Grenoble Institute of Technology

About: Grenoble Institute of Technology is a education organization based out in Grenoble, France. It is known for research contribution in the topics: Hyperspectral imaging & Geology. The organization has 3427 authors who have published 5345 publications receiving 137158 citations. The organization is also known as: Grenoble INP.

Critical Nucleation Effects on the Structural Relationship Between ZnO Seed Layer and Nanowires

Abstract: The effects of the structural morphology of the ZnO thin seed layer composed of nanoparticles grown by dip coating have been investigated on the structural properties of ZnO nanowires grown by chemical bath deposition. It is revealed by scanning electron microscopy that the growth of ZnO nanowires is limited by the mass transport of chemical precursors in solution, leading to the inverse relationship of their average diameter and length with their density. It is shown by transmission electron microscopy and X-ray diffraction measurements that ZnO nanowires epitaxially grow on the seed layer and preferentially nucleate on the free surface of ZnO nanoparticles. The vertical alignment of ZnO nanowires as quantitatively deduced by X-ray pole figures is found to be improved by strengthening the texture of the seed layer along the c axis. Similarly, their density increases, showing that the c polar plane is highly reactive chemically and presents preferential surface nucleation sites. The relationship between t...

Internal Composition versus the Mechanical Properties of Polyelectrolyte Multilayer Films: The Influence of Chemical Cross-Linking†

Abstract: Different types of polyelectrolyte multilayer Films composed of poly(L-lysine)/hyaluronan (PLL/HA), chitosan/hyaluronan (CHI/HA) and poly(allylamine hydrochloride)poly(L-glutamic acid) (PAH/PGA) have been investigated Cor their internal composition, including water content, ion pairing, and ability to be covalently cross-linked, as well as for their mechanical properties. Film buildup under physiological conditions was monitored by the quartz crystal microbalance with dissipation monitoring (QCM-D) and attenuated total reflectance Fourier transform infrared spectroscopy (ATR-FTIR), which allows unambiguous quantification of the different groups present in the polyelectrolytes. (PAH/PGA) films emerged as the most dense films with the lowest hydration (29%) and the highest COO(-) molar density. In addition, PAH is greatly in excess in these films (3 PAH monomers per PGA monomer), The formation of amide bonds during Film cross-linking using the water-soluble carbodiimide EDC was also investigated, All of the films could be cross-linked in a tunable manner, but PAH/PGA exhibited the highest absolute number of amide bonds created, similar to 7 times more than for (PLL/HA) and (CHI/HA) Films. The Young's modulus E of the films measured by AFM nanoindentation was shown to vary over I to 2 orders or magnitude for the different systems. Interestingly, a linear relationship between E and the density of the covalent cross-links created was observed for (PLL/HA) and (CHI/HA) films whereas (PGA/PAH) films exhibited biphasic behavior. The mean distance between covalent cross-links was estimated to be similar to 11 nm for (PLL/HA) and (CHI/HA) films and only similar to 6 nm for (PAH/PGA) Films for the maximum EDC concentration tested (100 mg/mL).

Very High-Resolution Remote Sensing: Challenges and Opportunities [Point of View]

Abstract: Advanced information processing and architectures will be needed to bridge the gap between the potential offered by the new generations of sensors and the needs of the end-users to actually face tomorrow's challenges in many applications with a very high societal impact. As remote sensing researchers and engineers, this is our passion, our charge, and our responsibility.

KameleonFuzz: evolutionary fuzzing for black-box XSS detection

Abstract: Fuzz testing consists in automatically generating and sending malicious inputs to an application in order to hopefully trigger a vulnerability. Fuzzing entails such questions as: Where to fuzz? Which parameter to fuzz? Where to observe its effects?In this paper, we specifically address the questions: How to fuzz a parameter? How to observe its effects? To address these questions, we propose KameleonFuzz, a black-box Cross Site Scripting (XSS) fuzzer for web applications. KameleonFuzz can not only generate malicious inputs to exploit XSS, but also detect how close it is revealing a vulnerability. The malicious inputs generation and evolution is achieved with a genetic algorithm, guided by an attack grammar. A double taint inference, up to the browser parse tree, permits to detect precisely whether an exploitation attempt succeeded.Our evaluation demonstrates no false positives and high XSS revealing capabilities: KameleonFuzz detects several vulnerabilities missed by other black-box scanners.