Suchergebnisse

14 páginas; 11 tablas; 1 figura ; Nowadays, information and communications technology systems are fundamental assets of our social and economical model, and thus they should be properly protected against the malicious activity of cybercriminals. Defence mechanisms are generally articulated around tools that trace and store information in several ways, the simplest one being the generation of plain text files coined as security logs. Such log files are usually inspected, in a semi-automatic way, by security analysts to detect events that may affect system integrity, confidentiality and availability. On this basis, we propose a parameter-free method to detect security incidents from structured text regardless its nature. We use the Normalized Compression Distance to obtain a set of features that can be used by a Support Vector Machine to classify events from a heterogeneous cybersecurity environment. In particular, we explore and validate the application of our method in four different cybersecurity domains: HTTP anomaly identification, spam detection, Domain Generation Algorithms tracking and sentiment analysis. The results obtained show the validity and flexibility of our approach in different security scenarios with a low configuration burden. ; This research has received funding from the European Union's Horizon 2020 Research and Innovation Programme under grant agreement No. 872855 (TRESCA project), from the Comunidad de Madrid (Spain) under the projects CYNAMON (P2018/TCS-4566) and S2017/BMD-3688, co-financed with FSE and FEDER EU funds, by the Consejo Superior de Investigaciones Científicas (CSIC) under the project LINKA20216 ("Advancing in cybersecurity technologies", i-LINK+ program), and by Spanish project MINECO/FEDER TIN2017-84452-R.

Nowadays, information and communications technology systems are fundamental assets of our social and economical model, and thus they should be properly protected against the malicious activity of cybercriminals. Defence mechanisms are generally articulated around tools that trace and store information in several ways, the simplest one being the generation of plain text files coined as security logs. Such log files are usually inspected, in a semi-automatic way, by security analysts to detect events that may affect system integrity, confidentiality and availability. On this basis, we propose a parameter-free method to detect security incidents from structured text regardless its nature. We use the Normalized Compression Distance to obtain a set of features that can be used by a Support Vector Machine to classify events from a heterogeneous cybersecurity environment. In particular, we explore and validate the application of our method in four different cybersecurity domains: HTTP anomaly identification, spam detection, Domain Generation Algorithms tracking and sentiment analysis. The results obtained show the validity and flexibility of our approach in different security scenarios with a low configuration burden ; This research has received funding from the European Union's Horizon 2020 Research and Innovation Programme under grant agreement No. 872855 (TRESCA project), from the Comunidad de Madrid (Spain) under the projects CYNAMON (P2018/TCS-4566) and S2017/BMD-3688, co-financed with FSE and FEDER EU funds, by the Consejo Superior de Investigaciones Científicas (CSIC) under the project LINKA20216 ("Advancing in cybersecurity technologies", i-LINK+ program), and by Spanish project MINECO/FEDER TIN2017-84452-R

The aim of this study was to characterize the relationship between the intake of the major nutrients and prognosis in breast cancer. A cohort based on 1350 women with invasive (stage I-IV) breast cancer (BC) was followed up. Information about their dietary habits before diagnosis was collected using a semi-quantitative Food Frequency Questionnaire. Participants without FFQ or with implausible energy intake were excluded. The total amount consumed of each nutrient (Kcal/day) was divided into tertiles, considering as "high intakes" those above third tertile. The main effect studied was overall survival. Cox regression was used to assess the association between death and nutrient intake. During a median follow-up of 6.5 years, 171 deaths were observed. None of the nutrients analysed was associated with mortality in the whole sample. However, in normal-weight women (BMI 18.5–25 kg/m2) a high intake of carbohydrates (≥809 Kcal/day), specifically monosaccharides (≥468 Kcal/day), worsened prognostic compared to lowest (≤352 Kcal/day). Haz-ard Ratios (HRs) for increasing tertiles of intake were HR:2.22 95%CI (1.04 to 4.72) and HR:2.59 95%CI (1.04 to 6.48), respectively (p trend = 0.04)). Conversely, high intakes of polyunsaturated fats (≥135Kcal/day) improved global survival (HR: 0.39 95%CI (0.15 to 1.02) p-trend = 0.05) compared to the lowest (≤92.8 kcal/day). In addition, a protective effect was found substituting 100 kcal of carbohydrates with 100 kcal of fats in normal-weight women (HR: 0.76 95% CI (0.59 to 0.98)). Likewise, in premenopausal women a high intake of fats (≥811Kcal/day) showed a protective effect (HR:0.20 95%CI (0.04 to 0.98) p trend = 0.06). Finally, in Estrogen Receptors (ER) negative tumors, we found a protective effect of high intake of animal proteins (≥238 Kcal/day, HR: 0.24 95% CI (0.06 to 0.98). According to our results, menopausal status, BMI and ER status could play a role in the relationship between diet and BC survival and must be taken into account when studying the influence of dif-ferent nutrients ; This research was funded by the 'Acción Transversal del Cancer', approved by the Spanish Ministry Council on the 11th October 2007, by the Instituto de Salud Carlos III, co-founded by FEDER funds –'a way to build Europe' (grants PI08/1770, PI08/0533, PI08/1359, PI09/00773, PI09/01286, PI09/01903, PI09/02078, PI09/01662, PI11/01403, PI11/01889, PI11/00226, PI11/01810, PI11/02213, PI12/00488, PI12/00265, PI12/01270, PI12/00715, PI12/00150, PI14/01219, PI14/00613, and PI15/00069). Support was also provided by the Fundación Marqués de Valdecilla (grant API 10/09); the Junta de Castilla y León (grant LE22A10-2); the Consejería de Salud of the Junta de Andalucía (2009-S0143); the Conselleria de Sanitat of the Generalitat Valenciana (grant AP 061/10); the Recercaixa (grant 2010ACUP 00310); the Regional Government of the Basque Country; the Consejería de Sanidad de la Región de Murcia; European Commission grants FOOD-CT-2006-036224-HIWATE;the Spanish Association Against Cancer (AECC) Scientific Foundation; the Catalan Government DURSI (grant 2014SGR647); the Fundación Caja de Ahorros de Asturias; the University of Oviedo and COST action BM1206 Eucolongene

Perinatal hypoxia is a severe condition that may harm fetus organs permanently. When the fetus brain is partially deprived from oxygen, the control of the fetal heart rate (FHR) is affected. We hypothesized that advanced processing of the FHR can reveal whether the fetus is under perinatal hypoxia. We analyzed FHR morphology with normalized compression distance (NCD) that compares two arbitrary sequences and outputs their dissimilarity. This parameter-free measure exploits linear and non-linear relations in the data and allows the comparison of sequences of different sizes. It was applied to raw FHR sequences and to a set of statistics computed from them (e.g. moments on 5 minutes signal windows). We classified the cases from the NCD dissimilarity matrix by using a simple nearest neighbor classifier and leave-one-out cross-validation. Best results in a database with 26 FHR recordings (13 controls and 13 cases) were provided by the central moment of order 3 calculated over sliding windows of 5 minutes on the interval from 4 to 3 hours to delivery. The resulting accuracy was 0.88 with sensitivity 0.92 and specificity 0.85. ; Spanish Government under the Research Project TEC2010-19263. Juan de la Cierva Program of the Spanish Ministry of Science and Innovation (Ref: JCI-2011-11150). ; Teor?a de la Se?al y Comunicaciones

This work is devoted to providing patients and physicians with a novel tool to analyse and extract information for better management of type I diabetes. We use a clustering methodology based on the normalised compression distance to identify different profiles of days. The methodology has been validated using data generated by a simulator of virtual patients, which include an exercise model. Profiling daily data can help physicians and patients cope with information overload and assist in future planning for improved treatments and self-management of diabetes type 1 ; Partially supported by the Spanish Ministry of Science and Innovation through grant DPI 2013-46982-C2-2-R and the Government of Catalonia trough grant SGR14-1052

Membership, structure, self-management rights; role in economic reform.

International audience ; Pressed by creditor institutions, Greece implemented a national means-tested General Minimum Income (GMI) targeting the extreme poor. Based on a 2017-2019 qualitative survey in the Attica region, we examine the new policy and engage in a critical analysis of its deployment. Our investigation places the Greek experiment in its European context, which prioritizes workfare and residualized welfare. It highlights the arbitrary character of the biopolitical management of populations and its overall purposefulness-the regularisation of the poor-and discusses difficulties emerging at local micromanagement level that often translate into inequalities and injustices, contrary to the institutions' stated aims. ; Sous la pression de ses créditeurs, la Grèce a mis en place un revenu minimum général (RMG) national sous condition de ressources, destiné aux personnes en situation d'extrême pauvreté. Sur la base d'une enquête qualitative réalisée entre 2017 et 2019 dans la région de l'Attique, nous examinons la nouvelle politique et procédons à une analyse critique de son déploiement. Notre enquête situe l'expérience grecque dans son contexte européen, qui tend à promouvoir le workfare et une protection sociale réduite, sous conditions de ressources. Elle met en évidence le caractère arbitraire de la gestion biopolitique des populations et la finalité de cette politique - la régularisation des pauvres; elle discute les difficultés qui apparaissent au niveau de la microgestion locale et qui se traduisent souvent par des inégalités et des injustices, contraires aux objectifs déclarés des institutions.

International audience ; Pressed by creditor institutions, Greece implemented a national means-tested General Minimum Income (GMI) targeting the extreme poor. Based on a 2017-2019 qualitative survey in the Attica region, we examine the new policy and engage in a critical analysis of its deployment. Our investigation places the Greek experiment in its European context, which prioritizes workfare and residualized welfare. It highlights the arbitrary character of the biopolitical management of populations and its overall purposefulness-the regularisation of the poor-and discusses difficulties emerging at local micromanagement level that often translate into inequalities and injustices, contrary to the institutions' stated aims. ; Sous la pression de ses créditeurs, la Grèce a mis en place un revenu minimum général (RMG) national sous condition de ressources, destiné aux personnes en situation d'extrême pauvreté. Sur la base d'une enquête qualitative réalisée entre 2017 et 2019 dans la région de l'Attique, nous examinons la nouvelle politique et procédons à une analyse critique de son déploiement. Notre enquête situe l'expérience grecque dans son contexte européen, qui tend à promouvoir le workfare et une protection sociale réduite, sous conditions de ressources. Elle met en évidence le caractère arbitraire de la gestion biopolitique des populations et la finalité de cette politique - la régularisation des pauvres; elle discute les difficultés qui apparaissent au niveau de la microgestion locale et qui se traduisent souvent par des inégalités et des injustices, contraires aux objectifs déclarés des institutions.