Using Verification Technology to Specify and Detect Malware

Computer viruses and worms are major threats for our computer infrastructure, and thus, for economy and society at large. Recent work has demonstrated that a model checking based approach to malware detection can capture the semantics of security exploits more accurately than traditional approaches, and consequently achieve higher detection rates. In this approach, malicious behavior is formalized using the expressive specification language CTPL based on classic CTL. This paper gives an overview of our toolchain for malware detection and presents our new system for computer assisted generation of malicious code specifications

Distributed information consensus filters for simultaneous input and state estimation

This paper describes the distributed information filtering where a set of sensor networks are required to simultaneously estimate input and state of a linear discrete-time system from collaborative manner. Our research purpose is to develop a consensus strategy in which sensor nodes communicate within the network through a sequence of Kalman iterations and data diffusion. A novel recursive information filtering is proposed by integrating input estimation error into measurement data and weighted information matrices. On the fusing process, local system state filtering transmits estimation information using the consensus averaging algorithm, which penalizes the disagreement in a dynamic manner. A simulation example is provided to compare the performance of the distributed information filtering with optimal Gillijins–De Moor’s algorithm

Into the groove:instructive conductive silk films with topological guidance cues

Instructive biomaterials capable of controlling the behaviour of the cells are particularly interesting scaffolds for tissue engineering and regenerative medicine. Novel biomaterials are particularly important in societies with rapidly aging populations, where demand for organ/tissue donations is greater than their supply. Herein we describe the preparation of electrically conductive silk film-based nerve tissue scaffolds that are manufactured using all aqueous processing. Aqueous solutions of Bombyx mori silk were cast on flexible polydimethylsiloxane substrates with micrometer-scale grooves on their surfaces, allowed to dry, and annealed to impart β-sheets to the silk which assures that the materials are stable for further processing in water. The silk films were rendered conductive by generating an interpenetrating network of polypyrrole and polystyrenesulfonate in the silk matrix. Films were incubated in an aqueous solution of pyrrole (monomer), polystyrenesulfonate (dopant) and iron chloride (initiator), after which they were thoroughly washed to remove low molecular weight components (monomers, initiators, and oligomers) and dried, yielding conductive films with sheet resistances of 124 ± 23 kΩ square-1. The micrometer-scale grooves that are present on the surface of the films are analogous to the natural topography in the extracellular matrix of various tissues (bone, muscle, nerve, skin) to which cells respond. Dorsal Root Gangions (DRGs) adhere to the films and the grooves in the surface of the films instruct the aligned growth of processes extending from the DRGs. Such materials potentially enable the electrical stimulation of cells cultured on them, and future in vitro studies will focus on understanding the interplay between electrical and topographical cues on the behaviour of cells cultured on them

Adaptive estimation in circular functional linear models

We consider the problem of estimating the slope parameter in circular functional linear regression, where scalar responses Y1,...,Yn are modeled in dependence of 1-periodic, second order stationary random functions X1,...,Xn. We consider an orthogonal series estimator of the slope function, by replacing the first m theoretical coefficients of its development in the trigonometric basis by adequate estimators. Wepropose a model selection procedure for m in a set of admissible values, by defining a contrast function minimized by our estimator and a theoretical penalty function; this first step assumes the degree of ill posedness to be known. Then we generalize the procedure to a random set of admissible m's and a random penalty function. The resulting estimator is completely data driven and reaches automatically what is known to be the optimal minimax rate of convergence, in term of a general weighted L2-risk. This means that we provide adaptive estimators of both the slope function and its derivatives

Chromium Substituted Cobalt Ferrites by Glycine-Nitrates Process

Chromium substituted cobalt ferrites (CoFe2–xCrxO4, 0 ≤ x ≤ 2) were synthesized through solution combustion method using glycine as fuel, named glycine-nitrates process (GNP). As evidenced by X-ray diffraction data (XRD), single cubic spinel phase was formed for all CoFe2–xCrxO4 (0 ≤ x ≤ 2) series. The cubic lattice parameter (a) decreases with increasing chromium content. Room temperature 57Fe Mössbauer spectra revealed the Fe3+ and Cr3+ site occupancy, the local hyperfine magnetic fields and the substitution of Fe3+ by Cr3+ in the lattice. Scanning electron microscopy (SEM) showed a refinement of particle size with the increase of Cr3+ content. Magnetic measurements from 5 K to 120 K have shown a dropping in the saturation magnetization as the chromium content increases. This behaviour has been explained in terms of substitution of Fe3+ by Cr3+ in the cubic lattice of cobalt ferrite

Highlights from the Pierre Auger Observatory

The Pierre Auger Observatory is the world's largest cosmic ray observatory. Our current exposure reaches nearly 40,000 km$^2$ str and provides us with an unprecedented quality data set. The performance and stability of the detectors and their enhancements are described. Data analyses have led to a number of major breakthroughs. Among these we discuss the energy spectrum and the searches for large-scale anisotropies. We present analyses of our X$_{max}$ data and show how it can be interpreted in terms of mass composition. We also describe some new analyses that extract mass sensitive parameters from the 100% duty cycle SD data. A coherent interpretation of all these recent results opens new directions. The consequences regarding the cosmic ray composition and the properties of UHECR sources are briefly discussed.Comment: 9 pages, 12 figures, talk given at the 33rd International Cosmic Ray Conference, Rio de Janeiro 201

Multiple functional regression with both discrete and continuous covariates

International audienceIn this paper we present a nonparametric method for extending functional regression methodology to the situation where more than one functional covariate is used to predict a functional response. Borrowing the idea from Kadri et al. (2010a), the method, which support mixed discrete and continuous explanatory variables, is based on estimating a function-valued function in reproducing kernel Hilbert spaces by virtue of positive operator-valued kernels