Revisit Sparse Polynomial Interpolation based on Randomized Kronecker Substitution

In this paper, a new reduction based interpolation algorithm for black-box multivariate polynomials over finite fields is given. The method is based on two main ingredients. A new Monte Carlo method is given to reduce black-box multivariate polynomial interpolation to black-box univariate polynomial interpolation over any ring. The reduction algorithm leads to multivariate interpolation algorithms with better or the same complexities most cases when combining with various univariate interpolation algorithms. We also propose a modified univariate Ben-or and Tiwarri algorithm over the finite field, which has better total complexity than the Lagrange interpolation algorithm. Combining our reduction method and the modified univariate Ben-or and Tiwarri algorithm, we give a Monte Carlo multivariate interpolation algorithm, which has better total complexity in most cases for sparse interpolation of black-box polynomial over finite fields

Secrecy Results for Compound Wiretap Channels

We derive a lower bound on the secrecy capacity of the compound wiretap channel with channel state information at the transmitter which matches the general upper bound on the secrecy capacity of general compound wiretap channels given by Liang et al. and thus establishing a full coding theorem in this case. We achieve this with a stronger secrecy criterion and the maximum error probability criterion, and with a decoder that is robust against the effect of randomisation in the encoding. This relieves us from the need of decoding the randomisation parameter which is in general not possible within this model. Moreover we prove a lower bound on the secrecy capacity of the compound wiretap channel without channel state information and derive a multi-letter expression for the capacity in this communication scenario.Comment: 25 pages, 1 figure. Accepted for publication in the journal "Problems of Information Transmission". Some of the results were presented at the ITW 2011 Paraty [arXiv:1103.0135] and published in the conference paper available at the IEEE Xplor

Maximum-Reward Motion in a Stochastic Environment: The Nonequilibrium Statistical Mechanics Perspective

We consider the problem of computing the maximum-reward motion in a reward field in an online setting. We assume that the robot has a limited perception range, and it discovers the reward field on the fly. We analyze the performance of a simple, practical lattice-based algorithm with respect to the perception range. Our main result is that, with very little perception range, the robot can collect as much reward as if it could see the whole reward field, under certain assumptions. Along the way, we establish novel connections between this class of problems and certain fundamental problems of nonequilibrium statistical mechanics . We demonstrate our results in simulation examples

Searchable Encryption with Optimal Locality: Achieving Sublogarithmic Read Efficiency

We propose the first linear-space searchable encryption scheme with constant locality and \emph{sublogarithmic} read efficiency, strictly improving the previously best known read efficiency bound (Asharov et al., STOC 2016) from $\Theta(\log N \log \log N)$ to $O(\log ^{\gamma} N)$ where $\gamma=\frac{2}{3}+\delta$ for any fixed $\delta>0$. Our scheme employs four different allocation algorithms for storing the keyword lists, depending on the size of the list considered each time. For our construction we develop (i) new probability bounds for the offline two-choice allocation problem; (ii) and a new I/O-efficient oblivious RAM with $\tilde{O}(n^{1/3})$ bandwidth overhead and zero failure probability, both of which can be of independent interest

Security of the Blockchain against Long Delay Attack

The consensus protocol underlying Bitcoin (the blockchain) works remarkably well in practice. However proving its security in a formal setting has been an elusive goal. A recent analytical result by Pass, Seeman and shelat indicates that an idealized blockchain is indeed secure against attacks in an asynchronous network where messages are maliciously delayed by at most $\Delta\ll1/np$, with $n$ being the number of miners and $p$ the mining hardness. This paper improves upon the result by showing that if appropriate inconsistency tolerance is allowed the blockchain can withstand even more powerful external attacks in the honest miner setting. Specifically we prove that the blockchain is secure against long delay attacks with $\Delta\geq1/np$ in an asynchronous network

Tight Time-Space Lower Bounds for Finding Multiple Collision Pairs and Their Applications

We consider a collision search problem (CSP), where given a parameter $C$, the goal is to find $C$ collision pairs in a random function $f:[N] \rightarrow [N]$ (where $[N] = \{0,1,\ldots,N-1\})$ using $S$ bits of memory. Algorithms for CSP have numerous cryptanalytic applications such as space-efficient attacks on double and triple encryption. The best known algorithm for CSP is parallel collision search (PCS) published by van Oorschot and Wiener, which achieves the time-space tradeoff $T^2 \cdot S = \tilde{O}(C^2 \cdot N)$ for $S = \tilde{O}(C)$. In this paper, we prove that any algorithm for CSP satisfies $T^2 \cdot S = \tilde{\Omega}(C^2 \cdot N)$ for $S = \tilde{O}(C)$, hence the best known time-space tradeoff is optimal (up to poly-logarithmic factors in $N$). On the other hand, we give strong evidence that proving similar unconditional time-space tradeoff lower bounds on CSP applications (such as breaking double and triple encryption) may be very difficult, and would imply a breakthrough in complexity theory. Hence, we propose a new restricted model of computation and prove that under this model, the best known time-space tradeoff attack on double encryption is optimal