"If You Can't Beat them, Join them": A Usability Approach to Interdependent Privacy in Cloud Apps

Cloud storage services, like Dropbox and Google Drive, have growing ecosystems of 3rd party apps that are designed to work with users' cloud files. Such apps often request full access to users' files, including files shared with collaborators. Hence, whenever a user grants access to a new vendor, she is inflicting a privacy loss on herself and on her collaborators too. Based on analyzing a real dataset of 183 Google Drive users and 131 third party apps, we discover that collaborators inflict a privacy loss which is at least 39% higher than what users themselves cause. We take a step toward minimizing this loss by introducing the concept of History-based decisions. Simply put, users are informed at decision time about the vendors which have been previously granted access to their data. Thus, they can reduce their privacy loss by not installing apps from new vendors whenever possible. Next, we realize this concept by introducing a new privacy indicator, which can be integrated within the cloud apps' authorization interface. Via a web experiment with 141 participants recruited from CrowdFlower, we show that our privacy indicator can significantly increase the user's likelihood of choosing the app that minimizes her privacy loss. Finally, we explore the network effect of History-based decisions via a simulation on top of large collaboration networks. We demonstrate that adopting such a decision-making process is capable of reducing the growth of users' privacy loss by 70% in a Google Drive-based network and by 40% in an author collaboration network. This is despite the fact that we neither assume that users cooperate nor that they exhibit altruistic behavior. To our knowledge, our work is the first to provide quantifiable evidence of the privacy risk that collaborators pose in cloud apps. We are also the first to mitigate this problem via a usable privacy approach.Comment: Authors' extended version of the paper published at CODASPY 201

Rational imitation for robots: the cost difference model

© 2017, © The Author(s) 2017. Infants imitate behaviour flexibly. Depending on the circumstances, they copy both actions and their effects or only reproduce the demonstrator’s intended goals. In view of this selective imitation, infants have been called rational imitators. The ability to selectively and adaptively imitate behaviour would be a beneficial capacity for robots. Indeed, selecting what to imitate is an outstanding unsolved problem in the field of robotic imitation. In this paper, we first present a formalized model of rational imitation suited for robotic applications. Next, we test and demonstrate it using two humanoid robots

Sample preservation and storage significantly impact taxonomic and functional profiles in metaproteomics studies of the human gut microbiome

With the technological advances of the last decade, it is now feasible to analyze microbiome samples, such as human stool specimens, using multi-omic techniques. Given the inherent sample complexity, there exists a need for sample methods which preserve as much information as possible about the biological system at the time of sampling. Here, we analyzed human stool samples preserved and stored using different methods, applying metagenomics as well as metaproteomics. Our results demonstrate that sample preservation and storage have a significant effect on the taxonomic composition of identified proteins. The overall identification rates, as well as the proportion of proteins from were much higher when samples were flash frozen. Preservation in RNAlater overall led to fewer protein identifications and a considerable increase in the share of , as well as . Additionally, a decrease in the share of metabolism-related proteins and an increase of the relative amount of proteins involved in the processing of genetic information was observed for RNAlater-stored samples. This suggests that great care should be taken in choosing methods for the preservation and storage of microbiome samples, as well as in comparing the results of analyses using different sampling and storage methods. Flash freezing and subsequent storage at -80 °C should be chosen wherever possible

Evaluating Local Community Methods in Networks

We present a new benchmarking procedure that is unambiguous and specific to local community-finding methods, allowing one to compare the accuracy of various methods. We apply this to new and existing algorithms. A simple class of synthetic benchmark networks is also developed, capable of testing properties specific to these local methods.Comment: 8 pages, 9 figures, code included with sourc

Conductance distribution between Hall plateaus

Mesoscopic fluctuations of two-port conductance and four-port resistance between Hall plateaus are studied within a realistic model for a two-dimensional electron gas in a perpendicular magnetic field and a smooth disordered potential. The two-port conductance distribution $P(g)$ is concave between $g=0$ and $g=1$ and is nearly flat between $g=0.2$ and $g=0.8$. These characteristics are consistent with recent observations. The distribution is found to be sharply peaked near the end-points $g=0$ and $g=1$. The distribution functions for the three independent resistances in a four-port Hall bar geometry are, on the other hand, characterized by a central peak and a relatively large width.Comment: 11 pages, 5 ps figures, submitted to Phys. Rev.

Unified functional network and nonlinear time series analysis for complex systems science: The pyunicorn package

We introduce the \texttt{pyunicorn} (Pythonic unified complex network and recurrence analysis toolbox) open source software package for applying and combining modern methods of data analysis and modeling from complex network theory and nonlinear time series analysis. \texttt{pyunicorn} is a fully object-oriented and easily parallelizable package written in the language Python. It allows for the construction of functional networks such as climate networks in climatology or functional brain networks in neuroscience representing the structure of statistical interrelationships in large data sets of time series and, subsequently, investigating this structure using advanced methods of complex network theory such as measures and models for spatial networks, networks of interacting networks, node-weighted statistics or network surrogates. Additionally, \texttt{pyunicorn} provides insights into the nonlinear dynamics of complex systems as recorded in uni- and multivariate time series from a non-traditional perspective by means of recurrence quantification analysis (RQA), recurrence networks, visibility graphs and construction of surrogate time series. The range of possible applications of the library is outlined, drawing on several examples mainly from the field of climatology.Comment: 28 pages, 17 figure

A unified approach for the solution of the Fokker-Planck equation

This paper explores the use of a discrete singular convolution algorithm as a unified approach for numerical integration of the Fokker-Planck equation. The unified features of the discrete singular convolution algorithm are discussed. It is demonstrated that different implementations of the present algorithm, such as global, local, Galerkin, collocation, and finite difference, can be deduced from a single starting point. Three benchmark stochastic systems, the repulsive Wong process, the Black-Scholes equation and a genuine nonlinear model, are employed to illustrate the robustness and to test accuracy of the present approach for the solution of the Fokker-Planck equation via a time-dependent method. An additional example, the incompressible Euler equation, is used to further validate the present approach for more difficult problems. Numerical results indicate that the present unified approach is robust and accurate for solving the Fokker-Planck equation.Comment: 19 page

Toward the Control of the Smoldering Front in the Reaction-Trailing Mode in Oil Shale Semicoke Porous Media

Results of an experimental investigation on the feasibility of propagating a smoldering front in reaction-trailing mode throughout an oil shale semicoke porous medium are reported. For oil recovery applications, this mode is particularly interesting to avoid low-temperature oxidation reactions, which appear simultaneously with organic matter devolatilization in the reaction-leading mode and are responsible for oxidation of part of the heavy oil. The particularity of this mode is that, contrary to the reaction-leading mode largely studied in the literature, the heat-transfer layer precedes the combustion layer. This leads to two separated high-temperature zones: (i) a devolatilization zone (free of oxygen), where the organic matter is thermally decomposed to incondensable gases, heavy oil, andfixed carbon, also called coke in the literature, without any oxidation, followed by (ii) an oxidation zone, where thefixed carbon left by devolatilization is oxidized. The transition from reaction-leading to reaction-trailing mode was obtained using low oxygen contents in the fed air. It is shown that two distinct layers, the heat-transfer layer and the combustion layer, propagate in a stable and repeatable way. The decrease of the oxygen fraction leads to a decrease of the smoldering temperature and to strongly limit the decarbonation of the mineral matrix. The CO2 emissions are limited. Regardless of the front temperature, all of the fed oxygen is consumed and all of thefixed carbon is oxidized at the passage of the smoldering front

Forward K+ production in subthreshold pA collisions at 1.0 GeV

K+ meson production in pA (A = C, Cu, Au) collisions has been studied using the ANKE spectrometer at an internal target position of the COSY-Juelich accelerator. The complete momentum spectrum of kaons emitted at forward angles, theta < 12 degrees, has been measured for a beam energy of T(p)=1.0 GeV, far below the free NN threshold of 1.58 GeV. The spectrum does not follow a thermal distribution at low kaon momenta and the larger momenta reflect a high degree of collectivity in the target nucleus.Comment: 4 pages, 3 figure

Localization of nonlinear excitations in curved waveguides

Motivated by the example of a curved waveguide embedded in a photonic crystal, we examine the effects of geometry in a ``quantum channel'' of parabolic form. We study the linear case and derive exact as well as approximate expressions for the eigenvalues and eigenfunctions of the linear problem. We then proceed to the nonlinear setting and its stationary states in a number of limiting cases that allow for analytical treatment. The results of our analysis are used as initial conditions in direct numerical simulations of the nonlinear problem and localized excitations are found to persist, as well as to have interesting relaxational dynamics. Analogies of the present problem in contexts related to atomic physics and particularly to Bose-Einstein condensation are discussed.Comment: 14 pages, 4 figure