Near real-time security system applied to SDN environments in IoT networks using convolutional neural network

[EN] The Internet of Things (IoT) paradigm brings new and promising possibilities for services and products. The heterogeneity of IoT devices highlights the inefficiency of traditional networks' structures to support their specific requirements due to their lack of flexibility. Thus, Software-defined Networking (SDN) is commonly associated with IoT since this architecture provides a more flexible and manageable network environment. As shown by recent events, IoT devices may be used for large scale Distributed Denial of Service (DDoS) attacks due to their lack of security. This kind of attack is commonly detected and mitigated at the destination-end network but, due to the massive volume of information that IoT botnets generate, this approach is becoming impracticable. We propose in this paper a near real-time SDN security system that both prevents DDoS attacks on the source-end network and protects the sources SDN controller against traffic impairment. For this, we apply and test a Convolutional Neural Network (CNN) for DDoS detection, and describe how the system could mitigate the detected attacks. The performance outcomes were performed in two test scenarios, and the results pointed out that the proposed SDN security system is promising against next-generation DDoS attacks. (C) 2020 Published by Elsevier Ltd.This study was financed in part by the National Council for Scientific and Technological Development (CNPq) of Brazil under Grants 310668/2019-0 and 309335/2017-5; by the Ministerio de Economia y Competitividad in the "Programa Estatal de Fomento de la Investigacion Cientifica y Tecnica de Excelencia, Subprograma Estatal de Generacion de Conocimiento" within the project under Grant TIN2017-84802-C2-1-P; by FCT/MCTES through national funds and when applicable co-funded EU funds under the Project UIDB/EEA/50008/2020; and by the Coordenacao de Aperfeicoamento de Pessoal de Nivel Superior (CAPES) by the granting of a scholarship through the "Programa de Doutorado Sanduche no Exterior (PDSE) 2019". Finally, this work was supported by Federal University of Parana(UFPR) under Project Banpesq/2014016797.De Assis, MVO.; Carvalho, LF.; Rodrigues, JJPC.; Lloret, J.; Proenca Jr, ML. (2020). Near real-time security system applied to SDN environments in IoT networks using convolutional neural network. Computers & Electrical Engineering. 86:1-16. https://doi.org/10.1016/j.compeleceng.2020.1067381168

Science teacher as classroom manager in online classes

Exploratory sequential mixed research was conducted to characterize science teachers' experiences as classroom managers in their online classes. There were 15 science teachers from elementary and secondary schools in Cebu, Philippines, participated in the phenomenological study, and 30 teachers responded to the developed tool on their management and its effect on students’ performance. Thematic analysis of the interview results unveiled a series of stages, including a different start of the school year and reintegration of online management skills that eventually led to autonomy in online classes and satisfying academic outcomes. Further exploration of the quantitative aspect of the study revealed that they have very good management, which has led to a good effect on students' performance. The different innovations in classroom management strategies by science teachers led to effective online classes. Training on proactive management and positive feedbacking are recommended

A1C as a Diagnostic Criteria for Diabetes in Low- and Middle-Income Settings: Evidence from Peru

OBJECTIVES: To determine the prevalence of type 2 diabetes mellitus, in three groups of Peruvian adults, using fasting glucose and glycosylated hemoglobin (A1C). METHODOLOGY/PRINCIPAL FINDINGS: This study included adults from the PERU MIGRANT Study who had fasted ≥ 8 h. Fasting glucose ≥ 126 mg/dL and A1C ≥ 6.5% were used, separately, to define diabetes. Subjects with a current diagnosis of diabetes were excluded. 964 of 988 subjects were included in this analysis. Overall, 0.9% (95%CI 0.3-1.5) and 3.5% (95%CI 2.4-4.7) had diabetes using fasting glucose and A1C criteria, respectively. Compared to those classified as having diabetes using fasting glucose, newly classified subjects with diabetes using A1C (n = 25), were older, poorer, thinner and more likely to come from rural areas. Of these, 40% (10/25) had impaired fasting glucose (IFG). CONCLUSIONS: This study shows that the use of A1C as diagnostic criteria for type 2 diabetes mellitus identifies people of different characteristics than fasting glucose. In the PERU MIGRANT population using A1C to define diabetes tripled the prevalence; the increase was more marked among poorer and rural populations. More than half the newly diagnosed people with diabetes using A1C had normal fasting glucose

Location of chlorogenic acid biosynthesis pathway and polyphenol oxidase genes in a new interspecific anchored linkage map of eggplant

© Gramazio et al.; licensee BioMed Central. 2014. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated

Multilocus Bayesian Estimates of Intra-Oceanic Genetic Differentiation, Connectivity, and Admixture in Atlantic Swordfish (Xiphias gladius L.)

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Long-term survival in patients with non-small cell lung cancer and synchronous brain metastasis treated with whole-brain radiotherapy and thoracic chemoradiation

<p>Abstract</p> <p>Background</p> <p>Brain metastases occur in 30-50% of Non-small cell lung cancer (NSCLC) patients and confer a worse prognosis and quality of life. These patients are usually treated with Whole-brain radiotherapy (WBRT) followed by systemic therapy. Few studies have evaluated the role of chemoradiotherapy to the primary tumor after WBRT as definitive treatment in the management of these patients.</p> <p>Methods</p> <p>We reviewed the outcome of 30 patients with primary NSCLC and brain metastasis at diagnosis without evidence of other metastatic sites. Patients were treated with WBRT and after induction chemotherapy with paclitaxel and cisplatin for two cycles. In the absence of progression, concurrent chemoradiotherapy for the primary tumor with weekly paclitaxel and carboplatin was indicated, with a total effective dose of 60 Gy. If disease progression was ruled out, four chemotherapy cycles followed.</p> <p>Results</p> <p>Median Progression-free survival (PFS) and Overall survival (OS) were 8.43 ± 1.5 and 31.8 ± 15.8 months, respectively. PFS was 39.5% at 1 year and 24.7% at 2 years. The 1- and 2-year OS rates were 71.1 and 60.2%, respectively. Three-year OS was significantly superior for patients with N0-N1 stage disease vs. N2-N3 (60 vs. 24%, respectively; Response rate [RR], 0.03; <it>p</it>= 0.038).</p> <p>Conclusions</p> <p>Patients with NSCLC and brain metastasis might benefit from treatment with WBRT and concurrent thoracic chemoradiotherapy. The subgroup of N0-N1 patients appears to achieve the greatest benefit. The result of this study warrants a prospective trial to confirm the benefit of this treatment.</p