A data-driven approach for Network Intrusion Detection and Monitoring based on Kernel Null Space

International audienceIn this study, we propose a new approach to determine intrusions of network in real-time based on statistical process control technique and kernel null space method. The training samples in a class are mapped to a single point using the Kernel Null Foley-Sammon Transform. The Novelty Score are computed from testing samples in order to determine the threshold for the real-time detection of anomaly. The efficiency of the proposed method is illustrated over the KDD99 data set. The experimental results show that our new method outperforms the OCSVM and the original Kernel Null Space method by 1.53% and 3.86% respectively in terms of accuracy

Lung Volume Reduction Surgery in Patients with Heterogenous Emphysema: Selecting Perspective

BACKGROUND: Lung volume reduction surgery (LVRS) was introduced to alleviate clinical conditions in selected patients with heterogenous emphysema. Clarifying the most suitable patients for LVRS remained unclear. AIM: This study was undertaken to specifically analyze the preoperative factor affecting to LVRS. METHODS: The prospective study was conducted at 103 Military Hospital between July 2014 and April 2016. Severe heterogenous emphysema patients were selected to participate in the study. The information, spirometry, and body plethysmographic pulmonary function tests in 31 patients who underwent LVRS were compared with postoperative outcomes (changing in FEV1 and CAT scale). RESULTS: Of the 31 patients, there was statistically significant difference in the outcome of functional capacity, lung function between two groups (FEV1 ≤ 50% and > 50%) (∆FEV1: 22.46 vs 18.32%; p = 0.042. ∆CAT: 6.85 vs 5.07; p = 0.048). Changes of the FEV1 and CAT scale were no statistically significant differences in three groups residual volume. Patients with total lung capacity < 140% had more improved than others (∆FEV1: 23.81 vs 15.1%; p = 0.031). CONCLUSION: Preoperative spirometry and body plethysmographic pulmonary function tests were useful measures to selected severe heterogenous emphysema patients for LVRS. Patients with FEV1 ≤ 50%, TLC in the range of 100-140% should be selected

A Clinically Oriented antimicrobial Resistance surveillance Network (ACORN): pilot implementation in three countries in Southeast Asia, 2019-2020

Background: Case-based surveillance of antimicrobial resistance (AMR) provides more actionable data than isolate- or sample-based surveillance. We developed A Clinically Oriented antimicrobial Resistance surveillance Network (ACORN) as a lightweight but comprehensive platform, in which we combine clinical data collection with diagnostic stewardship, microbiological data collection and visualisation of the linked clinical-microbiology dataset. Data are compatible with WHO GLASS surveillance and can be stratified by syndrome and other metadata. Summary metrics can be visualised and fed back directly for clinical decision-making and to inform local treatment guidelines and national policy. Methods: An ACORN pilot was implemented in three hospitals in Southeast Asia (1 paediatric, 2 general) to collect clinical and microbiological data from patients with community- or hospital-acquired pneumonia, sepsis, or meningitis. The implementation package included tools to capture site and laboratory capacity information, guidelines on diagnostic stewardship, and a web-based data visualisation and analysis platform. Results: Between December 2019 and October 2020, 2294 patients were enrolled with 2464 discrete infection episodes (1786 community-acquired, 518 healthcare-associated and 160 hospital-acquired). Overall, 28-day mortality was 8.7%. Third generation cephalosporin resistance was identified in 54.2% (39/72) of E. coli and 38.7% (12/31) of K. pneumoniae isolates. Almost a quarter of S. aureus isolates were methicillin resistant (23.0%, 14/61). 290/2464 episodes could be linked to a pathogen, highlighting the level of enrolment required to achieve an acceptable volume of isolate data. However, the combination with clinical metadata allowed for more nuanced interpretation and immediate feedback of results. Conclusions: ACORN was technically feasible to implement and acceptable at site level. With minor changes from lessons learned during the pilot ACORN is now being scaled up and implemented in 15 hospitals in 9 low- and middle-income countries to generate sufficient case-based data to determine incidence, outcomes, and susceptibility of target pathogens among patients with infectious syndromes

Does varicocele repair improve conventional semen parameters? A meta-analytic study of before-after data

Purpose The purpose of this meta-analysis is to study the impact of varicocele repair in the largest cohort of infertile males with clinical varicocele by including all available studies, with no language restrictions, comparing intra-person conventional semen parameters before and after the repair of varicoceles. Materials and Methods The meta-analysis was performed according to PRISMA-P and MOOSE guidelines. A systematic search was performed in Scopus, PubMed, Cochrane, and Embase databases. Eligible studies were selected according to the PICOS model (Population: infertile male patients with clinical varicocele; Intervention: varicocele repair; Comparison: intra-person before-after varicocele repair; Outcome: conventional semen parameters; Study type: randomized controlled trials [RCTs], observational and case-control studies). Results Out of 1,632 screened abstracts, 351 articles (23 RCTs, 292 observational, and 36 case-control studies) were included in the quantitative analysis. The before-and-after analysis showed significant improvements in all semen parameters after varicocele repair (except sperm vitality); semen volume: standardized mean difference (SMD) 0.203, 95% CI: 0.129–0.278; p<0.001; I2=83.62%, Egger’s p=0.3329; sperm concentration: SMD 1.590, 95% CI: 1.474–1.706; p<0.001; I2=97.86%, Egger’s p<0.0001; total sperm count: SMD 1.824, 95% CI: 1.526–2.121; p<0.001; I2=97.88%, Egger’s p=0.0063; total motile sperm count: SMD 1.643, 95% CI: 1.318–1.968; p<0.001; I2=98.65%, Egger’s p=0.0003; progressive sperm motility: SMD 1.845, 95% CI: 1.537%–2.153%; p<0.001; I2=98.97%, Egger’s p<0.0001; total sperm motility: SMD 1.613, 95% CI 1.467%–1.759%; p<0.001; l2=97.98%, Egger’s p<0.001; sperm morphology: SMD 1.066, 95% CI 0.992%–1.211%; p<0.001; I2=97.87%, Egger’s p=0.1864. Conclusions The current meta-analysis is the largest to date using paired analysis on varicocele patients. In the current meta-analysis, almost all conventional semen parameters improved significantly following varicocele repair in infertile patients with clinical varicocele. Keywords Controlled before-after studies; Infertility, male; Meta-analysis; Varicocel

Federated Learning-Based Explainable Anomaly Detection for Industrial Control Systems

International audienceWe are now witnessing the rapid growth of advanced technologies and their application, leading to Smart Manufacturing (SM). The Internet of Things (IoT) is one of the main technologies used to enable smart factories, which is connecting all the industrial assets, including machines and control systems, with the information systems and the business processes. Industrial Control Systems of smart IoT-based factories are one of the top industries attacked by numerous threats. With the distributed structure of plenty of IoT front-end sensing devices in SM, an effectively distributed architecture of an anomaly detection system should be created that can produce high detection performance while being able to handle the cybersecurity task in fast time scale. In this paper, we propose the so-called FedeX architecture that integrates Federated Learning (FL) into the detection learning model to ensure data privacy that can not be guaranteed by the centralized learning approach while still achieving high detection performance in comparison with a variety of recent research proposed solutions. FedeX is also robust in terms of running time and hardware consumption which allows us to deploy the detecting task on top of edge computing infrastructure in real-time. To the best of our knowledge, FedeX is also the first framework that uses eXplainable Artificial Intelligence (XAI) to deal with the problem of "black-box" anomaly detection for Industrial Control Systems

Detecting Cyberattacks using Anomaly Detection in Industrial Control Systems: A Federated Learning approach

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Light-Weight Federated Learning-based Anomaly Detection for Time-Series data in Industrial Control Systems

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Brain atrophy and disability worsening in primary progressive multiple sclerosis: Insights from the INFORMS study

Objective: To investigate the relationship between brain volume and disability worsening over ≥3 years in the natural history of primary progressive multiple sclerosis using data from the placebo group of the INFORMS trial (n = 487; clinicaltrials.gov NCT00731692). Methods: Magnetic resonance imaging scans were collected annually. Brain volume loss was determined using SIENA. Patients were stratified by baseline normalized brain volume after adjusting for demographic and disease-burden covariates. Results: Baseline normalized brain volume was predictive of disability worsening: Risk of 3-month confirmed disability progression was reduced by 36% for high versus low baseline normalized brain volume (Cox's model hazard ratio 0.64, P = 0.0339; log-rank test: P = 0.0297). Moreover, on-study brain volume loss was significantly associated with disability worsening (P = 0.012) and was evident in patients with or without new lesions or relapses. Brain volume loss depended significantly on baseline T2 lesion volume (P < 0.0001). Despite low inflammatory activity at baseline (13% of patients had gadolinium-enhancing lesions) and throughout the study (mean 0.5 new/enlarging T2 lesions and 172 mm 3 T2 lesion volume increase per year), baseline T2 lesion volume was substantial (mean 10 cm 3 ). Lower normalized brain volume at baseline correlated with higher baseline T2 volume and older age (both P < 0.0001). Interpretation: Baseline brain volume and the rate of ongoing brain atrophy are significantly associated with disability worsening in primary progressive multiple sclerosis. Brain volume loss is significantly related to baseline T2 lesion volume, but partially independent of new lesion activity, which might explain the limited efficacy of anti-inflammatory treatment