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RRTxFM: Probabilistic Counting for Differentially Private Statistics
Probabilistic Counting Differential Privacy Randomized Response
2019/7/15
Data minimization has become a paradigm to address privacy concerns when collecting and storing personal data. In this paper we present two new approaches, RSTxFM and RRTxFM, to estimate the cardinali...
P2KMV: A Privacy-preserving Counting Sketch for Efficient and Accurate Set Intersection Cardinality Estimations
P2KMV analytical expectations
2018/3/9
In this paper, we propose P2KMV, a novel privacy-preserving counting sketch, based on the k minimum values algorithm. With P2KMV, we offer a versatile privacy-enhanced technology for obtaining statist...
Universally Verifiable MPC with Applications to IRV Ballot Counting
IRV Ballot Counting MPC
2018/3/8
We present a very simple universally verifiable MPC protocol. The first component is a threshold somewhat homomorphic cryptosystem that permits an arbitrary number of additions (in the source group), ...
Two Sides of the Same Coin: Counting and Enumerating Keys Post Side-Channel Attacks Revisited
implementation side channels
2018/1/12
Motivated by the need to assess the concrete security of a device after a side channel attack, there has been a flurry of recent work designing both key rank and key enumeration algorithms. Two main c...
Model-counting Approaches For Nonlinear Numerical Constraints
Side-channel Attacks Modulo Exponentiation Quantitative Information Flow
2017/3/21
Model counting is of central importance in quantitative reasoning about systems. Examples include computing the probability that a system successfully accomplishes its task without errors, and measuri...
An Algorithm for Counting the Number of $2^n$-Periodic Binary Sequences with Fixed $k$-Error Linear Complexity
Sequence Linear Complexity k-Error Linear Complexity
2016/12/7
The linear complexity and kk-error linear complexity of sequences are important measures of the strength of key-streams generated by stream ciphers. The counting function of a sequence complexity meas...
Counting and Exploring Sizes of Markov Equivalence Classes of Directed Acyclic Graphs
Directed acyclic graphs Markov equivalence class Size distribution Causal- ity
2016/1/26
When learning a directed acyclic graph (DAG) model via observational data, one gener-ally cannot identify the underlying DAG, but can potentially obtain a Markov equivalence class. The size (the numbe...
Multiple Target Counting and Tracking using Binary Proximity Sensors: Bounds, Coloring, and Filter
Multiple Target Counting Tracking using Binary Proximity Sensors Bounds Coloring Filter
2016/1/22
Binary proximity sensors (BPS) provide extremely low cost and privacy preserving features for tracking mobile targets in smart environment, but great challenges are posed for track-ing multiple target...
Counting and Exploring Sizes of Markov Equivalence Classes of Directed Acyclic Graphs
Directed acyclic graphs Markov equivalence class Size distribution Causal- ity
2016/1/20
When learning a directed acyclic graph (DAG) model via observational data, one gener-ally cannot identify the underlying DAG, but can potentially obtain a Markov equivalence class. The size (the numbe...
Counting Keys in Parallel After a Side Channel Attack
key enumeration key rank side channels
2015/12/29
Side channels provide additional information to skilled adversaries
that reduce the effort to determine an unknown key. If sufficient
side channel information is available, identification of the sec...
Counting good truth assignments of random k-SAT formulae
Random k-SAT Correlation Decay Uniqueness Gibbs Distribution
2015/8/21
We present a deterministic approximation algorithm to compute logarithm of the number of ‘good’ truth assignments for a random k-satisfiability (k-SAT) formula in polynomial time (by ‘good’ we m...
Wald Lecture I: Counting Bits with Kolmogorov and Shannon
Rate-Distortion Gaussian Process Entrop Ellipsoids
2015/8/21
Shannon’s Rate-Distortion Theory describes the number of bits needed to approximately
represent typical realizations of a stochastic process X = (X(t) : t ∈ T),while Kolmogorov’s
-entropy describes...
COUNTING THE FACES OF RANDOMLY-PROJECTED HYPERCUBES AND ORTHANTS, WITH APPLICATIONS
RANDOMLY-PROJECTED ORTHANTS
2015/8/21
Let RN
+ denote the positive orthant; the expected number of k-faces of
the random cone ARN
+ obeys Efk(ARN
+)/fk(RN
+) = 1 − PN−n,N−k. The
formula applies to numerous matrix e...
COUNTING FACES OF RANDOMLY-PROJECTED POLYTOPES WHEN THE PROJECTION RADICALLY LOWERS DIMENSION
RANDOMLY-PROJECTED RADICALLY LOWERS DIMENSION
2015/8/21
The modern trend in statistics and probability is to consider the case where both
the number of dimensions d and the sample size n are large [19, 21]. In that case, the
intuition fostered by the cla...
Caporaso and Harris derive recursive formulas counting nodal plane
curves of degree d and geometric genus g in the plane (through the appropriate number of xed
general points). We rephrase their ar...