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Många mänskliga aktiviteter skapar miljöproblem som kan resultera i irreversibla och allvarligakonsekvenser för allt levande. Kognitiva, emotionella och ekonomiska barriärer utgör en grogrund förmiljörelaterad skepsis och förnekelse. Denna studie fokuserar på till vilken grad svenska män respektivekvinnor är skeptiska eller förnekar i förhållande till miljöproblem. Andra studier som gjorts kring detta visarpå att män är något mer skeptiska och förnekar något mer i förhållande till miljöproblem än kvinnor.Metoderna som använts i denna studie är enkät och kompletterande semi-strukturerade intervjuer. Det totalaresultatet bekräftar i stort sätt de andra studiernas resultat och lyder att män i något högre grad än kvinnorförnekar och är skeptiska i relation till miljöproblem. / Many human activities cause environmental issues that can result in irreversible and serious consequencesfor all living things. Cognitive, emotional and economic barriers constitute a hotbed for environmentalskepticism and denial. In this study, the focus is on the degree to which Swedish men and women areskeptical or in denial in relation to environmental issues. Other studies concerning this show that men aresomewhat more skeptical and deny somewhat more in relation to environmental issues than women. Themethods used in this study is a questionnaire and additional semi-structured interviews. The overall resultconfirms by and large the results of the other studies concerning this and shows that men are somewhat morelikely than women to deny and to be skeptical in relation to environmental issues.

With the ever increasing deployment and usage of gigabit networks, traditional network anomaly detection based intrusion detection systems have not scaled accordingly. Most, if not all, systems deployed assume the availability of complete and clean data for the purpose of intrusion detection. We contend that this assumption is not valid. Factors like noise in the audit data, mobility of the nodes, and the large amount of data generated by the network make it difficult to build a normal traffic profile of the network for the purpose of anomaly detection. From this perspective, the leitmotif of the research effort described in this dissertation is the design of a novel intrusion detection system that has the capability to detect intrusions with high accuracy even when complete audit data is not available. In this dissertation, we take a holistic approach to anomaly detection to address the threats posed by network based denial-of-service attacks by proposing improvements in every step of the intrusion detection process. At the data collection phase, we have implemented an adaptive sampling scheme that intelligently samples incoming network data to reduce the volume of traffic sampled, while maintaining the intrinsic characteristics of the network traffic. A Bloom filters based fast flow aggregation scheme is employed at the data pre-processing stage to further reduce the response time of the anomaly detection scheme. Lastly, this dissertation also proposes an expectation-maximization algorithm based anomaly detection scheme that uses the sampled audit data to detect intrusions in the incoming network traffic. / Ph. D.

Behavioral and physiological reactivity, and its relationship to cardiovascular disease has been studied in men for a number of years, and the expression of anger has been identified as a possible contributing factor. Few studies, however, have focused specifically on the reactivity of women, and those which have suggest that women are less reactive to laboratory tasks than men. For the present study, 45 undergraduate women, ages 19-21 were selected from a larger sample of 135 women to represent three discrete groups: (1) low anger/low denial, (2) high anger/low denial, and (3) low anger/high denial, based on their scores on the State-Trait Anger Expression Inventory, P and the Marlowe-Crowne Social Desirability Scale. It was hypothesized that the three groups would show reliable differences in heart rate and blood pressure during presentation of a stressful laboratory stimulus, the Stroop Color and Word Test. Each subject received three counterbalanced conditions: (1) no feedback, (2) error feedback without observer present, (3) error feedback with observer present. As hypothesized, women who reported a high level of denial and a low level of anger exhibited reliably greater systolic blood pressure to the no-feedback condition than subjects who reported low levels of denial and anger. The hypothesis that all groups would display greater A reactivity in a condition which provided error feedback with observation was not supported. / Master of Science

Multi-cloud applications are becoming a universal way for organizations to build and deploy systems. Multi-cloud systems are deployed across several different service providers, whether this is due to company mergers, budget concerns, or services provided with each provider. With the growing concerns of potential cyber attacks, security of multi-cloud is an important subject, especially within the communications between systems through Application Programming Interfaces (APIs). This thesis presents an in depth analysis of multi-cloud, looking at APIs and security, creates a mock architecture for a multi-cloud system, and executes a cyber attack on this architecture to demonstrate the catastrophic effects that could come of these systems if left unprotected. Finally, some solutions for security are discussed as well as the potential plan for more testing of cyber attacks in this realm

Similarities exist between the current climate change movement and the earlier suffragette movement. Both are progressive, challenge the status quo, have feminist underpinnings, and face opposition from the political right and through the media. However, the link between the similarities in argumentative opposition between the two, remains unestablished. Therefore, this study seeks to first establish the argumentative strategies developed to oppose climate activists and then place these in a historical perspective by comparing them to the opposition to women's suffrage in Sweden. Using rhetorical topoi analysis, this study examined Facebook posts to find, categorize, and analyze arguments with the help of green backlash and countermovement theory. These findings were then compared with pre-established arguments against women's suffrage in Sweden. The study finds that the argumentative strategies deployed against Swedish climate activists are characterized by climate denial, hostility, and mockery, which are used as tactics to discredit, undermine, and oppose them. The analysis also shows a historical resemblance between the opposition to climate activists and the suffragettes, highlighting the recurring resistance to socially progressive pro-women movements.

Distibuted denial of service (DDoS) attacks are getting more and more common in society as the number of devices connected to the Internet is increasing. To reduce the impact of such attacks it is important to detect them as soon as possible. Many papers have investigated how well different machine learning algorithms can detect DDoS attacks. However, most papers are focusing on supervised learning algorithms which require a lot of labeled data, which is hard to find. This thesis compares two unsupervised learning algorithms, an autoencoder and principal component analysis (PCA), in how well they detect DDoS attacks. The models are implemented in the Python libraries Keras, Tensorflow and scikit-learn. They are then trained and tested with data that has its origin in the CICDDOS2019 dataset. There are normal data and nine different types of DDoS attacks in the used dataset. The models are compared by computing the Receiver Operating Characteristic (ROC) curve and its Area Under the Curve (AUC) score, and the F1 score of the models. For both measures the mean value of the results of all attack types are used. The computations show that the autoencoder perform better than PCA with respect to both the mean AUC score (0.981 compared to 0.967) and the mean F1 score (0.987 compared to 0.978). The thesis goes on to discussing why the autoencoder performs better than PCA and, finally draws conclusions based on the insights of the analysis.

A cyber-physical control system (CPS) typically consists of a set of physical subsystems, their remote terminal units, a central control center (if applicable), and local communication networks that interconnect all the components to achieve a common goal. Applications include energy systems, autonomous vehicles, and collaborative robots. Ensuring stability, performance, and resilience in CPS requires thorough analysis and control design, utilizing robust algorithms to handle delays, communication failures, and potential cyber-attacks. Time delays are a challenge in CPS, particularly in teleoperation systems, where human operators remotely control robotic systems. These delays cause chattering, oscillations, and instability, making it difficult to achieve smooth and stable remote robot control. Applications like remote surgery, space exploration, and hazardous environment operations are highly susceptible to these disruptions. To address this issue, a novel passivity-shortage framework is proposed, that enables systems to maintain stability and transparency despite time-varying communication delays and environmental disturbances. CPS are prone to attacks, particularly Denial-of-Service (DoS) attacks, which disrupt the normal functioning of a network by overwhelming it with excessive internet traffic, rendering the communication channels unavailable to legitimate users. These attacks threaten the stability and functionality of CPS. To enhance resilience in multi-agent systems, novel distributed algorithms are proposed. These graph theory-based algorithms mitigate network vulnerabilities by incorporating strategically placed additional communication channels, thereby increasing tolerance to attacks in large, dynamic networks. The effectiveness of these proposed approaches is validated through simulations, experiments, and numerical examples. The passivity-shortage teleoperation strategies are tested using Phantom Omni devices and they show reduced chattering and better steady-state error convergence. A case study demonstrates how the proposed distributed algorithms effectively achieve consensus, even when some agents are disconnected from the network due to DoS attacks.

Voice Over IP (VoIP) telephony is becoming widespread, and is often integrated into computer networks. Because of his, it is likely that malicious software will threaten VoIP systems the same way traditional computer systems have been attacked by viruses, worms, and other automated agents. While most users have become familiar with email spam and viruses in email attachments, spam and malicious traffic over telephony currently is a relatively unknown threat. VoIP networks are a challenge to secure against such malware as much of the network intelligence is focused on the edge devices and access environment. A novel security architecture is being developed which improves the security of a large VoIP network with many inexperienced users, such as non-IT office workers or telecommunication service customers. The new architecture establishes interaction between the VoIP backend and the end users, thus providing information about ongoing and unknown attacks to all users. An evaluation of the effectiveness and performance of different implementations of this architecture is done using virtual machines and network simulation software to emulate vulnerable clients and servers through providing apparent attack vectors.

Hearing voices is a well researched experience, found in both schizophrenia and the general population. Previous research investigating the unusual experience has reinforced cognitive psychology concepts such as beliefs, power, core beliefs about the self, intent and identity. It has been suggested that these factors all mediate individual coping with the experience. Coping with voices is a clinically significant area of research pioneered by Romme and Escher and requires careful consideration. Kelly‘s Personal Construct Psychology and the repertory grid technique were used in the study to compare two ways of coping with voices: engaging and resisting coping. The groups were compared on the repertory grid measures of construed distance between the self and the voice, salience of the self and voice, and tightness of the overall construct system. In a sample of 18 voice hearers, the Beliefs about Voices Questionnaire- Revised (BAVQ-R), a measure of psychological distress (OQ45.2) and Kelly‘s repertory grid were administered. The study also used three case examples and content analysis of construct poles applied to the dominant voice and the self as coper to supplement the quantitative analysis with a more in-depth exploration. Resisting coping was found to be associated with a greater construed distance between the self and the voice, a more salient view of the voice, and a tighter construct system. However, neither resisting nor engaging coping was associated with psychological distress. In addition, voice malevolence was associated with distancing oneself from the voice, suggesting that distancing was an adaptive coping strategy used, possibly as a way to preserve selfhood. The study therefore added to the list of mediating factors between the voice hearing experience and the coping strategy adopted. As a result, the repertory grid showed some scope in assessing the three areas of interest. The findings suggest that clinically, voice hearers can best be supported by adopting the appropriate relational approach with the voice (closeness or distance), reducing the salience of the voice and moving through Kelly‘s Creativity and Experience Cycle.