Thesis (M.A.)--University of London. / Bibliography: p. 150-153.

Thesis (M.A.)--University of London. / Bibliography: p. 150-153.

Web applications provide the basis for the use of the "World-Wide-Web", as people know itnowadays. These software solutions get programmed by a numerous amount of developersall over the world. For all this software, it is not possible to guarantee a 100 percent security.Therefore, it is desirable that every application should get evaluated using penetration tests.Anewformof security testing platforms is getting provided by bug bounty programs, whichencourage the community to help searching for security breaches. This work introduces thecurrently leading portal for bug bounties, called Bugcrowd Inc. In addition, web applications,which were part of the program, got tested in order to evaluate their security level.A comparison is made with given statistics by leading penetration testing companies, showingthe average web application security level. The submission process, to send informationabout vulnerabilities, is getting evaluated. The average time it takes, to receive an answer regardinga submission is getting reviewed. In the end, the findings get retested, to evaluate, ifthe bug bounty program is a useful opportunity to increase security and if website operatorstake submissions serious by patching the software flaws.

Vegetation community patterns and processes are indicators and integrators of climate. Recently, scientists have shown that climate change is most pronounced in circumpolar regions. Arctic ecosystems have traditionally been sequestering carbon and accumulating large carbon stores. However, given enhanced warming in the Arctic, the potential exists for intensified global climate change if these ecosystems transition from sinks to sources of atmospheric CO2. In the Mid and High Arctic, ecosystems exhibit extreme levels of spatial heterogeneity, particularly at landscape scales. High spatial-resolution (e.g., 4m) remote sensing data capture heterogeneous vegetation patterns of the Arctic landscape and have the potential to model ecosystem biophysical properties and CO2 fluxes. The following conditions are required to model arctic ecosystem processes: (i) unique spectral signatures that correspond to variations in the landscape pattern; (ii) models that transform remote sensing data into derivative values pertaining to the landscape; and (iii) field measures of the variables to calibrate and validate the models. First, this research creates an ecosystem classification scheme through ordination, clustering, and spectral-separability of ground cover data to generate ecologically meaningful and spectrally distinct image classifications. Classifications had overall accuracies between 69% - 79% and Kappa values of 0.54 - 0.69. Secondly, biophysical variable models of percent vegetation cover, aboveground biomass, and soil moisture are calibrated and validated using a k-fold cross-validation linear bivariate regression methodology. Percent vegetation cover and percent soil moisture produce the strongest and most consistent results (r2 ≥ 0.84 and 0.73) across both study sites. Finally, in situ CO2 exchange rate data, an NDVI model for each component flux, which explains between 42% and 95% of the variation at each site, is generated. Analysis of coincidence indicates that a single model for each component flux can be applied, independent of site. This research begins to fill a gap in the application of high spatial-resolution remote sensing data for modelling Arctic ecosystem biophysical variables and carbon dioxide exchange, particularly in the Canadian Arctic. The results of this research also indicate high levels of functional convergence in ecosystem-level structure and function within Arctic landscapes. / Thesis (Ph.D, Geography) -- Queen's University, 2013-01-03 22:24:20.157

Bug bounties are an increasingly popular way of performing penetration tests of web applications. User statistics of bug bounty platforms show that a lot of hackers struggle to find bugs. This report explores a way of using Markov decision processes and reinforcement learning to help hackers find vulnerabilities in web applications by building a tool that suggests attack surfaces to examine and vulnerability reports to read to get the relevant knowledge. The attack surfaces, vulnerabilities and reports are all derived from a taxonomy of web vulnerabilities created in a collaborating project. A Markov decision process (MDP) was defined, this MDP includes the environment, different states of knowledge and actions that can take a user from one state of knowledge to another. To be able to suggest the best possible next action to perform, the MDP uses a policy that describes the value of entering each state. Each state is given a value that is called Q-value. This value indicates how close that state is to another state where a vulnerability has been found. This means that a state has a high Q-value if the knowledge gives a user a high probability of finding a vulnerability and vice versa. This policy was created using a reinforcement learning algorithm called Q-learning. The tool was implemented as a web application using Java Spring Boot and ReactJS. The resulting tool is best suited for new hackers in the learning process. The current version is trained on the indexed reports of the vulnerability taxonomy but future versions should be trained on user behaviour collected from the tool. / Bug bounties är ett alltmer populärt sätt att utföra penetrationstester av webbapplikationer. Användarstatistik från bug bounty-plattformar visar att många hackare har svårt att hitta buggar. Denna rapport undersöker ett sätt att använda Markov-beslutsprocesser och förstärkt inlärning för att hjälpa hackare att hitta sårbarheter i webbapplikationer genom att bygga ett verktyg som föreslår attackytor att undersöka och sårbarhetsrapporter att läsa för att tillgodogöra sig rätt kunskaper. Attackytor, sårbarheter och rapporter är alla hämtade från en taxonomi över webbsårbarheter skapad i ett samarbetande projekt. En Markovbeslutsprocess (MDP) definierades. Denna MDP inkluderar miljön, olika kunskapstillstånd och handlingar som kan ta användaren från ett kunskapstillstånd till ett annat. För kunna föreslå nästa handling på bästa möjliga sätt använder MDPn en policy som beskriver värdet av att träda in i alla de olika tillstånden. Alla tillstånd ges ett värde som kallas Q-värde. Detta värde indikerar hur nära ett tillstånd har till ett annat tillstånd där en sårbarhet har hittats. Detta betyder att ett tillstånd har ett högt Q-värde om kunskapen ger användaren en hög sannolikhet att hitta en sårbarhet och vice versa. Policyn skapades med hjälp av en typ av förstärkt inlärningsalgoritm kallad Q-inlärning. Verktyget implementerades som en webbapplikation med hjälp av Java Spring Boot och ReactJS. Det resulterande verktyget är bäst lämpat för nya hackare i inlärningsstadiet. Den nuvarande versionen är tränad på indexerade rapporter från sårbarhetstaxonomin men framtida versioner bör tränas på användarbeteende insamlat från verktyget.

Data derived largely from ecclesiastical (mostly churchwardens') accounts, foxhunting statistics, local scientific society records and 19th and 20th century literature sources from a wide range of published material, have provided detailed evidence of the status and changes in distribution over the past four centuries in Yorkshire for fox (Vulpes vulpes), badger (Meles meles), otter (Lutra lutra), pine marten (Martes martes), stoat (Mustela erminea), weasel (M. nivalis), polecat (M. putorius), American mink (M. vison), wildcat (Felis silvestris) and domestic cat (Felis catus). In the case of the domestic cat, questionnaire surveys quantified population sizes and predatory activity in rural, suburban and urban situations. Evidence of the former distribution of all the carnivores studied provides a credible historical basis for biodiversity action planning and the substantial archived database and bibliography provide further research opportunities.

Data derived largely from ecclesiastical (mostly churchwardens¿) accounts, foxhunting statistics, local scientific society records and 19th and 20th century literature sources from a wide range of published material, have provided detailed evidence of the status and changes in distribution over the past four centuries in Yorkshire for fox (Vulpes vulpes), badger (Meles meles), otter (Lutra lutra), pine marten (Martes martes), stoat (Mustela erminea), weasel (M. nivalis), polecat (M. putorius), American mink (M. vison), wildcat (Felis silvestris) and domestic cat (Felis catus). In the case of the domestic cat, questionnaire surveys quantified population sizes and predatory activity in rural, suburban and urban situations. Evidence of the former distribution of all the carnivores studied provides a credible historical basis for biodiversity action planning and the substantial archived database and bibliography provide further research opportunities.

Crowdfunding challenges century long boundaries between the public, the industry andinnovation. In that respect the phenomenon holds the potential to decentralize and democratizethe way ventures are financed and realized. Crowdfunding has seen a lot of exitingdevelopments during the last few years, partly because of new crowdfunding platformsemerging on the internet, and partly because of new ground-breaking technology being used forfunding purposes. Meanwhile research has not quite catched up with the recent developments ofdifferent models for crowdfunding. This study’s aim is therefor to give an comprehensiveoverview of the different models of crowdfunding that are being utilized by crowdfundingplatforms on the internet today. A deductive content analysis has been made of 67 currentcrowdfunding platforms. The platforms have been analysed in order to determine what model ofcrowdfunding they utilize. The result has, apart from partly confirming prior studies, alsoproduced new exiting findings on what mechanisms constitute some of the crowdfundingmodels we see today. A new taxonomy of crowdfunding models is discussed and proposed. Theconclusion is that the need for a updated taxonomy, like the one this study provides, was wellneeded in order to understand the field. One important finding is that blockchain technology hasproduced a new form of crowdfunding through cryptocurrency: Initial coin offering. Thatparticular area will likely develop and continue to decentralize and democratise the economicalhuman interaction when it comes to financing.

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