Nuclear Recoil Scintillation Linearity of a High Pressure 4^4He Gas Detector

We investigate scintillation linearity of a commercial high pressure $^4$He gas detector using monoenergetic 2.8 MeV neutrons from a deuterium-deuterium fusion neutron generator. The scintillation response of the detector was measured for a range of recoil energies between 83 keV and 626 keV by tagging neutrons scattering into fixed angles with a far-side organic scintillator detector. Detailed Monte Carlo simulations were compared to experimental data to determine the linearity of the detector response by comparing the scaling of the energy deposits in the simulations to the detector output. In this analysis, a linear scintillation response corresponds to a consistent value for the scaling factor between simulated energy deposits and experimental data for several different scattering angles. We demonstrate that the detector can be used to detect fast neutron interactions down to 83 keV recoil energies and can be used to characterize low-energy neutron sources, one of its potential applications

Enhancing Network Security: Host Trustworthiness Estimation

Network connected devices has become inherent part of our lives. These devices have come to be more and more mobile and are target of various malware attacks. An inability to guarantee or check proper security settings of such devices poses a serious risk to network security. In this paper we propose a novel concept of flow based host trustworthiness estimation. The estimated trustworthiness determines a level of the risk to the network security the host posses. This concept enables network operators to identify a potential dangerous host in their network and take an appropriate precautions. Models used for trustworthiness estimation are based on scoring either single events or host characteristics. In order to be able to estimate trustworthiness of a host even in large scale networks, the data used for estimation are reduced only to extended network flows. The research is in its initial phase and will conclude with Ph.D. thesis in three years.Zařízení připojené do sítě se stala neodmyslitelnou součástí našeho života. Tyto zařízení jsou stále mobilnější a stávají se cílem různých druhů škodlivého softwaru. Neschopnost zaručit či prověřit správné nastavení bezpečnostního zajištění těchto zařízení představuje nezanedbatelné riziko pro bezpečnost počítačové sítě. V tomto článku je představen koncept pro odhadování míry důvěryhodnosti daného zařízení. Míra důvěryhodnosti reprezentuje míru rizika, kterou zařízení představuje pro síťovou bezpečnost. Tento koncept umožní správcům sítě identifikovat potenciálně nebezpečné zařízení. Modely pro odhadování důvěryhodnosti jsou založeny na scoringu buď jednotlivých událostí nebo charakteristik zařízení. Aby bylo možné odhadovat důvěryhodnost zařízené dokonce i v rozsáhlých sítích, pro odhad důvěryhodnosti jsou využívána pouze data ze síťových toků. Výzkum je v jeho počáteční fázi a bude v horizontu tří let završen disertační prací

Factors associated with 2009 pandemic influenza A (H1N1) vaccination acceptance among university students from India during the post-pandemic phase

<p>Abstract</p> <p>Background</p> <p>There was a low adherence to influenza A (H1N1) vaccination program among university students and health care workers during the pandemic influenza in many parts of the world. Vaccination of high risk individuals is one of the recommendations of World Health Organization during the post-pandemic period. It is not documented about the student's knowledge, attitude and willingness to accept H1N1 vaccination during the post-pandemic period. We aimed to analyze the student's knowledge, attitude and willingness to accept H1N1 vaccination during the post-pandemic period in India.</p> <p>Methods</p> <p>Vaccine against H1N1 was made available to the students of Vellore Institute of Technology, India from September 2010. The data are based on a cross-sectional study conducted during October 2010 to January 2011 using a self-administered questionnaire with a representative sample of the student population (N = 802).</p> <p>Results</p> <p>Of the 802 respondents, only 102/802 (12.7%) had been vaccinated and 105/802 (13%) planned to do so in the future, while 595/802 (74%) would probably or definitely not get vaccinated in the future. The highest coverage was among the female (65/102, 63.7%) and non-compliance was higher among men in the group (384/595; 64.5%) (p < 0.0001). The representation of students from school of Bio-sciences and Bio-technology among vaccinees is significantly higher than that of other schools. Majority of the study population from the three groups perceived vaccine against H1N1 as the effective preventive measure when compared to other preventive measures. 250/595 (42%) of the responders argued of not being in the risk group. The risk perception was significantly higher among female (p < 0.0001). With in the study group, 453/802 (56.4%) said that they got the information, mostly from media.</p> <p>Conclusions</p> <p>Our study shows that the vaccination coverage among university students remains very low in the post-pandemic period and doubts about the safety and effectiveness of the vaccine are key elements in their rejection. Our results indicate a need to provide accessible information about the vaccine safety by scientific authorities and fill gaps and confusions in this regard.</p

Next Generation Application-Aware Flow Monitoring

Deep packet inspection (DPI) and IP flow monitoring are frequently used network monitoring approaches. Although the DPI provides application visibility, detailed examination of every packet is computationally intensive. The IP flow monitoring achieves high performance by processing only packet headers, but provides less details about the traffic itself. Application-aware flow monitoring is proposed as an attempt to combine DPI accuracy and IP flow monitoring performance. However, the impacts, benefits and disadvantages of application flow monitoring have not been studied in detail yet. The work proposed in this paper attempts to rectify this lack of research. We also propose a next generation flow measurement for application monitoring. The flows will represent events within the application protocol, e.g., web page download, instead of packet stream. Finally, we will investigate the performance of different approaches to application classification and application parsing with a computational complexity in mind.Často používané metody monitorování sítě jsou hloubková inspekce paketů (DPI) a monitorování síťových IP toků. Přestože DPI poskytuje formace z aplikační vrstvy, podrobné zkoumání každého paketu je výpočetně náročné. Monitorování pomocí IP síťových toků dosahuje vysokého výkonu, protože zpracovává pouze záhlaví paketů, ale také poskytuje méně informací o provozu samotném. Měření aplikačních síťových toků bylo navrženo jako pokus zkombinovat přesnost DPI a výkon IP síťových toků. Dopady, výhody a nevýhody aplikačních síťových toků zatím ale nebyly dostatečně prostudovány. Práce navrhovaná v tomto článku se snaží napravit tento nedostatek výzkumu. Navíc také navrhujeme další generaci měření síťových toků. Tyto toky budou místo sekvence paketů reprezentovat události v aplikačních protokolech, například stažení webové stránky. Budeme se také zabývat výkonem a výpočetní složitostí různých přístupů ke klasifikaci provozu a zpracování aplikačních protokolů