Vikten av säkra nätverk

The purpose of this thesis is to show how to use vulnerability testing to identify and search for security flaws in networks of computers. The goal is partly to give a casual description of different types of methods of vulnerability testing and partly to present the method and results from a vulnerability test. A document containing the results of the vulnerability test will be handed over and a solution to the found high risk vulnerabilities. The goal is also to carry out and present this work as a form of a scholarly work.The problem was to show how to perform vulnerability tests and identify vulnerabilities in the organization's network and systems. Programs would be run under controlled circumstances in a way that they did not burden the network. Vulnerability tests were conducted sequentially, when data from the survey was needed to continue the scan.A survey of the network was done and data in the form of operating system, among other things, were collected in the tables. A number of systems were selected from the tables and were scanned with Nessus. The result was a table across the network and a table of found vulnerabilities. The table of vulnerabilities has helped the organization to prevent these vulnerabilities by updating the affected computers. Also a wireless network with WEP encryption, which is insecure, has been detected and decrypted.

Passive MVC och MVVM designmönster i Android : En jämförelse av kodkomplexitet mellan Passive MVC och MVVM

Det mobila operativsystemet Android är idag ett ganska dominerande operativsystem på den mobila marknaden dels på grund av sin öppenhet men också på grund av att tillgängligheten är stor i och med både billiga och dyra telefoner finns att tillgå. Men idag har Android inget fördefinierat designmönster vilket leder till att varje utvecklare får bestämma själv vad som ska användas, vilket ibland kan leda till onödigt komplex kod i applikationerna som sen blir svårtestad och svårhanterlig. Detta arbete ämnar jämföra två designmönster, Passive Model View Controller (PMVC) och Model View View-Model (MVVM), för att se vilket designmönster som blir minst komplext med hjälp av att räkna fram mätvärden med hjälp av Cyclomatic Complexity Number (CCN). Studien är gjord utifrån arbetssättet Design & Creation och ämnar bidra med: kunskap om vilket mönster man bör välja, samt om CCN kan peka ut vilka delar i en applikation som kommer att ta mer eller mindre lång tid att testa. Under studiens gång tog vi även fram skillnader på om man anväder sig av den så kallade Single Responsibilyt Principle (SRP) eller inte. Detta för att se om separerade vyer gör någon skillnad i applikationernas komplexitet. I slutändan så visar studien på att komplexiteten i små applikationer är väldigt likvärdig, men att man även på små applikationer kan se skillnad på hur komplex koden är men också att kodkomplexitet på metodnivå kan ge riktlinjer för testfall.

A Computer Vision Framework For Finger-Tapping Evaluation In Parkinson's Disease

Objective: To define and evaluate a Computer-Vision (CV) method for scoring Paced Finger-Tapping (PFT) in Parkinson's disease (PD) using quantitative motion analysis of index-fingers and to compare the obtained scores to the UPDRS (Unified Parkinson's Disease Rating Scale) finger-taps (FT). Background: The naked-eye evaluation of PFT in clinical practice results in coarse resolution to determine PD status. Besides, sensor mechanisms for PFT evaluation may cause patients discomfort. In order to avoid cost and effort of applying wearable sensors, a CV system for non-invasive PFT evaluation is introduced. Methods: A database of 221 PFT videos from 6 PD patients was processed. The subjects were instructed to position their hands above their shoulders besides the face and tap the index-finger against the thumb consistently with speed. They were facing towards a pivoted camera during recording. The videos were rated by two clinicians between symptom levels 0-to-3 using UPDRS-FT. The CV method incorporates a motion analyzer and a face detector. The method detects the face of testee in each video-frame. The frame is split into two images from face-rectangle center. Two regions of interest are located in each image to detect index-finger motion of left and right hands respectively. The tracking of opening and closing phases of dominant hand index-finger produces a tapping time-series. This time-series is normalized by the face height. The normalization calibrates the amplitude in tapping signal which is affected by the varying distance between camera and subject (farther the camera, lesser the amplitude). A total of 15 features were classified using K-nearest neighbor (KNN) classifier to characterize the symptoms levels in UPDRS-FT. The target ratings provided by the raters were averaged. Results: A 10-fold cross validation in KNN classified 221 videos between 3 symptom levels with 75% accuracy. An area under the receiver operating characteristic curves of 82.6% supports feasibility of the obtained features to replicate clinical assessments. Conclusions: The system is able to track index-finger motion to estimate tapping symptoms in PD. It has certain advantages compared to other technologies (e.g. magnetic sensors, accelerometers etc.) for PFT evaluation to improve and automate the ratings