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1	Evaluating the effectiveness of free rule sets for Snort / En utvärdering av effektiviteten av gratis regeluppsättningar för Snort Granberg, Niklas January 2022 (has links) As more of the modern world is connected to the Internet, threats can reach further than ever before. Attacks happen all the time and many have serious consequences that disrupts the daily processes of people and companies, possibly causing lasting damage. To fight back, defensive tools are used to find and counter attacks. One of these tools is Snort. Snort finds malicious data packets and warns the user and counters the found attack. Snort relies on a list of signatures of different attacks, called a rule set, to know what is malicious. Many rule sets are available as paid subscriptions, but there are free alternatives. But how well can Snort defend a network using these free rule sets? By designing a network for experimentation and populating it with realistic background traffic, a group of rule sets are evaluated using a set of common attacks and tools. The performance hit when defending in a high speed, high bandwidth environment is evaluated as well. The results favour the Emerging Threats rule set. As for performance, Snort could not handle the most extreme amounts of traffic, with the rate of dropped packets making security dubious, but that occurred at the absolute peak of what consumer hardware can provide. Snort rule sets Snort rule sets information security network security Computer Sciences Datavetenskap (datalogi)
2	A Unified Model of Rule-Set Learning and Selection Pierson J. Fleischer (5929673) 16 January 2019 (has links) A new, biologically plausible model of task-set learning that reproduces effects from both rule-learning experiments and task-switching experiments.<br> learning model rule sets basal ganglia prefrontal cortex presynaptic inhibition task set switching
3	Automating Geographic Object-Based Image Analysis and Assessing the Methods Transferability : A Case Study Using High Resolution Geografiska SverigedataTM Orthophotos Hast, Isak, Mehari, Asmelash January 2016 (has links) Geographic object-based image analysis (GEOBIA) is an innovative image classification technique that treats spatial features in an image as objects, rather than as pixels; thus resembling closer to that of human perception of the geographic space. However, the process of a GEOBIA application allows for multiple interpretations. Particularly sensitive parts of the process include image segmentation and training data selection. The multiresolution segmentation algorithm (MSA) is commonly applied. The performance of segmentation depends primarily on the algorithms scale parameter, since scale controls the size of image objects produced. The fact that the scale parameter is unit less makes it a challenge to select a suitable one; thus, leaving the analyst to a method of trial and error. This can lead to a possible bias. Additionally, part from the segmentation, training area selection usually means that the data has to be manually collected. This is not only time consuming but also prone to subjectivity. In order to overcome these challenges, we tested a GEOBIA scheme that involved automatic methods of MSA scale parameterisation and training area selection which enabled us to more objectively classify images. Three study areas within Sweden were selected. The data used was high resolution Geografiska Sverigedata (GSD) orthophotos from the Swedish mapping agency, Lantmäteriet. We objectively found scale for each classification using a previously published technique embedded as a tool in eCognition software. Based on the orthophoto inputs, the tool calculated local variance and rate of change at different scales. These figures helped us to determine scale value for the MSA segmentation. Moreover, we developed in this study a novel method for automatic training area selection. The method is based on thresholded feature statistics layers computed from the orthophoto band derivatives. Thresholds were detected by Otsu’s single and multilevel algorithms. The layers were run through a filtering process which left only those fit for use in the classification process. We also tested the transferability of classification rule-sets for two of the study areas. This test helped us to investigate the degree to which automation can be realised. In this study we have made progress toward a more objective way of object-based image classification, realised by automating the scheme. Particularly noteworthy is the algorithm for automatic training area selection proposed, which compared to manual selection restricts human intervention to a minimum. Results of the classification show overall well delineated classes, in particular, the border between open area and forest contributed by the elevation data. On the other hand, there still persists some challenges regarding separating between deciduous and coniferous forest. Furthermore, although water was accurately classified in most instances, in one of the study areas, the water class showed contradictory results between its thematic and positional accuracy; hence stressing the importance of assessing the result based on more than the thematic accuracy. From the transferability test we noted the importance of considering the spatial/spectral characteristics of an area before transferring of rule-sets as these factors are a key to determine whether a transfer is possible. automatic training area selection scale parameterisation multiresolution segmentation classification rule-sets positional accuracy Other Civil Engineering Annan samhällsbyggnadsteknik
4	On Rules and Methods: Neural Representations of Complex Rule Sets and Related Methodological Contributions Görgen, Kai 20 November 2019 (has links) Wo und wie werden komplexe Regelsätze im Gehirn repräsentiert? Drei empirische Studien dieser Doktorarbeit untersuchen dies experimentell. Eine weitere methodische Studie liefert Beiträge zur Weiterentwicklung der genutzten empirischen Methode. Die empirischen Studien nutzen multivariate Musteranalyse (MVPA) funktioneller Magnetresonanzdaten (fMRT) gesunder Probanden. Die Fragestellungen der methodischen Studie wurden durch die empirischen Arbeiten inspiriert. Wirkung und Anwendungsbreite der entwickelten Methode gehen jedoch über die Anwendung in den empirischen Studien dieser Arbeit hinaus. Die empirischen Studien bearbeiten Fragen wie: Wo werden Hinweisreize und Regeln repräsentiert, und sind deren Repräsentationen voneinander unabhängig? Wo werden Regeln repräsentiert, die aus mehreren Einzelregeln bestehen, und sind Repräsentationen der zusammengesetzten Regeln Kombinationen der Repräsentationen der Einzelregeln? Wo sind Regeln verschiedener Hierarchieebenen repräsentiert, und gibt es einen hierarchieabhängigen Gradienten im ventrolateralen präfrontalen Kortex (VLPFK)? Wo wird die Reihenfolge der Regelausführung repräsentiert? Alle empirischen Studien verwenden informationsbasiertes funktionales Mapping ("Searchlight"-Ansatz), zur hirnweiten und räumlich Lokalisierung von Repräsentationen verschiedener Elemente komplexer Regelsätze. Kernergebnisse der Arbeit beinhalten: Kompositionalität neuronaler Regelrepräsentationen im VLPFK; keine Evidenz für Regelreihenfolgenrepräsentation im VLPFK, welches gegen VLPFK als generelle Task-Set-Kontrollregion spricht; kein Hinweis auf einen hierarchieabhängigen Gradienten im VLPFK. Die komplementierende methodische Studie präsentiert "The Same Analysis Approach (SAA)", ein Ansatz zur Erkennung und Behebung experimentspezifischer Fehler, besonders solcher, die aus Design–Analyse–Interaktionen entstehen. SAA ist für relevant MVPA, aber auch für anderen Bereichen innerhalb und außerhalb der Neurowissenschaften. / Where and how does the brain represent complex rule sets? This thesis presents a series of three empirical studies that decompose representations of complex rule sets to directly address this question. An additional methodological study investigates the employed analysis method and the experimental design. The empirical studies employ multivariate pattern analysis (MVPA) of functional magnetic resonance imaging (fMRI) data from healthy human participants. The methodological study has been inspired by the empirical work. Its impact and application range, however, extend well beyond the empirical studies of this thesis. Questions of the empirical studies (Studies 1-3) include: Where are cues and rules represented, and are these represented independently? Where are compound rules (rules consisting of multiple rules) represented, and are these composed from their single rule representations? Where are rules from different hierarchical levels represented, and is there a hierarchy-dependent functional gradient along ventro-lateral prefrontal cortex (VLPFC)? Where is the order of rule-execution represented, and is it represented as a separate higher-level rule? All empirical studies employ information-based functional mapping ("searchlight" approach) to localise representations of rule set features brain-wide and spatially unbiased. Key findings include: compositional coding of compound rules in VLPFC; no order information in VLPFC, suggesting VLPFC is not a general controller for task set; evidence against the hypothesis of a hierarchy-dependent functional gradient along VLPFC. The methodological study (Study 4) introduces "The Same Analysis Approach (SAA)". SAA allows to detect, avoid, and eliminate confounds and other errors in experimental design and analysis, especially mistakes caused by malicious experiment-specific design-analysis interactions. SAA is relevant for MVPA, but can also be applied in other fields, both within and outside of neuroscience. fMRT funktionale Magnetresonanztomographie SAA multivariate Musteranalyse Kontrollfunktionen Dekodierung Frontallappen Neuronaler Kode Task Set Komplexe Regelsätze Kognitive Kontrolle Regelrepräsentation VLPFK ventro-lateraler Präfrontalkortex Kognitive Neuropsychologie Experimentaldesign Störfaktoren Kreuzvalidierung unterzufällige Accuracies schlechter-als-Zufall Klassifikation Unittests below-chance accuracies fMRI functional magnetic resonance imaging SAA MVPA multivariate pattern analysis control functions decoding frontal lobe neural code task set complex rule sets cognitive control rule representations VLPFC ventrolateral prefrontal cortex cognitive neuropsychology experimental design design of experiment confounds cross validation worse-than-chance classification unit testing 153 Kognitive Prozesse, Intelligenz 150 Psychologie 570 Biowissenschaften; Biologie WW 4200 CP 4000 CZ 1000 CZ 1320 ddc:153 ddc:150 ddc:570

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