Weighted isoperimetric inequalities in cones and applications

This paper deals with weighted isoperimetric inequalities relative to cones of $\mathbb{R}^{N}$. We study the structure of measures that admit as isoperimetric sets the intersection of a cone with balls centered at the vertex of the cone. For instance, in case that the cone is the half-space $\mathbb{R}_{+}^{N}={x \in \mathbb{R}^{N} : x_{N}>0}$ and the measure is factorized, we prove that this phenomenon occurs if and only if the measure has the form $d\mu=ax_{N}^{k}\exp(c|x|^{2})dx$, for some $a>0$, $k,c\geq 0$. Our results are then used to obtain isoperimetric estimates for Neumann eigenvalues of a weighted Laplace-Beltrami operator on the sphere, sharp Hardy-type inequalities for functions defined in a quarter space and, finally, via symmetrization arguments, a comparison result for a class of degenerate PDE's

Exploring the Usage of Topic Modeling for Android Malware Static Analysis

The rapid growth in smartphone and tablet usage over the last years has led to the inevitable rise in targeting of these devices by cyber-criminals. The exponential growth of Android devices, and the buoyant and largely unregulated Android app market, produced a sharp rise in malware targeting that platform. Furthermore, malware writers have been developing detection-evasion techniques which rapidly make anti-malware technologies ineffective. It is hence advisable that security expert are provided with tools which can aid them in the analysis of existing and new Android malware. In this paper, we explore the use of topic modeling as a technique which can assist experts to analyse malware applications in order to discover their characteristic. We apply Latend Dirichlet Allocation (LDA) to mobile applications represented as opcode sequences, hence considering a topic as a discrete distribution of opcode. Our experiments on a dataset of 900 malware applications of different families show that the information provided by topic modeling may help in better understanding malware characteristics and similarities

Timed Automata for Mobile Ransomware Detection

Considering the plethora of private and sensitive information stored in smartphone and tablets, it is easy to understand the reason why attackers develop everyday more and more aggressive malicious payloads with the aim to exfiltrate our data. One of the last trend in mobile malware landascape is represented by the so-called ransomware, a threat capable to lock the user interface and to cipher the data of the mobile device under attack. In this paper we propose an approach to model an Android application in terms of timed automaton by considering system call traces i.e., performing a dynamic analysis. We obtain encouraging results in the experimental analysis we performed exploiting real-world  (ransomware and legitimate) Android applications

diabetes mellitus affected patients classification and diagnosis through machine learning techniques

Medical studies demonstrated that diabetes pathology is increasing in last decades and the trend do not tends to stop. In order to help and to accelerate the diagnosis of diabetes in this paper we propose a method able to classify patients affected by diabetes using a set of characteristic selected in according to World Health Organization criteria. Evaluating real-world data using state of the art machine learning algorithms, we obtain a precision value equal to 0.770 and a recall equal to 0.775 using the HoeffdingTree algorithm

Spectroscopic Signatures of Gate-Controlled Superconducting Phases

We investigate the tunneling conductance of superconductor-insulator-normal metal (SIN) and superconductor-insulator-superconductor (SIS) heterostructures with one superconducting side of the junction that is electrically driven and can exhibit $\pi$-pairing through a modification of the surface inversion asymmetric couplings. In SIN tunneling we find that the variation of the electrically driven interactions generally brings an increase of quasi-particles in the gap due to orbitally polarized depaired states, irrespective of the inter-band phase rearrangement. The peak of SIN conductance at the gap edge varies with a trend that depends both on the strength of the surface interactions as well as on the character of the gate-induced superconducting state. While this shift can be also associated with thermal effects in the SIN configuration, for the SIS geometry at low temperature the electric field does not yield the characteristic matching peak at voltages related with the difference between the gaps of the superconducting electrodes. This observation sets out a distinctive mark for spectroscopically distinguishing the thermal population effects from the quantum gate-driven signatures. In SIS the electrostatic gating yields a variety of features with asymmetric peaks and broadening of the conductance spectral weight. These findings indicate general qualitative trends for both SIN and SIS tunneling spectroscopy which could serve to evaluate the impact of gate-control on superconductors and the occurrence of non-centrosymmetric orbital antiphase pairing.Comment: 15 pages, 8 panels of figure