A Shared-Disk Database Approach towards Securing Data in the Cloud

The increasing popularity of cloud computing in distributed computing environment may have positive as well as negative effects on the data security of service consumers. This paper highlights some major security issues existing in current cloud computing environments. The primary issue to be dealt with when talking about security in a cloud is protection of the data. The idea is to construct a privacy preserving repository where data sharing services can update and control the access and limit the usage of their shared data, instead of submitting data to central authorities, and, hence, the shared-disk database architecture will promote data sharing and privacy of data. This paper aims at simultaneously achieving data confidentiality while still keeping the harmonizing relations intact in the cloud. Our proposed scheme enables the data owner to delegate most of computation intensive tasks to cloud servers without disclosing data contents or user access privilege information

Cued-Click Point Graphical Password Using Circular Tolerance to Increase Password Space and Persuasive Features

AbstractGraphical password can be used as an alternative to text based (alphanumeric) password in which users click on images to set their passwords. Text based password uses username and password. So recalling of password is necessary which may be a difficult one. Images are generally easier to be remembered than text and in Graphical password; user can set images as their password. Therefore graphical password has been proposed by many researchers as an alternative to text based password Graphical passwords can be applied to workstation, web log-in applications, ATM machines, mobile devices etc. This paper presents implementation of Cued click point (CCP) graphical password which uses circular tolerance. Then it is found that CCP with circular tolerance is better as compared to CCP with rectangular tolerance

A protection scheme for microgrids using intelligent relays

Microgrids are emerging as an important part in modern power distribution systems due to significant development in distributed generation technologies. Microgrids operate with a high level of inverter interfaced distributed generation (IIDG) penetration such as fuel cells, solar cell, and battery storage etc. The problem of microgrid protection becomes challenging as the fault current varies widely depending upon the operating conditions such as grid-connected and islanded mode in presence of IIDG. Fast and accurate fault detection coupled with a clearing mechanism is required for a safe and secured micro-grid operation.This thesis presents a microgrid protection scheme using intelligent relays. The proposed intelligent relay is developed by combining a Wavelet Transform and Decision Tree models. The relay detects and classifies faults using local measurements irrespective of the operating mode of the micro-grid. The process starts by measuring and pre-processing the current signal at the relaying point using the Wavelet Transform. Time-frequency features such as change in energy, entropy and standard deviations are calculated using the wavelet coefficients. Cases representing various faulted and normal conditions are simulated to generate the complete data set containing the above mentioned features. This data set is used to train the decision tree for fault detection. The fault classification data set contains line current negative and zero sequence components along with the wavelet based features from current signals for the faulted cases only. The detection and classification decision trees are extensively tested on a large unseen data set and the test results indicate that the proposed relaying scheme can reliably protect the micro-grid against faulty conditions under wide variations in operating conditions. The performance is superior to that of instantaneous over current relays. The performance of the decision tree model is compared with another data mining model known as the random forest model.Les micro-réseaux pourraient jouer un rôle important dans les réseaux de distribution modernes en raison de développements importants dans les technologies de production décentralisée. Les micro-réseaux fonctionnent avec un haut niveau de pénétration de la production décentralisée interfacée avec des onduleurs, telle que les piles à combustible, les panneaux solaires, et le stockage de batteries. Le problème de la protection du micro-réseau devient difficile étant donné que le courant de défaut varie largement en fonction des conditions de fonctionnement, soit raccordé au réseau et en mode îlotage. Une détection de défaut rapide et précise, couplée avec un mécanisme d’élimination de défaut, est nécessaire pour une opération sûre et sécurisée du micro-réseau.Cette thèse présente un système de protection des micro-réseaux utilisant des relais intelligents. Le relais intelligent proposé est développé en combinant la transformée en ondelettes et le modèle d'arbre de décision. Le relais détecte et classe les défauts, en utilisant des mesures locales, quel que soit le mode d’opération du micro réseau. Le processus commence par la mesure et le prétraitement du signal de courant au point de connexion du relais en utilisant la transformée en ondelettes. Les caractéristiques temps-fréquence ainsi que les variations d'énergie, d'entropie et les écarts types sont calculés en utilisant les coefficients de la transformée en ondelettes. Les scénarios représentant diverses conditions avec et sans défaut sont simulées pour générer un ensemble de données les caractéristiques choisies. Cet ensemble est utilisé pour former le l’arbre de décision pour la détection de défaut. L'ensemble des données de classification de défaut contient le courant de ligne, inverse et homopolaire et les caractéristiques à base d'ondelettes des signaux de courant pour les cas de défauts. Les arbres de décision pour la détection et la classification de défauts sont testés sur un grand ensemble de données. Les résultats indiquent que l’approche proposée peut assurer la protection du micro-réseau dans des situations de défaut, avec des conditions d'exploitation très variables et qu’elle est supérieure aux performances des relais de surintensité instantanée. La performance du modèle de l’arbre de décision a été comparée avec un autre modèle d'exploration de données connu sous le nom de forêt d’arbres décisionnels

Histoplasmosis presenting as isolated cervical lymphadenopathy: A rare presentation

Histoplasmosis is an opportunistic fungal infection caused by inhaling the spores of a fungus called Histoplasma capsulatum. Disseminated histoplasmosis is the most common form associated with acquired immune deficiency syndrome (AIDS). Here, we report a case of histoplasmosis presenting as isolated cervical lymphadenopathy in a human immunodeficiency virus (HIV)-infected patient diagnosed by a less invasive method (fine-needle aspiration cytology) and confirmed by fungal culture of fine-needle aspiration material. Due to varied and nonspecific clinical manifestations of histoplasmosis, most of the infections are misdiagnosed or underreported. It has to be considered in differential diagnosis of cervical lymphadenopathy, particularly in immunocompromised patients so that patients can be treated medically at an early stage before dissemination occurs and unnecessary surgery can be avoided. Here, we present this case because of its rare presentation as isolated cervical lymphadenopathy and classical cytological picture