Is Information-Theoretic Topology-Hiding Computation Possible?

Topology-hiding computation (THC) is a form of multi-party computation over an incomplete communication graph that maintains the privacy of the underlying graph topology. Existing THC protocols consider an adversary that may corrupt an arbitrary number of parties, and rely on cryptographic assumptions such as DDH. In this paper we address the question of whether information-theoretic THC can be achieved by taking advantage of an honest majority. In contrast to the standard MPC setting, this problem has remained open in the topology-hiding realm, even for simple privacy-free functions like broadcast, and even when considering only semi-honest corruptions. We uncover a rich landscape of both positive and negative answers to the above question, showing that what types of graphs are used and how they are selected is an important factor in determining the feasibility of hiding topology information-theoretically. In particular, our results include the following. We show that topology-hiding broadcast (THB) on a line with four nodes, secure against a single semi-honest corruption, implies key agreement. This result extends to broader classes of graphs, e.g., THB on a cycle with two semi-honest corruptions. On the other hand, we provide the first feasibility result for information-theoretic THC: for the class of cycle graphs, with a single semi-honest corruption. Given the strong impossibilities, we put forth a weaker definition of distributional-THC, where the graph is selected from some distribution (as opposed to worst-case). We present a formal separation between the definitions, by showing a distribution for which information theoretic distributional-THC is possible, but even topology-hiding broadcast is not possible information-theoretically with the standard definition. We demonstrate the power of our new definition via a new connection to adaptively secure low-locality MPC, where distributional-THC enables parties to reuse a secret low-degree communication graph even in the face of adaptive corruptions

Linear and non-linear dependencies between copy number aberrations and mRNA expression reveal distinct molecular pathways in breast cancer

<p>Abstract</p> <p>Background</p> <p>Elucidating the exact relationship between gene copy number and expression would enable identification of regulatory mechanisms of abnormal gene expression and biological pathways of regulation. Most current approaches either depend on linear correlation or on nonparametric tests of association that are insensitive to the exact shape of the relationship. Based on knowledge of enzyme kinetics and gene regulation, we would expect the functional shape of the relationship to be gene dependent and to be related to the gene regulatory mechanisms involved. Here, we propose a statistical approach to investigate and distinguish between linear and nonlinear dependences between DNA copy number alteration and mRNA expression.</p> <p>Results</p> <p>We applied the proposed method to DNA copy numbers derived from Illumina 109 K SNP-CGH arrays (using the log R values) and expression data from Agilent 44 K mRNA arrays, focusing on commonly aberrated genomic loci in a collection of 102 breast tumors. Regression analysis was used to identify the type of relationship (linear or nonlinear), and subsequent pathway analysis revealed that genes displaying a linear relationship were overall associated with substantially different biological processes than genes displaying a nonlinear relationship. In the group of genes with a linear relationship, we found significant association to canonical pathways, including purine and pyrimidine metabolism (for both deletions and amplifications) as well as estrogen metabolism (linear amplification) and BRCA-related response to damage (linear deletion). In the group of genes displaying a nonlinear relationship, the top canonical pathways were specific pathways like PTEN and PI13K/AKT (nonlinear amplification) and Wnt(B) and IL-2 signalling (nonlinear deletion). Both amplifications and deletions pointed to the same affected pathways and identified cancer as the top significant disease and cell cycle, cell signaling and cellular development as significant networks.</p> <p>Conclusions</p> <p>This paper presents a novel approach to assessing the validity of the dependence of expression data on copy number data, and this approach may help in identifying the drivers of carcinogenesis.</p

Leakage Resilient Secret Sharing and Applications

A secret sharing scheme allows a dealer to share a secret among a set of $n$ parties such that any authorized subset of the parties can recover the secret, while any unauthorized subset of the parties learns no information about the secret. A local leakage-resilient secret sharing scheme (introduced in independent works by (Goyal and Kumar, STOC 18) and (Benhamouda, Degwekar, Ishai and Rabin, Crypto 18)) additionally requires the secrecy to hold against every unauthorized set of parties even if they obtain some bounded local leakage from every other share. The leakage is said to be local if it is computed independently for each share. So far, the only known constructions of local leakage resilient secret sharing schemes are for threshold access structures for very low ($O(1)$) or very high ($n -o(\log n)$) thresholds. In this work, we give a compiler that takes a secret sharing scheme for any monotone access structure and produces a local leakage resilient secret sharing scheme for the same access structure, with only a constant-factor blow-up in the sizes of the shares. Furthermore, the resultant secret sharing scheme has optimal leakage-resilience rate i.e., the ratio between the leakage tolerated and the size of each share can be made arbitrarily close to $1$. Using this secret sharing scheme as the main building block, we obtain the following results: 1. Rate Preserving Non-Malleable Secret Sharing: We give a compiler that takes any secret sharing scheme for a 4-monotone access structure with rate $R$ and converts it into a non-malleable secret sharing scheme for the same access structure with rate $\Omega(R)$. The prior such non-zero rate construction (Badrinarayanan and Srinivasan, 18) only achieves a rate of $\Theta(R/{t_{\max}\log^2 n})$, where $t_{\max}$ is the maximum size of any minimal set in the access structure. As a special case, for any threshold $t \geq 4$ and an arbitrary $n \geq t$, we get the first constant rate construction of $t$-out-of-$n$ non-malleable secret sharing. 2. Leakage-Tolerant Multiparty Computation for General Interaction Pattern: For any function, we give a reduction from constructing leakage-tolerant secure multi-party computation protocols obeying any interaction pattern to constructing a secure (and not necessarily leakage-tolerant) protocol for a related function obeying the star interaction pattern. This improves upon the result of (Halevi et al., ITCS 2016), who constructed a protocol that is secure in a leak-free environment

Unifying Leakage Models: From Probing Attacks to Noisy Leakage

A recent trend in cryptography is to formally show the leakage resilience of cryptographic implementations in a given leakage model. One of the most prominent leakage models -- the so-called bounded leakage model -- assumes that the amount of leakage is a-priori bounded. Unfortunately, it has been pointed out that the assumption of bounded leakages is hard to verify in practice. A more realistic assumption is to assume that leakages are sufficiently noisy, following the engineering observation that real-world physical leakages are inherently noisy. While the noisy leakage assumption has first been studied in the seminal work of Chari et al. (CRYPTO 99), the recent work of Prouff and Rivain (Eurocrypt 2013) provides the first analysis of a full masking scheme under a physically motivated noise model. In particular, the authors show that a block-cipher implementation that uses an additive masking scheme is secure against noisy leakages. Unfortunately, the security analysis of Prouff and Rivain has three important shortcomings: (1) it requires leak-free gates, (2) it considers a restricted adversarial model (random message attacks), and (3) the security proof has limited application for cryptographic settings. In this work, we provide an alternative security proof in the same noisy model that overcomes these three challenges. We achieve this goal by a new reduction from noisy leakage to the important theoretical model of probing adversaries (Ishai et al~ -- CRYPTO 2003). Our work can be viewed as a next step of closing the gap between theory and practice in leakage resilient cryptography: while our security proofs heavily rely on concepts of theoretical cryptography, we solve problems in practically motivated leakage models

Tight Leakage-Resilient CCA-Security from Quasi-Adaptive Hash Proof System

We propose the concept of quasi-adaptive hash proof system (QAHPS), where the projection key is allowed to depend on the specific language for which hash values are computed. We formalize leakage-resilient(LR)-ardency for QAHPS by defining two statistical properties, including LR--universal and LR--key-switching. We provide a generic approach to tightly leakage-resilient CCA (LR-CCA) secure public-key encryption (PKE) from LR-ardent QAHPS. Our approach is reminiscent of the seminal work of Cramer and Shoup (Eurocrypt\u2702), and employ three QAHPS schemes, one for generating a uniform string to hide the plaintext, and the other two for proving the well-formedness of the ciphertext. The LR-ardency of QAHPS makes possible the tight LR-CCA security. We give instantiations based on the standard k-Linear (k-LIN) assumptions over asymmetric and symmetric pairing groups, respectively, and obtain fully compact PKE with tight LR-CCA security. The security loss is O(log Q_e) where Q_e denotes the number of encryption queries. Specifically, our tightly LR-CCA secure PKE instantiation from SXDH has only 4 group elements in the public key and 7 group elements in the ciphertext, thus is the most efficient one

Computational solutions for omics data

High-throughput experimental technologies are generating increasingly massive and complex genomic data sets. The sheer enormity and heterogeneity of these data threaten to make the arising problems computationally infeasible. Fortunately, powerful algorithmic techniques lead to software that can answer important biomedical questions in practice. In this Review, we sample the algorithmic landscape, focusing on state-of-the-art techniques, the understanding of which will aid the bench biologist in analysing omics data. We spotlight specific examples that have facilitated and enriched analyses of sequence, transcriptomic and network data sets.National Institutes of Health (U.S.) (Grant GM081871

Thousands of Rab GTPases for the Cell Biologist

Rab proteins are small GTPases that act as essential regulators of vesicular trafficking. 44 subfamilies are known in humans, performing specific sets of functions at distinct subcellular localisations and tissues. Rab function is conserved even amongst distant orthologs. Hence, the annotation of Rabs yields functional predictions about the cell biology of trafficking. So far, annotating Rabs has been a laborious manual task not feasible for current and future genomic output of deep sequencing technologies. We developed, validated and benchmarked the Rabifier, an automated bioinformatic pipeline for the identification and classification of Rabs, which achieves up to 90% classification accuracy. We cataloged roughly 8.000 Rabs from 247 genomes covering the entire eukaryotic tree. The full Rab database and a web tool implementing the pipeline are publicly available at www.RabDB.org. For the first time, we describe and analyse the evolution of Rabs in a dataset covering the whole eukaryotic phylogeny. We found a highly dynamic family undergoing frequent taxon-specific expansions and losses. We dated the origin of human subfamilies using phylogenetic profiling, which enlarged the Rab repertoire of the Last Eukaryotic Common Ancestor with Rab14, 32 and RabL4. Furthermore, a detailed analysis of the Choanoflagellate Monosiga brevicollis Rab family pinpointed the changes that accompanied the emergence of Metazoan multicellularity, mainly an important expansion and specialisation of the secretory pathway. Lastly, we experimentally establish tissue specificity in expression of mouse Rabs and show that neo-functionalisation best explains the emergence of new human Rab subfamilies. With the Rabifier and RabDB, we provide tools that easily allows non-bioinformaticians to integrate thousands of Rabs in their analyses. RabDB is designed to enable the cell biology community to keep pace with the increasing number of fully-sequenced genomes and change the scale at which we perform comparative analysis in cell biology