powerful, observation that many importance sampling-based algorithms give rise to adversarial robustness which is in contrast to sketching based algorithms, which are very prevalent in the streaming literature but suffer from adversarial attacks. In addition, we show that the well-known merge and reduce paradigm in streaming is adversarially robust.