Damage Patterns

This chapter provides an overview of the macroseismic effects of the Bhuj earthquake. Such information is useful for several reasons. First, direct information about the vulnerability of structures to strong ground motion is useful for assessing, and perhaps mitigating, the hazard posed to similar structures by future large earthquakes. Secondly, given the paucity of instrumental recordings of the Bhuj earthquake, macroseismic data can provide useful information about the spatial variation of ground motions. Finally, detailed damage assessments for this earthquake can be compared to available accounts of historic earthquakes in India and other similar tectonic regimes around the world. These comparisons will provide additional insight into the magnitude of important earthquakes for which there are few or no instrumental recordings. The Bhuj earthquake is of particular interest because of the possibility that it represents an analog for the principal New Madrid (central United States) earthquakes of 1811-1812. The Bhuj earthquake occurred much closer to an active plate boundary than did the New Madrid events, and the Bhuj earthquake might therefore be considered a plate boundary-related event. However, in both cases, the regions primarily affected by the earthquake are stable continental interiors with low attenuation. A quantification of damage patterns, such as that presented in this chapter, can provide useful insight into the attenuation and frequency content of ground motions, which may in turn be useful in resolving whether the Bhuj earthquake should be considered interplate or intraplate for the purpose of data classification. This chapter combines two different approaches to quantify macroseismic effects of the Bhuj earthquake. First, a large-scale map of intensities was compiled based on media accounts. Second, ground-level surveys of damage in towns and villages across the epicentral area by the India-U.S. Geotechnical Earthquake Engineering Reconnaissance Team were synthesized. This approach provides both coarse- and fine-scale overviews of damage, as well as an opportunity to compare detailed ground-based intensity results to a "broad brush" intensity value determined from one or a small handful of media accounts for any one location

KYPO: A Tool for Collaborative Study of Cyberattacks in Safe Cloud Environment

This paper introduces the KYPO -- a cloud-based virtual environment faithfully simulating real networks and enabling users to study cyber attacks as well as to train users in isolated and controlled environment. Particularly, the paper focuses on the user environment and visualizations, providing views and interactions improving the understanding of processes emerged during experiments. Web user interface of the KYPO system supports several collaboration modes enabling the participants to experiment and replay different types of security related tasks

Electro oxidation of Malachite Green and Modeling Using ANN

This study involves the electro-oxidation of malachite green, a triphenyl methane dye, extensively used in industries and aquaculture, and later banned in most developed countries because of its potential carcinogenicity, mutagenicity and teratogenicity in mammals. The study is conducted in a batch electro-chemical reactor using the catalytic anode (made of noble oxide coated, RuOx-TiOx, titanium expanded mesh) that mediates the oxidation of organic species by the formation of higher oxidation state oxides of the metal (e.g., RuO2 or IrO2). The operating variables are current density, electrolysis time and initial dye concentration. Complete removal of the dye has been reported by 41 minutes of treatment at a current density of 2.2 A dm–2 for the case of initial dye concentration of 200 mg L–1. The experimental data are modeled using back-propagation artificial neural network. The results were compared with experimental observations, and found that the model predictions adequately match experimental observations. Combination of the factors giving complete removal of the dye has also been commented

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

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