A Methodology for Evaluating the Robustness of Anomaly Detectors to Adversarial Attacks in Industrial Scenarios

Anomaly Detection systems based on Machine and Deep learning are the most promising solutions to detect cyberattacks in the industry. However, these techniques are vulnerable to adversarial attacks that downgrade prediction performance. Several techniques have been proposed to measure the robustness of Anomaly Detection in the literature. However, they do not consider that, although a small perturbation in an anomalous sample belonging to an attack, i.e., Denial of Service, could cause it to be misclassified as normal while retaining its ability to damage, an excessive perturbation might also transform it into a truly normal sample, with no real impact on the industrial system. This paper presents a methodology to calculate the robustness of Anomaly Detection models in industrial scenarios. The methodology comprises four steps and uses a set of additional models called support models to determine if an adversarial sample remains anomalous. We carried out the validation using the Tennessee Eastman process, a simulated testbed of a chemical process. In such a scenario, we applied the methodology to both a Long-Short Term Memory (LSTM) neural network and 1-dimensional Convolutional Neural Network (1D-CNN) focused on detecting anomalies produced by different cyberattacks. The experiments showed that 1D-CNN is significantly more robust than LSTM for our testbed. Specifically, a perturbation of 60% (empirical robustness of 0.6) of the original sample is needed to generate adversarial samples for LSTM, whereas in 1D-CNN the perturbation required increases up to 111% (empirical robustness of 1.11)

Use of an experimental model to evaluate infection resistance of meshes in abdominal wall surgery

Background: Staphylococcal species are the most common organisms causing prosthetic mesh infections, however, infections due to rapidly growing mycobacteria are increasing. This study evaluates the resistance of biomaterial for abdominal wall prostheses against the development of postoperative infection in a rat model. Material and methods: In 75 rats, we intramuscularly implanted three different types of prostheses: (1) low-density polypropylene monofilament mesh (PMM), (2) high-density PMM, and (3) a composite prosthesis composed of low-density PMM and a nonporous hydrophilic film. Meshes were inoculated with a suspension containing 108 colony-forming units of Staphylococcus aureus, Staphylococcus epidermidis, Mycobacterium fortuitum, or Mycobacterium abscessus before wound closure. Animals were sacrificed on the eighth day postoperatively for clinical evaluation, and the implants were removed for bacteriologic analyses. Results: Prostheses infected with S aureus showed a higher bacterial viability, worse integration, and clinical outcome compared with infection by other bacteria. Composite prostheses showed a higher number of viable colonies of both M fortuitum and Staphylococcus spp., with poorer integration in host tissue. However, when the composite prosthesis was infected with M abscessus, a lower number of viable bacteria were isolated and a better integration was observed compared with infection by other bacteria. Conclusions: Considering M abscessus, a smaller collagen-free contact surface shows better resistance to infection, however, depending on the type of bacteria, prostheses with a large surface, and covered with collagen shows reduced resistance to infection, worse integration, and worse clinical outcome. (C) 2016 Elsevier Inc. All rights reserved.Peer reviewe

LiPISC: A Lightweight and Flexible Method for Privacy-Aware Intersection Set Computation

Privacy-aware intersection set computation (PISC) can be modeled as secure multi-party computation. The basic idea is to compute the intersection of input sets without leaking privacy. Furthermore, PISC should be sufficiently flexible to recommend approximate intersection items. In this paper, we reveal two previously unpublished attacks against PISC, which can be used to reveal and link one input set to another input set, resulting in privacy leakage. We coin these as Set Linkage Attack and Set Reveal Attack. We then present a lightweight and flexible PISC scheme (LiPISC) and prove its security (including against Set Linkage Attack and Set Reveal Attack)

Anomalies in the Charge Yields of Fission Fragments from the U(n,f)238 Reaction

Fast-neutron-induced fission of 238U at an energy just above the fission threshold is studied with a novel technique which involves the coupling of a high-efficiency γ-ray spectrometer (MINIBALL) to an inverse-kinematics neutron source (LICORNE) to extract charge yields of fission fragments via γ−γ coincidence spectroscopy. Experimental data and fission models are compared and found to be in reasonable agreement for many nuclei; however, significant discrepancies of up to 600% are observed, particularly for isotopes of Sn and Mo. This indicates that these models significantly overestimate the standard 1 fission mode and suggests that spherical shell effects in the nascent fission fragments are less important for low-energy fast-neutron-induced fission than for thermal neutron-induced fission. This has consequences for understanding and modeling the fission process, for experimental nuclear structure studies of the most neutron-rich nuclei, for future energy applications (e.g., Generation IV reactors which use fast-neutron spectra), and for the reactor antineutrino anomaly

Linking seed photosynthesis and evolution of the Australian and Mediterranean seagrass genus Posidonia

Recent findings have shown that photosynthesis in the skin of the seed of Posidonia oceanica enhances seedling growth. The seagrass genus Posidonia is found only in two distant parts of the world, the Mediterranean Sea and southern Australia. This fact led us to question whether the acquisition of this novel mechanism in the evolution of this seagrass was a pre-adaptation prior to geological isolation of the Mediterranean from Tethys Sea in the Eocene. Photosynthetic activity in seeds of Australian species of Posidonia is still unknown. This study shows oxygen production and respiration rates, and maximum PSII photochemical efficiency (Fv : Fm) in seeds of two Australian Posidonia species (P. australis and P. sinuosa), and compares these with previous results for P. oceanica. Results showed relatively high oxygen production and respiratory rates in all three species but with significant differences among them, suggesting the existence of an adaptive mechanism to compensate for the relatively high oxygen demands of the seeds. In all cases maximal photochemical efficiency of photosystem II rates reached similar values. The existence of photosynthetic activity in the seeds of all three species implicates that it was an ability probably acquired from a common ancestor during the Late Eocene, when this adaptive strategy could have helped Posidonia species to survive in nutrient-poor temperate seas. This study sheds new light on some aspects of the evolution of marine plants and represents an important contribution to global knowledge of the paleogeographic patterns of seagrass distribution

Morphological and functional effects of graphene on the synthesis of uranium carbide for isotopes production targets

The development of tailored targets for the production of radioactive isotopes represents an active field in nuclear research. Radioactive beams find applications in nuclear medicine, in astrophysics, matter physics and materials science. In this work, we study the use of graphene both as carbon source for UO2 carbothermal reduction to produce UCx targets, and also as functional properties booster. At fixed composition, the UCx target grain size, porosity and thermal conductivity represent the three main points that affect the target production efficiency. UCx was synthesized using both graphite and graphene as the source of carbon and the target properties in terms of composition, grain size, porosity, thermal diffusivity and thermal conductivity were studied. The main output of this work is related to the remarkable enhancement achieved in thermal conductivity, which can profitably improve thermal dissipation during operational stages of UCx targets.JRC.G.I.5-Advanced Nuclear Knowledg