Perscido

2019 Mar 14
Open
experimental data

Sparse Integer Matrices Collection
Contributor: Jean-Guillaume Dumas
Collection of matrices used in exact computations. Most of them are sparse with integral or modular coefficients, some have rational or polynomial entries. > ...

2018 Nov 30
Open
Image data

UV and visible fluorescence images of maize stem: macroscopy and confocal microscopy
Contributor: marie-françoise devaux
Fluorescence Macroscopy is a full field imaging system at low magnification. The interest is to rapidly observe large fields of view (~5x5 mm²). Fluorescence filters are used that select excitation and emission ranges of wavelengths. The spectral resolution is low. Confocal microscopy equipped with a spectral detector and several excitation lasers allows to acquire hyperspectral images. The spectral resolution is around 6-10 nm. The field of view is small and is about 500 x500 µm² with a good sp atial resolution. The fusion or the multiset analysis of the two kinds of images should provide a link between the two scales of observation and therefore a strategy to develop multiscale acquisition.> ... ...

2018 Oct 30
Open
experimental data

Micro-seismic-monitoring of a floating ice plate to monitor its deformation: Catalog
Contributor: Cédric Lachaud
This dataset corresponds to the detected fractures characteristics related to the microseismic monitoring of a floating ice plate. This dataset is used in the manuscript submitted to JGR titled "Micro-seismic monitoring of a floating ice plate to characterize its deformation' by C. Lachaud, D. Marsan, M. Montagnat, J. Weiss, L. Moreau and F. Gimbert > ...

2018 Sep 24
Open
Trace data

GICS Intrusion Detection Datasets
Contributor: Stephane Mocanu
Context These datasets were generated for the evaluation of cybersecurity measures in the context of industrial control systems (ICS). An ICS is a set of devices (electrical, mechanical, hydraulic,. . . ) whose interaction controls the behavior of a physical process in order to achieve an industrial objective (manufacturing, transportation of matter and energy, etc.). ICSs serve as the backbone of several critical infrastructures that provide facilities for the generation and distribution of ele ctricity, water treatment and supply, railway transportation networks, and manufacturing applications. Due to their criticality, failures in these systems, whether of accidental or intentional origins, can lead to significant human and economic loss. The recent history of ICSs is that of an ever-growing convergence with classical information technology (IT) systems. In an effort to drive down costs and provide stakeholders, engineers and operators with seamless access to the industrial plants, ICSs are nowadays interconnected with the Internet and have adopted off-the-shelf IT technology such as TCP/IP networking, standard computer architectures, and common operating systems. Concurrently, many of the security vulnerabilities which marred IT systems have been exported to ICSs. Thus, if such systems were once considered secure because of their isolation, their use of proprietary protocols and peculiar architectures, this is no longer the case as witnessed by the growing number of increasingly sophisticated cybersecurity incidents in the last decades. As a result, nation-states, organizations, and industries have become sensitive to the security threats of ICSs, and have been adamant in their call for the development of adequate security measures to protect ICSs from security breaches. One of the key aspects which distinguish an ICS from classical IT systems is the presence of a physical process. This has lead to the apparition of a new class of novel threats which target the physical process. These datasets contain instances of such attacks and can be used to evaluate the efficiency of security measures in protecting an ICS against targeted attacks. Content These datasets include network traces collected at the ENSE3 GICS platform for the purposes of evaluating an intrusion detection system (IDS) for ICS. An IDS is a system which monitors a system in order to automatically detect security breaches. The network traces capture the behavior of an ICS test bed under attacks targeting the physical process. The test bed is implemented in GICS and is comprised of several controllers (Schneider M340/M580, Wago IPC-C6, Siemens, etc.) along with supervisory machines, engineering workstations and human machine interfaces (HMIs). Each controller sends commands and receives sensor information, via I/O interface cards, from a real-time OpenModelica simulation of a complex physical process representing a complex chemical plant. The traces contain, among other protocols, Modbus traffic carrying attacks violating the specifications of the underlying physical process. This is performed by sending a sequence of Modbus commands from workstations to controllers running the control logics which steer the process. Two types of attacks are contained in these datasets. The first type of attacks violates qualitative temporal constraints on the behavior of the physical process. Examples of such attacks include opening simultaneously two valves or stopping a motor before its due time. The second type of attacks violates quantitative temporal constraints. For example, the traces include attacks that wear a valve by quickly opening and closing it. The contents of the datasets is as follows: • One capture free from attacks and containing only legitimate traffic (capture16) • Four captures containing attacks (capture17, capture18, capure19, capture20)> ... ...

2018 Jul 10
Open
experimental data

Physical and morphological parameters of two Antarctic polar sites : Dome C and Lock In
Contributor: Alexis Burr
This dataset contains all parameters measured or determined in Burr, A., Ballot, C., Lhuissier, P., Martinerie, P., Martin, C. L., and Philip, A.: Pore morphology of polar firn around closure revealed by X-ray tomography, The Cryosphere Discuss, 2018. It contains for both Dome C and Lock In sites (Antarctic plateau) various parameters of the pores embedded in firn, and were obtained by X-ray tomography : the closed porosity ratio, connectivity index, specific surface area, surface-to-volume rati o, but also other parameters related to the pore structure. In particular, the connectivity index was used to predict the close-off depth and density.> ... ...