Modern IT companies manage security of their customers'networks following particular models, processes and procedures. In this thesis are presented the most important and widespread guidelines on Security Incident Response Plans as well as the implementation of a software for an IT danish company called NNIT. In particular, this software aims to improve NNIT's Security Incident Management Process generating automatic reports of vulnerabilities found in NNIT clients networks. Enhancing this process reducing its execution time is directly translated into a proactive response where vulnerabilities are tackled and patched before an attacker could exploit them. The software developed and described in this thesis is called VRC and thanks to a particular algorithm analyzes the database of vulnerabilities found by the vulnerability scanner and produces customizable reports. In the reports, the list of vulnerabilities is ordered by severity and number of machines a ected in order to present the most urgent vulnerabilities that should be xed. Finally, an evaluation of the VRC performance and usefulness is also included.

Ett ständigt växande antal människor världen över använder sig numera av biometriska system istället för lösenord när de ska hålla sina tillgångar säkra. Det finns flera anledningar till att biometriska system har blivit ett så stort fenomen idag, bland annat på grund av dess höga grad av säkerhet. Eftersom varje människa har unika biometriska attribut leder detta till ett system som är oerhört säkert. Denna studie syftar till att utföra en systematisk litteraturstudie, där vi avgränsar oss till att undersöka hur man kan mäta säkerhetsaspekter hos två av dagens mest tillämpade biometriska system, nämligen fingerprint scanner och face recognition. Resultaten av denna litteraturstudie visar bland annat att båda systemen är mycket säkra och att det inte enbart finns ett sätt att mäta säkerheten hos de två ovannämnda biometriska systemen utan flera. / Biometric systems are becoming increasingly popular around the world and it has become more common among people to use biometric systems instead of passwords when they are to keep their assets safe. There are many reasons why biometric systems have become such a phenomenon today, among other things because of its high degree of security. Because no human has the same biometric attributes as the other this leads to a very safe system. In this study, two different biometric systems, namely fingerprint scanners and face recognition, and their security aspects are addressed. These two systems are two of the most widely used biometric systems today. A systematic literature study has been carried out aiming at examining how to measure the safety of a biometric system according to previous research studies and which of the two selected biometric solutions showing the greatest safety with the found test methods. Based on the answers we received from the literature study, we concluded that both systems were very safe and moreover, we also found that there is not only one way to measure the safety of biometric systems but several different.

At the start of millennia harvesters in forestry have gained popularity for their productive and accurate timber processing. However the accuracy of harvester measurement and overall reliability is often in question and hot topic in forest technology as it is directly responsible for economical profits of the machine. As harvesters timber measurement is affected by various factors both internally and externally the influence level of these factors needed practical approach. In the view of this aim of this analysis was directed to discover the factors and characteristics that are essential to harvesters timber measurement. Target of this analysis is divided in to practical field measurements and harvester simulator experiments. In the field measurements small number of trees were measured with various measurement methods which are used in the professional field of forestry. For harvester simulator experiments number parameters in the computer system were chosen that are linked to timber measurement and modified based on their individual characteristics. Results for both field measurements and harvester simulator experiments were processed and analyzed to see which had the most essential effect on the measurement accuracy and reliability and what other discoveries it might produce. Field measurement data analysis discovered that 3D scanner and image analysis produced the most accurate measurement results and harvester underestimated the tree volume data in most of the assortments. Other notion was that image analysis over measured some tree stem bases that had over expanded butt part. Simulator parameter experimentation led to the discovery that price type and diameter base curve had the most influence on the timber volume estimation while other experimented parameters produced less data change after their modification. Also some parameter were restricted by other parameters from producing any possible discoveries.

京都大学 / 0048 / 新制・課程博士 / 博士(医学) / 甲第20612号 / 医博第4261号 / 新制||医||1023(附属図書館) / 京都大学大学院医学研究科医学専攻 / (主査)教授 増永 慎一郎, 教授 溝脇 尚志, 教授 小泉 昭夫 / 学位規則第4条第1項該当 / Doctor of Medical Science / Kyoto University / DFAM

The development of smart ID cards necessitates the development of secure methods for verifying the authenticity of these cards by organizations, businesses, and government authorities. This motivated the development of such a scanner capable of reading several ID cards from various countries. 365id presented its solution in 2016 by introducing a unique scanner that can verify the authenticity of ID cards. The verification process works by capturing three images using the scanner's three distinct techniques to validate the ID cards' hidden features. After many years of the company's success and the services it provides, including the 365id scanner, it is now the time to take the scanner a step further and improve its services. Thus, this project was founded by the 365id company to research and generate various suggestions for improving the quality of the scanner's photo environment. Either by modifying the way light is reflected inside the scanner or by modifying the parameters that control the camera's operation and investigating the possibility of replacing the camera with a better alternative. This is to increase the image quality and accuracy of the verification procedure. The results proved that the desired effect could be achieved at the lowest costs by adjusting the camera settings and adding new materials to reduce and isolate the light's reflection inside the scanner. In comparison, the results proved that it is not feasible to replace the camera at present. Nevertheless, it is an option that may be available soon.

Today, new web applications are made every single day with increasingly more sensitive data to manage. To ensure that no security vulnerabilities such as data leakage in web applications exist, developers are using tools such as a web vulnerability scanner. This type of tool can detect vulnerabilities by automatically finding input fields where data can be injected and performing different attacks on these fields. One of the most common web vulnerability scanners is OWASP ZAP. Web vulnerability scanners were first developed during a time when traditional multi-page applications were prominent. Nowadays, when modern single-page applications have become the de facto standard, new challenges for web vulnerability scanners have arisen. These problems include identifying dynamically updated web pages. This thesis aims to evaluate the techniques used by OWASP ZAP and several other web vulnerability scanners for identifying two of the most common vulnerabilities, SQL injections and cross-site scripting. This issue is approached by testing the selected web vulnerability scanners on deliberately vulnerable web applications, to assess the performance and techniques used, and to determine if the performance of OWASP ZAP could be improved. If an identified technique in another web vulnerability scanner performed better than the counterpart in OWASP ZAP, it will be implemented in OWASP ZAP and evaluated. From the tests performed, it could be concluded that the performance of OWASP ZAP was lacking in the search for input fields, where a depth-first search algorithm was used. The breadth-first search algorithm used by other scanners was shown to be more effective in specific cases and was therefore implemented in OWASP ZAP. The result shows that the use case for the two algorithms differs between web applications and by using both of the algorithms to find vulnerabilities, better performance is achieved.

Structure from motion is a novel approach to generate 3D models of objects and structures. The dataset simply consists of a series of images of an object taken from different positions. The ease of the data acquisition and the wide array of available algorithms makes the technique easily accessible. The structure from motion method identifies features in all the images from the dataset, like edges with gradients in multiple directions, and tries to match these features between all the images and then computing the relative motion that the camera was subject to between any pair of images. It builds a 3D model with the correlated features. It then creates a 3D point cloud with colour information of the scanned object. There are different implementations of the structure from motion method that use different approaches to solve the feature-correlation problem between the images from the data set, different methods for detecting the features and different alternatives for sparse reconstruction and dense reconstruction as well. These differences influence variations in the final output across distinct algorithms. This thesis benchmarked these different algorithms in accuracy and processing time. For this purpose, a terrestrial 3D laser scanner was used to scan structures and buildings to generate a ground truth reference to which the structure from motion algorithms were compared. Then a video feed from a drone with a built-in camera was captured when flying around the structure or building to generate the input for the structure from motion algorithms. Different structures are considered taking into account how rich or poor in features they are, since this impacts the result of the structure from motion algorithms. The structure from motion algorithms generated 3D point clouds, which then are analysed with a tool like CloudCompare to benchmark how similar it is to the laser scanner generated data, and the runtime was recorded for comparing it across all algorithms. Subjective analysis has also been made, such as how easy to use the algorithm is and how complete the produced model looks in comparison to the others. In the comparison it was found that there is no absolute best algorithm, since every algorithm highlights in different aspects. There are algorithms that are able to generate a model very fast, managing to scale the execution time linearly in function of the size of their input, but at the expense of accuracy. There are also algorithms that take a long time for dense reconstruction, but generate almost complete models even in the presence of featureless surfaces, like COLMAP modified PatchMacht algorithm. The structure from motion methods are able to generate models with an accuracy of up to \unit[3]{cm} when scanning a simple building, where Visual Structure from Motion and Open Multi-View Environment ranked among the most accurate. It is worth highlighting that the error in accuracy grows as the complexity of the scene increases. Finally, it was found that the structure from motion method cannot reconstruct correctly structures with reflective surfaces, as well as repetitive patterns when the images are taken from mid to close range, as the produced errors can be as high as \unit[1]{m} on a large structure.

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