Hybrid Epidemics - A Case Study on Computer Worm Conficker

Conficker is a computer worm that erupted on the Internet in 2008. It is unique in combining three different spreading strategies: local probing, neighbourhood probing, and global probing. We propose a mathematical model that combines three modes of spreading, local, neighbourhood and global to capture the worm's spreading behaviour. The parameters of the model are inferred directly from network data obtained during the first day of the Conifcker epidemic. The model is then used to explore the trade-off between spreading modes in determining the worm's effectiveness. Our results show that the Conficker epidemic is an example of a critically hybrid epidemic, in which the different modes of spreading in isolation do not lead to successful epidemics. Such hybrid spreading strategies may be used beneficially to provide the most effective strategies for promulgating information across a large population. When used maliciously, however, they can present a dangerous challenge to current internet security protocols

Detecting simultaneous variant intervals in aligned sequences

Given a set of aligned sequences of independent noisy observations, we are concerned with detecting intervals where the mean values of the observations change simultaneously in a subset of the sequences. The intervals of changed means are typically short relative to the length of the sequences, the subset where the change occurs, the "carriers," can be relatively small, and the sizes of the changes can vary from one sequence to another. This problem is motivated by the scientific problem of detecting inherited copy number variants in aligned DNA samples. We suggest a statistic based on the assumption that for any given interval of changed means there is a given fraction of samples that carry the change. We derive an analytic approximation for the false positive error probability of a scan, which is shown by simulations to be reasonably accurate. We show that the new method usually improves on methods that analyze a single sample at a time and on our earlier multi-sample method, which is most efficient when the carriers form a large fraction of the set of sequences. The proposed procedure is also shown to be robust with respect to the assumed fraction of carriers of the changes.Comment: Published in at http://dx.doi.org/10.1214/10-AOAS400 the Annals of Applied Statistics (http://www.imstat.org/aoas/) by the Institute of Mathematical Statistics (http://www.imstat.org

Signatures of Majorana Fermions in Topological Insulator Josephson Junction Devices

We study theoretically the electrical current and low-frequency noise for a linear Josephson junction structure on a topological insulator, in which the superconductor forms a closed ring and currents are injected from normal regions inside and outside the ring. We find that this geometry offers a signature for the presence of gapless 1D Majorana fermion modes that are predicted in the channel when the phase difference \phi, controlled by the magnetic flux through the ring, is \pi. We show that for low temperature the linear conductance jumps when \phi\ passes through \pi, accompanied by non-local correlations between the currents from the inside and outside of the ring. We compute the dependence of these features on temperature, voltage and linear dimensions, and discuss the implications for experiments.Comment: 11 pages, 5 figure

Correlated photon pair generation in low-loss double-stripe silicon nitride waveguides

We demonstrate correlated photon pair generation via spontaneous four-wave mixing in a low-loss double-stripe silicon nitride waveguide with a coincidence-to-accidental ratio over 10. The coincidence-to-accidental ratio is limited by spontaneous Raman scattering, which can be mitigated by cooling in the future. This demonstration suggests that this waveguide structure is a potential platform to develop integrated quantum photonic chips for quantum information processing.Comment: 7 pages, 4 figure

LeoTask: a fast, flexible and reliable framework for computational research

LeoTask is a Java library for computation-intensive and time-consuming research tasks. It automatically executes tasks in parallel on multiple CPU cores on a computing facility. It uses a configuration file to enable automatic exploration of parameter space and flexible aggregation of results, and therefore allows researchers to focus on programming the key logic of a computing task. It also supports reliable recovery from interruptions, dynamic and cloneable networks, and integration with the plotting software Gnuplot

On the Differential Privacy of Bayesian Inference

We study how to communicate findings of Bayesian inference to third parties, while preserving the strong guarantee of differential privacy. Our main contributions are four different algorithms for private Bayesian inference on proba-bilistic graphical models. These include two mechanisms for adding noise to the Bayesian updates, either directly to the posterior parameters, or to their Fourier transform so as to preserve update consistency. We also utilise a recently introduced posterior sampling mechanism, for which we prove bounds for the specific but general case of discrete Bayesian networks; and we introduce a maximum-a-posteriori private mechanism. Our analysis includes utility and privacy bounds, with a novel focus on the influence of graph structure on privacy. Worked examples and experiments with Bayesian na{\"i}ve Bayes and Bayesian linear regression illustrate the application of our mechanisms.Comment: AAAI 2016, Feb 2016, Phoenix, Arizona, United State