During the last decade, there has been an increase in the number of automated programs (bots) that perform tasks such as harvesting information or making posts on social media. CAPTCHA was developed as a defense against bots, but several common CAPTCHAs have usability issues and are difficult for users to solve. This project aims to determine if a non-visible user input-based CAPTCHA can help solve this problem. The CAPTCHA looks for patterns in the user input, that is, signs that the input is controlled by scripted logic. The CAPTCHA is evaluated by looking at how capable it is at identifying patterns, human mouse movements and bot-controlled mouse movements. Additionally, it is investigated if there exists a data sequence size at which the pattern recognition algorithm can most successfully detect patterns and avoid false negatives. The results showed that interval sizes 40-50 provide the best results. Using these sizes, the pattern recognition algorithm was able to fulfill the commonly accepted rates of at least a 99 % success rate and at most a 10 % false negative rate. This shows that the CAPTCHA is robust under the circumstances investigated.

The semestral thesis deals with the analysis of the modern open-source NIDPS tools for monitoring and analyzing the network traffic. The work rates these instruments in terms of their network location and functions. Also refers about more detailed analysis of detecting and alerting mechanisms. Further analyzes the possibilities of detection of anomalies, especially in terms of statistical analysis and shows the basics of other approaches, such as approaches based on data mining and machine learning. The last section presents specific open-source tools, deals with comparison of their activities and the proposal allowing monitoring and traffic analysis, classification, detection of anomalies and (D)DoS attacks.

Orientador: Kester Carrara / Resumo: Ultrapassando qualquer expectativa inicial de servir exclusivamente como um meio de comunicação interpessoal, as mídias sociais tornaram-se complexas fontes de informações que exercem grande influência e poder de persuasão no cotidiano de seus usuários. Essa ferramenta é tão adaptada ao modo de vida contemporâneo que viabiliza a imediaticidade do reforço e seus efeitos e promove a manutenção de laços afetivos e sociais através do uso de seus dispositivos. Nesse contexto, este trabalho tem como principal objetivo identificar o fenômeno da polarização de opiniões utilizando uma abordagem multirreferenciada quanto à revisão da literatura, além de proceder um exame conceitual do tema a partir dos fundamentos da Análise do Comportamento, buscando descrever como os temas são percebidos através das respostas dos participantes da pesquisa. O estudo teve a participação de 53 estudantes do curso de Psicologia em duas cidades do interior do estado de São Paulo, que se posicionaram frente a temas polarizantes. Na bibliografia pesquisada constatou-se a grande capilaridade das mídias sociais e a influência de variáveis, como Fake News, Filtro Bolha, Bots e Pensamento Binário. Através dos pressupostos da Teoria das Molduras Relacionais (de Rose, 2016) verificou-se que funções atribuídas por treino direto a um estímulo passam a ser compartilhadas pelos estímulos coordenados a ele de modo que, sem necessidade de qualquer treino direto, as relações de coordenação (equivalência) podem reproduzi... (Resumo completo, clicar acesso eletrônico abaixo) / Abstract: Exceeding any initial expectation of serving exclusively as a means of interpersonal communication, social media have become complex sources of information that exert great influence and power of persuasion in the daily lives of its users. This tool is so adapted to the contemporary way of life that it makes the reinforcement immediate and its effects viable and promotes the maintenance of affective and social ties through the use of its devices. In this context, this work has as main objective to identify the phenomenon of polarization of opinions using a multi-referenced approach regarding the literature review, in addition to proceeding to a conceptual examination of the theme from the fundamentals of Behavior Analysis, seeking to describe how the themes are perceived through the responses of the research participants. The study had the participation of 53 students of the Psychology course in two cities in the interior of the state of São Paulo, who took a stand against polarizing themes. The researched bibliography showed the great capillarity of social media and the influence of variables, such as Fake News, Bubble Filter, Bots and Binary Thought. Through the assumptions of the Theory of Relational Frames (de Rose, 2016) it was found that functions attributed by direct training to a stimulus are shared by stimuli coordinated to it so that, without the need for any direct training, coordination relationships (equivalence) can reproduce the effects of respondent conditioni... (Complete abstract click electronic access below) / Mestre

Environs 70 millions de personnes seront atteintes par la maladie d’Alzheimer (MA) en 2030 et les coûts engendrés par la prise en charge des patients affectés par cette pathologie excédera quatre fois les coûts des maladies cancéreuses. Dans le but lutter contre cette pathologie multifactorielle, des stratégies thérapeutiques combinatoires ainsi que le développement de MTDL « Multi Target Directed Ligands » suscitent un grand intérêt. Dans ce contexte, l’association d’inhibiteurs de l’acétylcholinestérase (AChE) avec les agonistes des récepteurs sérotoninergiques de type 4 (5-HT4) a montré des effets bénéfiques sur la mémoire et la protection du cerveau chez les rongeurs. Après avoir démontré l’avantage de l’association de la galantamine, un inhibiteur de l’AChE avec le RS 67333, un agoniste des récepteurs 5-HT4 dans un modèle de déficit mnésique induit par la scopolamine sur les performances de mémoires de travail et de référence, nous avons étudié le donecopride, un MTDL récemment développé, à la fois inhibiteur de l’AChE et agoniste partiel des récepteurs 5-HT4. Chez les souris sauvages, une administration unique de donecopride augmente la sécrétion du neuropeptide protecteur sAPPα et a démontré des effets anti-amnésiants et pro-cognitifs. Dans un modèle amyloïdogénique de la MA (5xFAD), six mois de traitement chronique par le donecopride ont amélioré les performances de mémoire de travail à l’âge de 9 mois, sans modifier la densité des plaques amyloïdes au niveau cérébral. Par ailleurs, nous avons également étudié les effets d’un autre composé MTDL « 7m » qui est à la fois agoniste des récepteurs 5-HT4 et antagoniste des récepteurs 5-HT6, qui a montré des effets anti-amnésiants chez les souris sauvages lorsque le déficit mnésique est induit par administration de scopolamine. Ainsi, la modulation chronique et simultanée de différentes cibles centrales d’intérêt représente un potentiel thérapeutique important dans le cadre du traitement de la MA. / In 2030, the number of people affected by Alzheimer’s disease (AD) is expected to reach almost 70 million, and the cost of the disease would be over four folds cost of cancer diseases care. To face the multifactorial disease combining drugs arouse a big interest and the concept of MTDL “Multi Target Directed Ligands” has emerged. Thus, combining acetylcholinesterase (AChE) inhibitors with serotonergic receptor type 4 (5-HT4) showed beneficial effects on memory and brain protection in rodents. First, we showed beneficial effects of galatamine, an AChE inhibitor while combined to RS 67333, a 5-HT4 receptors partial agonist, on working and reference memory performances in a pharmacological model with scopolamine-induced amnesia. Then, we assessed effects of donecopride, the AChE inhibitor and partial agonist of 5-HT4 receptors. Donecopride, which increases sAPPα release in cell culture and C57BL/6 mice, showed anti-amnesiant and pro-cognitive effects in NMRI mice. In 5xFAD mice, an amyloidogenic mice model of AD, six months of chronic treatment of donecopride improves working memory performances in 9 months old 5xFAD mice, but does not affect spatial learning performances neither flexibility. Moreover, donecopride inhibits AChE and does not affect 5-HT4 receptor expression level neither amyloid plaque density in the brain. In the other hand, we also showed that the MTDL, which modulate 5-HT4 and 5-HT6 receptors, recovers working memory performances in NMRI mice where scopolamine induced memory deficit. Thus, hitting multiple targets, particularly while administered early and chronically, accounts for a hopeful strategy to better face AD

京都大学 / 0048 / 新制・課程博士 / 博士(工学) / 甲第18594号 / 工博第3955号 / 新制||工||1608(附属図書館) / 31494 / 京都大学大学院工学研究科合成・生物化学専攻 / (主査)教授 森 泰生, 教授 梅田 眞郷, 教授 濵地 格 / 学位規則第4条第1項該当 / Doctor of Philosophy (Engineering) / Kyoto University / DGAM

京都大学 / 新制・課程博士 / 博士(情報学) / 甲第24732号 / 情博第820号 / 新制||情||138(附属図書館) / 京都大学大学院情報学研究科社会情報学専攻 / (主査)教授 緒方 広明, 教授 伊藤 孝行, 准教授 近藤 一晃 / 学位規則第4条第1項該当 / Doctor of Informatics / Kyoto University / DGAM

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Ransomware is an ever-growing issue that has been affecting individuals and corporations since its inception, leading to losses of the order of billions each year. This research builds upon the existing body of research pertaining to ransomware detection for Windows-based platforms through behavioral analysis using sandboxing techniques and classification using machine learning (ML), considering the various predefined function calls, known as API (Application Programming Interface) calls, made by ransomware and benign samples as classifying features. The primary aim of this research is to study the effect of the frequency of API calls made by ransomware samples spanning across a large number of ransomware families exhibiting varied behavior, and benign samples on the classification accuracy of various ML algorithms. Conducting an experiment based on this, a quantitative analysis of the ML classification algorithms was performed, for the frequency of API calls based input and binary input based on the existence of an API call, resulting in the conclusion that considering the frequency of API calls marginally improves the ransomware recall rate. The secondary research question posed by this research aims to justify the ML classification of ransomware by conducting behavioral analysis of ransomware and goodware in the context of the API calls that had a major effect on the classification of ransomware. This research was able to provide meaningful insights into the runtime behavior of ransomware and goodware, and how such behavior including API calls and their frequencies were in line with the MLbased classification of ransomware. / Master of Science / Ransomware is an ever-growing issue that has been affecting individuals and corporations since its inception, leading to losses of the order of billions each year. It infects a user machine, encrypts user files or locks the user out of their machine, or both, demanding ransom in exchange for decrypting or unlocking user data. Analyzing ransomware either statically or behaviorally is a prerequisite for building detection and countering mechanisms. Behavioral analysis of ransomware is the basis for this research, wherein ransomware is analyzed by executing it on a safe sandboxed environment such as a virtual machine to avoid infecting a real-user machine, and its runtime characteristics are extracted for analysis. Among these characteristics, the various predefined function calls, known as API (Application Programming Interface) calls, made to the system by ransomware will serve as the basis for the classification of ransomware and benign software. After analyzing ransomware samples across various families, and benign samples in a sandboxed environment, and considering API calls as features, the curated dataset was fed to a set of ML algorithms that have the capability to extract useful information from the dataset to take classification decisions without human intervention. The research will consider the importance of the frequency of API calls on the classification accuracy and also state the most important APIs for classification along with their potential use in the context of ransomware and goodware to justify ML classification. Zero-Day detection, which refers to testing the accuracy of trained ML models on unknown ransomware samples and families was also performed.

L’étude et la compréhension du comportement humain est devenue l’une des problématiques majeures dans différents secteurs d’activités. Ce besoin de comprendre les habitudes des individus a conduit plusieurs entreprises vers l’utilisation de vidéos pour l’analyse et l’interprétation des comportements. Ces raisons ont conduit à l’émergence de travaux de recherches qui ont pour objectif l’automatisation de ces procédures. De ce fait, l’étude du comportement humain est devenue l’un des principaux sujets de recherche dans le domaine de la vision par ordinateur, et de nombreuses solutions d’analyse du comportements basées sur l’utilisation de l’intelligence artificielle ont émergé.Dans ce travail, notre objectif est le développement d’un système qui va permettre de suivre simultanément plusieurs individus dans un réseau multi-caméras dans le contexte de l’analyse comportementale. Pour cela, nous avons proposé un système de suivi qui est composé de trois modules principaux et d’un module de gestion. Le premier est un module de comptage pour mesurer les entrées. Le deuxième module, basé sur l’utilisation de filtres à particules, est un système de suivi mono-caméra destiné à suivre les individus indépendamment dans chacune des caméras. Le troisième module, basé sur la sélection des régions saillantes de chaque individu, sert à la ré-identification et permet d’associer les individus détectés dans les différentes caméras. Enfin, le module de gestion est conçu pour créer des trajectoires sémantiques à partir des trajectoires brutes obtenues précédemment. / The study and the understanding of human behavior has become one of the major concerns for various reasons in different sectors of activity. This need to understand the habits of people led several big firms towards the use of videos surveillance for analyzing and interpreting behaviors. These reasons led to the emergence of research aimed at automating these procedures. As a result, the study of human behavior has become the main subject of several researches in the field of computer vision. Thus, a variety of behavior analysis solutions based on artificial intelligence emerged.In this work, our objective is the proposal of a solution that enable the simultaneous track of several individuals in a multi-camera network in order to reconstruct their trajectories in the context of behavioral analysis. For this, we have proposed a system that is made of three main modules and a management module. The first module is a counting module to measure entries. The second module is a mono-camera tracking system that is based on the use of particle filtering to track individuals independently in each camera. The third module is a re-identification module which is based on the selection of salient regions for each individual. It enables the association of the individuals that are detected in the different cameras. The last module which is the management module is based on the use of ontologies for interpreting trajectories. This module is designed to create semantic trajectories from raw trajectories obtained previously.

Orientador: Jair Lopes Junior / Banca: Kester Carrara / Banca: Sérgio Dias Cirino / Resumo: O modelo de mudança conceitual,de reconhecida difusão na área do Ensino de Ciências,foi alvo de diversas críticas e revisões ao longo dos mais de vinte anos desde sua proposição inicial. oder-se-ia afirmar,no entanto,que tanto os proponentes do modelo quanto seus críticos apresentam um enfoque restritivo no tratamento das medidas comportamentais correspondentes à ocorrência ou não de mudança conceitual. Admite-se,como hipótese deste trabalho,que o Behaviorismo Radical propicia ferramentas capazes de uma avaliação da pertinência das críticas dirigidas ao modelo e da própria proposta de avaliação dos resultados obtidos através de sua utilização,tal como apresentada por seus proponentes . Para tanto, o presente trabalho concentrou ênfase na tentativa de,considerando estudos que ilustram a difusão posterior do modelo em trabalhos empíricos,descrever as medidas comportamentais que parecem fundamentar inferências sobre a ocorrência ou não da mudança conceitual,analisando se e como o tratamento de tais medidas foi considerado em alguns dos artigos que expressam uma revisão crítica do modelo Argumenta-se que tais artigos falham em descrever semelhanças e diferenças dos instrumentos e das interações que definem a obtenção das medidas comportamentais de conhecimentos prévios e posteriores à intervenção,bem como as intervenções intencionalmente planejadas e as condições de avaliação que sucedem a tais intervenções. / Abstract: The conceptual change model, well-known spread in Science Teaching, has been reviewed and criticized, since its initial proposal, for over twenty years. It could be argued, however, that either authors or critics present a restrictive view concerning the behavioral measures related to the absence or occurrence of conceptual change. The hypothesis within this paper is that Radical Behaviorism provides tools that can assess the pertinence of criticisms toward the model as well as the result evaluation proposal obtained from their application, as referred to by their proponents. Thus, the emphasis of this paper, taking into account studies that illustrate the posterior spreading of the model in empirical applications, is the attempt to describe the behavioral measures that seem to support inferences about the occurrence or absence of conceptual change, analyzing whereas and how the treatment of such measures were considered in some articles expressing a critical revision of the model. We understand that such articles have failed to describe similarities and differences concerning the instruments and interactions that define the achievement of behavioral measures from the knowledge (and not about responses) before and after the intervention, as well as intentionally planned interventions and the assessment conditions subsequent to the interventions. / Mestre