This master thesis deals with the implementation of information security management system in the company. It summarizes the theoretical background in this field and uses it to analyze the current state of information security, as well as analysis and risk management and not least the actual implementation of ISMS in the particular company. This work also contains three groups of measures that reduce the impact of identified risks and which also implements an essential parts of ISMS.

The subject of this thesis is risk management in construction companies. The theoretical part describes the origin and definition of risk, risk classification, sources and methods of risk management and risk reduction. The practical part is focused on a particular contract, in the particular construction company. This project presents a practical approach and risk management solutions with suggestions for preventive measures to eliminate risk factors.

The aim of this master's thesis is to present risk management and methods used in risk management. The thesis is based on the ATOM methodology, which was developed for practical risk management. The thesis is focused on methods of the visualization that should present risks at IT projects with an intuitive and understandable form. It also concerns with different options of the visualization and their use at risk management. The visualization could be like a table, a graph, or another form. The thesis also contains requirements specification for risk visualization application created due to found information. The design and implementation of the project management risk visualization application is based on requirements specification. The benefits of the thesis and possible extensions are proposed at the end.

Software Defined Networking (SDN) is a technology which provides a network architecture with three distinct layers that is, the application layer which is made up of SDN applications, the control layer which is made up of the controller and the data plane layer which is made up of switches. However, the exits different types of SDN architectures some of which are interconnected with the physical network. At the core of SDN, the control plane is physically and logically separated from the data plane. The controller is connected to the application layer through an interface known as the northbound interface and to the data plane through another interface known as the southbound interface. The centralized control plane uses APIs to communicate through the northbound and southbound interface with the application layer and the data plane layer respectively. By default, these APIs such as Restful and OpenFlow APIs do not implement security mechanisms like data encryption and authentication thus, this introduces new network security threats to the SDN architecture. This report presents a technique known as threat modeling in SDN. To achieve this technique, attack scenarios are created based on the OpenFlow SDN vulnerabilities. After which these vulnerabilities are defined as predicates or facts and rules, a framework known as multihost multistage vulnerability analysis (MulVAL) then takes these predicates and rules to produce a threat model known as attack graph. The attack graph is further used to performed quantitative risk analysis using a metric to depict the risks associated to the OpenFlow SDN model

Le principe de l'Internet des objets (IdO) est d'interconnecter non seulement les capteurs, les appareils mobiles et les ordinateurs, mais aussi les particuliers, les maisons, les bâtiments intelligents et les villes, ainsi que les réseaux électriques, les automobiles et les avions, pour n'en citer que quelques-uns. Toutefois, la réalisation de la connectivité étendue de l'IdO tout en assurant la sécurité et la confidentialité des utilisateurs reste un défi. Les systèmes IdO présentent de nombreuses caractéristiques non conventionnelles, telles que l'évolutivité, l'hétérogénéité, la mobilité et les ressources limitées, qui rendent les solutions de sécurité Internet existantes inadaptées aux systèmes basés sur IdO. En outre, l'IdO préconise des réseaux peer-to-peer où les utilisateurs, en tant que propriétaires, ont l'intention d'établir des politiques de sécurité pour contrôler leurs dispositifs ou services au lieu de s'en remettre à des tiers centralisés. En nous concentrant sur les défis scientifiques liés aux caractéristiques non conventionnelles de l'IdO et à la sécurité centrée sur l'utilisateur, nous proposons une infrastructure sécurisée de l'IdO activée par la technologie de la chaîne de blocs et pilotée par des réseaux peer-to-peer sans confiance. Notre infrastructure sécurisée IoT permet non seulement l'identification des individus et des collectifs, mais aussi l'identification fiable des objets IoT par leurs propriétaires en se référant à la chaîne de blocage des réseaux peer-to-peer sans confiance. La chaîne de blocs fournit à notre infrastructure sécurisée de l'IdO une base de données fiable, immuable et publique qui enregistre les identités individuelles et collectives, ce qui facilite la conception du protocole d'authentification simplifié de l'IdO sans dépendre des fournisseurs d'identité tiers. En outre, notre infrastructure sécurisée pour l'IdO adopte un paradigme d'IdO socialisé qui permet à toutes les entités de l'IdO (à savoir les individus, les collectifs, les choses) d'établir des relations et rend l'IdO extensible et omniprésent les réseaux où les propriétaires peuvent profiter des relations pour définir des politiques d'accès pour leurs appareils ou services. En outre, afin de protéger les opérations de notre infrastructure sécurisée de l'IdO contre les menaces de sécurité, nous introduisons également un mécanisme autonome de détection des menaces en complément de notre cadre de contrôle d'accès, qui peut surveiller en permanence le comportement anormal des opérations des dispositifs ou services. / The premise of the Internet of Things (IoT) is to interconnect not only sensors, mobile devices, and computers but also individuals, homes, smart buildings, and cities, as well as electrical grids, automobiles, and airplanes, to mention a few. However, realizing the extensive connectivity of IoT while ensuring user security and privacy still remains a challenge. There are many unconventional characteristics in IoT systems such as scalability, heterogeneity, mobility, and limited resources, which render existing Internet security solutions inadequate to IoT-based systems. Besides, the IoT advocates for peer-to-peer networks where users as owners intend to set security policies to control their devices or services instead of relying on some centralized third parties. By focusing on scientific challenges related to the IoT unconventional characteristics and user-centric security, we propose an IoT secure infrastructure enabled by the blockchain technology and driven by trustless peer-to-peer networks. Our IoT secure infrastructure allows not only the identification of individuals and collectives but also the trusted identification of IoT things through their owners by referring to the blockchain in trustless peer-to-peer networks. The blockchain provides our IoT secure infrastructure with a trustless, immutable and public ledger that records individuals and collectives identities, which facilitates the design of the simplified authentication protocol for IoT without relying on third-party identity providers. Besides, our IoT secure infrastructure adopts socialized IoT paradigm which allows all IoT entities (namely, individuals, collectives, things) to establish relationships and makes the IoT extensible and ubiquitous networks where owners can take advantage of relationships to set access policies for their devices or services. Furthermore, in order to protect operations of our IoT secure infrastructure against security threats, we also introduce an autonomic threat detection mechanism as the complementary of our access control framework, which can continuously monitor anomaly behavior of device or service operations.

La société contemporaine fait face à un niveau de menace sans précédent depuis la seconde guerre mondiale. La lutte contre le trafic illicite mobilise aussi l’ensemble desorganes de police, visant à endiguer le financement du crime organisé. Dans cet effort, les autorités s’engagent à employer des moyens de plus en plus modernes, afin notamment d’automatiser les processus d’inspection. L’objectif de cette étude est de développer des outils de vision par ordinateur afin d’assister les officiers de douanes dans la détection d’armes et de narcotiques. Letravail présenté examine l’emploi de techniques avancées de classification et de recalage d’images pour l’identification d’irrégularités dans des acquisitions radiographiques de fret. Plutôt que de recourir à la reconnaissance par apprentissage, nos méthodes revêtent un intérêt particulier lorsque les objets ciblés présentent des caractéristiques visuelles variées. De plus, elles augmentent notablement la détectabilité d’éléments cachés dans des zones denses, là où même les algorithmes de reconnaissance n’identifieraient pas d’anomalie. Nos travaux détaillent l’état de l’art des méthodes de classification et de recalage, explorant aussi diverses pistes de résolution. Les algorithmes sont testés sur d’importantes bases de données pour apprécier visuellement et numériquement leurs performances / Our societies, faced with an unprecedented level of security threat since WWII, must provide fast and adaptable solutions to cope with a new kind of menace. Illicit trade also, oftencorrelated with criminal actions, is viewed as a defining stake by governments and agencies. Enforcement authorities are thus very demandingin terms of technological features, asthey explicitly aim at automating inspection processes. The main objective of our research is to develop assisting tools to detect weapons and narcotics for lawenforcement officers. In the present work, we intend to employ and customize both advanced classification and image registration techniques for irregularity detection in X-ray cargo screening scans. Rather than employing machine-learning recognition techniques, our methods prove to be very efficient while targeting a very diverse type of threats from which no specific features can be extracted. Moreover, the proposed techniques significantly enhance the detection capabilities for law-enforcement officers, particularly in dense regions where both humans or trained learning models would probably fail. Our work reviews state-of-the art methods in terms of classification and image registration. Various numerical solutions are also explored. The proposed algorithms are tested on a very large number ofimages, showing their necessity and performances both visually and numerically.

Certain Small Island Developing States (hereinafter the "SIDS") such as Kiribati or Tuvalu are often incorrectly called "sinking islands" because their highest points are located just a few meters above the sea level. Sea level rise may turn their territories to uninhabitable land gradually disappearing beneath the tide. Worsening of the environmental conditions causes internal displacement, migration and other problems. SIDS repeatedly brought their plight to the United Nations Security Council (the "UNSC") during its meetings in 2007, 2011, 2015, 2018 and 2019. They demanded that the UNSC should deal with their situation as a potential security issue and safeguard more equal distribution of environmental security risks and costs. During the UNSC negotiations, various states attempted to interpret and re-interpreted the UNSC mandate in order to suit their interests. The representatives of SIDS suggested that the UNSC should be a body based on the principles of distributive justice decision-making and thus safeguard fairer sharing of threats and burdens, including those of environmental character. The rapidly developing states strongly opposed; they implicitly claimed that the UNSC should be based rather on the principles of commutative justice, i.e. decide in strictly given situations of violations of...

The problem that was identified is that physical surveillance is not generally used by general detectives in the South African Police Service as a technique during their investigations. According to the researcher’s experience, this can be due to lack of understanding or experience or may stem from ignorance. A lack of training on the use of physical surveillance as a method to obtain information for the investigation process was also identified as a problem. This study therefore investigated the role and use of physical surveillance within the forensic investigation process. The focus of the research was on basic static (stationary), foot and vehicle surveillance as these types of surveillance are usually conducted in conjunction with each other. An empirical research design was used to conduct the research. A qualitative research approach enabled the researcher to obtain first-hand information from interviews with general detectives. Information was also obtained from a thorough literature study and from the researcher’s own experience on the topic. To conduct effective investigation, it is important for investigators to be familiar with the concept of physical surveillance, its elements, its influence and its values. A physical surveillance operation is a forensic tool used to gather evidence, to recover stolen property, and to identify and arrest the perpetrator. The use of physical surveillance during investigations serves the purpose of gathering evidence and information that can be used as intelligence. Successful forensic investigation requires skill and places extraordinary demands on detectives to utilise all available methods and techniques. The recognition of the use of physical surveillance as a method of evidence gathering is of outmost importance. The research has revealed that general detectives do not acknowledge the importance of physical surveillance as a method to obtain information for the investigation process. It is of vital importance that all detectives be properly trained with the necessary knowledge and skills to make use of this valuable investigative tool. / Police Practice / M. Tech. (Forensic Investigation)

Inspired by the enormous technological advancements of previous decades, this doctoral thesis revolves around users’ perception of emotion-sensitive artificial intelligence (AI), with particular focus on the role of human likeness attributions. For the development of my hypotheses, I acknowledge both cognitive scientific as well as philosophical and cultural psychological literature. Eventually, my interdisciplinary review culminates in one central assumption: Since many people regard the recognition of mental and emotional states in other entities as a core component of their human uniqueness, affective technology with similar capabilities runs the risk of being seen as uncanny or aversive—turning into a discomforting ‘challenger’ of an inherently human domain. Indeed, a first empirical study (N = 92) provides evidence for the validity of my hypothesis. My findings show that empathically acting characters in a virtual environment are met with much stronger aversion if participants suspect them to be controlled by highly complex AI (autonomous agents) instead of other humans (avatars). Acknowledging statements from my participants which repeatedly hint towards the importance of threat perceptions, I turn this concept into the main subject of a second study. Based on additional literature research, I develop a “Model of Autonomous Technology Threat”, which combines two potential determinants of technology aversion: Whereas the model’s distal facet summarizes overarching attitudes about human uniqueness, I also postulate a strong influence of immediate (proximal) perceptions, including the experience of situational control or users’ concern about their immediate physical well-being. Using yet another virtual reality (VR) setting, I ask participants (N = 125) to interact with an allegedly autonomous—in fact remotely controlled—digital agent under different conditions, which allow for a statistical comparison of my proposed model. Although the yielded results do lend some support to the validity of the distal path, it is mostly the proposed proximal factor that connects to participants’ threat experience, which in turn emerges as a negative predictor of technology acceptance. Lastly, a third study is designed to investigate whether perceptions of human likeness possess any relevance in the context of disembodied emotion-sensitive AI. Moreover, I now focus on potential cross-cultural differences, inviting participants from different cultural backgrounds (N = 89) to familiarize themselves with automatic emotion recognition software. Whereas Chinese participants, whose cultural socialization encompasses a much broader understanding of ‘animacy’, only show brief arousal after feedback from the affective software, I observe a significantly longer increase in physiological activity among German participants. At the same time, the obtained subjective measures paint a surprising picture: The more participants attribute human likeness to the emotion-sensitive machine—an abstract mechanical box in this scenario—the higher they actually rate the technology’s attractiveness. By summarizing the three conducted studies, I reach the conclusion that only AI stimuli involving elaborate embodiments activated both paths of the developed threat model, which might be a requirement for a distinctly aversive reaction. The presentation of the abstract software in Study 3, on the other hand, did not influence participants’ immediate control perceptions—a possible explanation as to why attributions of human likeness turned out as a positive predictor for the subjective evaluations in this experiment. / Inspiriert von den enormen technologischen Fortschritten der letzten Jahrzehnte beschäftigt sich die vorliegende Dissertation mit der Wahrnehmung emotionssensitiver künstlicher Intelligenz (KI) und nimmt dabei vor allem die Bedeutung von erlebter Menschenhaftigkeit in den Fokus. Bei der Entwicklung meiner Hypothesen finden Befunde von kognitionswissenschaftlichen Studien ebenso Beachtung wie philosophische und kulturpsychologische Literatur. Tatsächlich gipfelt die interdisziplinäre Recherche in einer deutlichen Vermutung: Da das Erkennen von Geistes- und Gefühlszuständen in anderen Lebewesen von vielen Personen als Kernkomponente ihrer menschlichen Einzigartigkeit betrachtet wird, laufen affektive Technologien mit ähnlichen Fähigkeiten Gefahr, unheimlich oder abstoßend zu wirken – sie werden zu unliebsamen ‚Eroberern‘ einer urmenschlichen Domäne. In einer ersten empirischen Studie (N = 92) finde ich Hinweise auf die Gültigkeit der getroffenen Annahme. Es zeigt sich, dass empathisch agierende Figuren in einer virtuellen Umgebung deutlich stärkere Ablehnung hervorrufen, wenn Probanden dahinter keine Menschen (Avatare), sondern ein hochkomplexes KI-System (autonome Agenten) vermuten. Nachdem persönliche Beobachtungen und Aussagen der Versuchspersonen wiederholt auf die Rolle von Bedrohungswahrnehmnungen hindeuten, stelle ich diese Variable ins Zentrum einer zweiten Untersuchung. Mithilfe vertiefender Literaturrecherche entwickle ich ein „Model of Autonomous Technology Threat“ („Modell der Bedrohung durch autonome Technologie“), welches zwei potentielle Determinanten von Technologieaversion kombiniert: Während die distale Facette übergeordnete Einstellungen zu menschlicher Einzigartigkeit bündelt, wird zudem ein starker Einfluss von unmittelbaren (proximalen) Wahrnehmungen postuliert, etwa dem erlebten Ausmaß an situativer Kontrolle oder der Sorge um die eigene physische Unversehrtheit. Ein neues Virtual-Reality-Experiment, in dem Probanden (N = 125) mit einem angeblich autonomen – tatsächlich jedoch ferngesteuerten – Agenten interagieren, dient dazu, das Modell statistisch zu überprüfen. Obgleich sich durchaus Hinweise zur Bedeutsamkeit des distalen Pfades abzeichnen, erweisen sich vor allem proximale Faktoren als signifikanter Prädiktor von Bedrohungsempfinden und infolgedessen der Nutzerakzeptanz. Mit einer dritten Studie soll schließlich exploriert werden, inwieweit die Wahrnehmung von Menschenartigkeit auch bei nicht verkörperlichten, emotionssensitiven KIs Relevanz besitzt. Zugleich rücke ich nun Kultureinflüsse in den Fokus, indem ich Versuchspersonen verschiedener kultureller Herkunft (N = 89) eine automatisierte Emotionserkennungssoftware kennenlernen lasse. Während chinesische Probanden, deren kulturelle Sozialisation tendenziell ein breiteres Verständnis von ‚Beseeltheit‘ umfasst, nur kurzzeitig vom Feedback der affektiven Software in Erregung versetzt werden, lässt sich bei deutschen Versuchspersonen ein deutlich längerer Anstieg physiologischer Aktivierung feststellen. Zugleich zeichnet die Messung subjektiver Empfindungen ein überraschendes Bild: Die emotionssensitive Maschine – in diesem Fall ein abstrakter, mechanischer Kasten – wird umso positiver bewertet, je mehr Menschenhaftigkeit Probanden in ihr erkennen. Angesichts der drei durchgeführten Studien komme ich zu dem Schluss, dass lediglich Szenarien mit verkörperlichter KI im Sinne des entwickelten Bedrohungsmodells beide Pfade bedienen, was für eine eindeutig aversive Reaktion erforderlich sein könnte. Die Gestaltung der Software in Studie 3 spielte unterdessen für das unmittelbare Kontrollerleben der Versuchspersonen keine Rolle; eine mögliche Erklärung, warum sich Attributionen von Menschenähnlichkeit hier sogar positiv in den subjektiven Evaluationen niederschlugen.

La web oscura es una zona propicia para actividades ilegales de todo tipo. En los últimos tiempos los cibercriminales están cambiando su enfoque hacia el tráfico de informacion (personal o corporativa) porque los riesgos son mucho más bajos en comparación con otros tipos de delito. Hay una gran cantidad de información alojada aquí, pero pocas compañías saben cómo acceder a estos datos, evaluarlos y minimizar el daño que puedan causar. El presente trabajo propone un modelo de referencia para identificar el nivel de madurez del proceso de Ciber Inteligencia de Amenazas. Esta propuesta considera la información comprometida en la web oscura, originando un riesgo latente que las organizaciones no consideran en sus estrategias de ciberseguridad. El modelo propuesto tiene como objetivo aumentar el nivel de madurez del proceso mediante un conjunto de controles propuestos de acuerdo a los hallazgos encontrados en la web oscura. El modelo consta de 3 fases:1. Identificación de los activos de información mediante herramientas de Ciber inteligencia de amenazas. 2. Diagnóstico de la exposición de los activos de información. 3. Propuesta de controles según las categorías y criterios propuestos. La validación de la propuesta se realizó en una institución de seguros en Lima, Perú con datos obtenidos por la institución. Los resultados preliminares mostraron 196 correos electrónicos y contraseñas expuestos en la web oscura de los cuales 1 correspondía al Gerente de Tecnología. Con esta identificación, se diagnosticó que la institución se encontraba en un nivel de madurez “Normal”, y a partir de la implementación de los controles propuestos se llegó al nivel “Avanzado”. / The dark web is an area conducive to illegal activities of all kinds. In recent times, cybercriminals are changing their approach towards information trafficking (personal or corporate) because the risks are much lower compared to other types of crime. There is a wealth of information hosted here, but few companies know how to access this data, evaluate it, and minimize the damage it can cause. In this work, we propose a reference model to identify the maturity level of the Cyber ​​Intelligence Threat process. This proposal considers the dark web as an important source of cyber threats causing a latent risk that organizations do not consider in their cybersecurity strategies. The proposed model aims to increase the maturity level of the process through a set of proposed controls according to the information found on the dark web. The model consists of 3 phases: 1. Identification of information assets using cyber threat intelligence tools. 2. Diagnosis of the exposure of information assets. 3. Proposal of controls according to the proposed categories and criteria. The validation of the proposal was carried out in an insurance institution in Lima, Peru with data obtained by the institution. Preliminary results showed 196 emails and passwords exposed on the dark web of which 1 corresponded to the Technology Manager of the company under evaluation. With this identification, it was diagnosed that the institution was at a “Normal” maturity level, and from the implementation of the proposed controls the “Advanced” level was reached. / Tesis