yes / Cyber attacks are increasing in every aspect of daily life. There are a number of different technologies around to tackle cyber-attacks, such as Intrusion Detection Systems (IDS), Intrusion Prevention Systems (IPS), firewalls, switches, routers etc., which are active round the clock. These systems generate alerts and prevent cyber attacks. This is not a straightforward solution however, as IDSs generate a huge volume of alerts that may or may not be accurate: potentially resulting in a large number of false positives. In most cases therefore, these alerts are too many in number to handle. In addition, it is impossible to prevent cyber-attacks simply by using tools. Instead, it requires greater intelligence in order to fully understand an adversary’s motive by analysing various types of Indicator of Compromise (IoC). Also, it is important for the IT employees to have enough knowledge to identify true positive attacks and act according to the incident response process. In this paper, we have proposed a new threat intelligence technique which is evaluated by analysing honeypot log data to identify behaviour of attackers to find attack patterns. To achieve this goal, we have deployed a honeypot on an AWS cloud to collect cyber incident log data. The log data is analysed by using elasticsearch technology namely an ELK (Elasticsearch, Logstash and Kibana) stack.

Threat assessment and reliable motion-prediction of surrounding vehicles are some of the major challenges encountered in autonomous vehicles' safe decision-making. Predicting a threat in advance can give an autonomous vehicle enough time to avoid crashes or near crash situations. Most vehicles on roads are human-driven, making it challenging to predict their intentions and movements due to inherent uncertainty in their behaviors. Moreover, different driver behaviors pose different kinds of threats. Various driver behavior predictive models have been proposed in the literature for motion prediction. However, these models cannot be trusted entirely due to the human drivers' highly uncertain nature. This thesis proposes a novel trust-based driver behavior prediction and stochastic reachable set threat assessment methodology for various dangerous situations on the road. This trust-based methodology allows autonomous vehicles to quantify the degree of trust in their predictions to generate the probabilistically safest trajectory. This approach can be instrumental in the near-crash scenarios where no collision-free trajectory exists. Three different driving behaviors are considered: Normal, Aggressive, and Drowsy. Hidden Markov Models are used for driver behavior prediction. A "trust" in the detected driver is established by combining four driving features: Longitudinal acceleration, lateral acceleration, lane deviation, and velocity. A stochastic reachable set-based approach is used to model these three different driving behaviors. Two measures of threat are proposed: Current Threat and Short Term Prediction Threat which quantify present and the future probability of a crash. The proposed threat assessment methodology resulted in a lower rate of false positives and negatives. This probabilistic threat assessment methodology is used to address the second challenge in autonomous vehicle safety: crash avoidance decision-making. This thesis presents a fast, proactive decision-making methodology based on Stochastic Model Predictive Control (SMPC). A proactive decision-making approach exploits the surrounding human-driven vehicles' intent to assess the future threat, which helps generate a safe trajectory in advance, unlike reactive decision-making approaches that do not account for the surrounding vehicles' future intent. The crash avoidance problem is formulated as a chance-constrained optimization problem to account for uncertainty in the surrounding vehicle's motion. These chance-constraints always ensure a minimum probabilistic safety of the autonomous vehicle by keeping the probability of crash below a predefined risk parameter. This thesis proposes a tractable and deterministic reformulation of these chance-constraints using convex hull formulation for a fast real-time implementation. The controller's performance is studied for different risk parameters used in the chance-constraint formulation. Simulation results show that the proposed control methodology can avoid crashes in most hazardous situations on the road. / Master of Science / Unexpected road situations frequently arise on the roads which leads to crashes. In an NHTSA study, it was reported that around 94% of car crashes could be attributed to driver errors and misjudgments. This could be attributed to drinking and driving, fatigue, or reckless driving on the roads. Full self-driving cars can significantly reduce the frequency of such accidents. Testing of self-driving cars has recently begun on certain roads, and it is estimated that one in ten cars will be self-driving by the year 2030. This means that these self-driving cars will need to operate in human-driven environments and interact with human-driven vehicles. Therefore, it is crucial for autonomous vehicles to understand the way humans drive on the road to avoid collisions and interact safely with human-driven vehicles on the road. Detecting a threat in advance and generating a safe trajectory for crash avoidance are some of the major challenges faced by autonomous vehicles. We have proposed a reliable decision-making algorithm for crash avoidance in autonomous vehicles. Our framework addresses two core challenges encountered in crash avoidance decision-making in autonomous vehicles: 1. The outside challenge: Reliable motion prediction of surrounding vehicles to continuously assess the threat to the autonomous vehicle. 2. The inside challenge: Generating a safe trajectory for the autonomous vehicle in case of future predicted threat. The outside challenge is to predict the motion of surrounding vehicles. This requires building a reliable model through which future evolution of their position states can be predicted. Building these models is not trivial, as the surrounding vehicles' motion depends on human driver intentions and behaviors, which are highly uncertain. Various driver behavior predictive models have been proposed in the literature. However, most do not quantify trust in their predictions. We have proposed a trust-based driver behavior prediction method which combines all sensor measurements to output the probability (trust value) of a certain driver being "drowsy", "aggressive", or "normal". This method allows the autonomous vehicle to choose how much to trust a particular prediction. Once a picture is painted of surrounding vehicles, we can generate safe trajectories in advance – the inside challenge. Most existing approaches use stochastic optimal control methods, which are computationally expensive and impractical for fast real-time decision-making in crash scenarios. We have proposed a fast, proactive decision-making algorithm to generate crash avoidance trajectories based on Stochastic Model Predictive Control (SMPC). We reformulate the SMPC probabilistic constraints as deterministic constraints using convex hull formulation, allowing for faster real-time implementation. This deterministic SMPC implementation ensures in real-time that the vehicle maintains a minimum probabilistic safety.

Stereotype threat is the threat of confirming a negative stereotype about a group with which a person identifies. Researchers have found that stereotype threat can result in underperformance in multiple domains, shifts in social behavior, and shifts in assessed implicit attitudes, the likelihood of which increases as an individual's concern about the domain of interest increases. According to theory, this threat can be "alleviated",thereby diminishing or eliminating its impact. In this project, over the course of two experiments, the impact of stereotype threat and stereotype threat-alleviation on explicit self-report measures are examined. In experiment one, white college student participants were exposed (or not) to an on-line task intended to elicit race-based stereotype threat. Differences in reporting style (i.e., bias) between the two groups on self-reported measures of race-related attitudes were examined. It was hypothesized that the group exposed to stereotype threat would endorse lower racism and lower stereotypicality (i.e., stereotypic "White" behaviors, attitudes, adjectives, and beliefs). The data provided only partial support for the hypothesis - the threat group reported significantly less stereotypicality than the non threat group. However, the groups were not statistically different on measures of racism or race and social policy. In experiment two, again examining white college students who participated on-line, a stereotype threat-alleviation task was added, and whether this diminished or removed bias was examined. It was hypothesized the threat group would endorse lower stereotypicality and racism than the non threat group and the group receiving the threat alleviation task. The findings from study one did not replicate in study two. Instead, contrary to predictions, across measures of racism and stereotypicality, it was the non threat group that consistently showed the lowest scores. Potential explanations for these findings are offered, including the possibility of having eliciting stereotype threat, cognitive dissonance, or both for the threat and non threat groups via their filler task. Finally, implications for assessing, broaching, and reducing stereotype threat in clinical and research applications are also discussed. / Ph. D.

Due to difficulties in elucidating neurobiological aspects of psychological disorders, the National Institute of Mental Health (NIMH) created the Research Domain Criteria (RDoC), which encourages novel conceptualizations of the relationship between neurobiological circuitry and clinical difficulties. This approach is markedly different from the Diagnostic and Statistical Manual of Mental Disorders (DSM) based approach that has dominated clinical research to date. Thus, RDoC necessitates exploration of novel experimental and statistical approaches. Fear learning paradigms represent a promising methodology for elucidating connections between acute threat (“fear”) circuitry and fear-related clinical difficulties. However, traditional analytical approaches rely on central tendency statistics, which are tethered to a priori categories and assume homogeneity within groups. Growth Mixture Modeling (GMM) methods such as Latent Class Growth Analysis (LCGA) may be uniquely suited for examining fear learning phenotypes. However, just three extant studies have applied GMM to fear learning and only one did so in a human population. Thus, the degree to which classes identified in known studies represent characteristics of the general population and to which GMM methodology is applicable across populations and paradigms is unclear. This preliminary study applied LCGA to a fear learning lab study in an attempt to identify heterogeneity in fear learning patterns based on a posteriori classification. The findings of this investigation may inform efforts to move toward a trans-diagnostic conceptualization of fear learning. Consistent with the goals laid out in RDoC, explication of fear learning phenotypes may eventually provide critical information needed to spur innovation in psychotherapeutic and psychopharmacological treatment. / Master of Science / To date, most clinical psychology research has been based on the Diagnostic and Statistical Manual of Mental Disorders (DSM), which is a catalog of mental health disorders that was originally designed to facilitate communication among clinicians. Many experts contend that this approach has hampered progress in the field of biological clinical psychology research. Thus, the National Institute of Mental Health (NIMH) created a new template for biological clinical psychology research called the Research Domain Criteria (RDoC). Since RDoC calls for a complete overhaul in the conceptualization of clinical dysfunction, this approach requires statistical and experimental innovation. One traditional experimental approach that may be helpful in understanding the RDoC topic of acute threat (“fear”) is called Pavlovian Fear Learning (PFL). However, traditional PFL studies have utilized statistical methods that are based on comparing group averages and require researchers to determine groups of interest based on theory before the study begins. This is problematic because RDoC calls for research that begins with evidence rather than theory. Growth Mixture Modeling (GMM) is a statistical methodology that may allow researchers to analyze fear learning data without having to begin with theoretically determined categories such as DSM disorders. However, little research has tested how well this approach would work. This study is just the second to apply a GMM approach to a human PFL study. The findings from this investigation may inform efforts to develop a statistical technique that is well suited for RDoCian research and may also spur innovation in psychotherapeutic and psychopharmacological treatment.

The competing values of national security and civil liberties have been contested as conflicting ideas during times of national emergencies and war, in which the canonical knowledge asserts that the temporary secession of civil liberties is sometimes necessary to protect national security. After the September 11, 2001 terrorist attack there has been increased pressure on the U.S. government to provide safety and security, which has required Americans to accept certain restrictions on their freedoms, leading to debates about whether liberty or security should be prioritized. The increasing popularization of securitization in post 9/11 discourse justified by a perpetual state of emergency via the War on Terror, has reinforced the racialization of reified "others," specifically Muslims or people who are perceived to be descendent from the Middle East. The conceptualization of Middle Easterners as 'terrorists' and 'threats' to be securitized has been constructed by political elites and media narratives to garner support for security measures leading to the diminished civil liberties of those stereotyped as "terrorists." Using the theoretical approach of racialized "othering" and the minority threat perception, this research seeks to analyze public opinion on counterterrorism policies when the race/ethnicity and ideological motivations of perpetrators in a hypothetical terrorist attack scenario are manipulated. To investigate this premise, an online survey experiment distributed through Amazon MTurk was conducted to gather public opinion data on counterterrorism policies. Regression analyses were conducted from the 314 respondents to evaluate support amongst various social groups for the counterterrorism policies and whether or not this support was affected by the presence of either American-born, White, men motivated by the teachings of far-right extremism or American-born, men of Middle Eastern descent motivated by the teachings of Islamic extremism. Respondents were asked to evaluate two counterterrorism policies, one that required ceding the civil liberties of the public at large, and the other required ceding the civil liberties of suspected terrorists specifically – which is also referred to as the 'punitive' policy throughout the research. Overall, respondents were more likely to support the policy requiring ceding civil liberties in general, than the punitive policy that would take away the civil liberties of suspected terrorist. When factoring in survey type, respondents in general were more likely to support the punitive policy when taking the White/Far-right extremism survey and were also the most likely to support the policy requiring the public to cede their civil liberties when taking the Middle Eastern/Islamic extremism survey. The willingness to cede civil liberties increased for Black and Asian respondents with the presence of the White/Far-right extremism survey, while willingness to cede civil liberties decreased for White respondents taking the same survey. In general, conservatives were more likely to cede their civil liberties than liberals, and liberals were more likely to view counterterrorism policies as ineffective. When accounting for the effects of survey type on ideology, the results show that conservatives were the least likely to cede their civil liberties when taking the White/Far-right extremism survey, while liberals were the most likely to cede their civil liberties when taking the Middle Eastern/Islamic extremism survey. / Master of Arts / This thesis explores the role of issue framing, and threat perception on terrorism and its effects on public perception of the liberty vs. security paradigm by way of support for counterterrorism policies. Specifically, this research aims to assess whether support for counterterrorism policies by social group (focusing on race and ideology) varies when the race/ethnicity and ideological motivations of the perpetrators are manipulated in a hypothetical terrorist attack scenario. In order to test this effect, a survey experiment was conducted to gather public opinion data on counterterrorism policies which emulated the liberty/security trade-offs within the Patriot Act. The survey was distributed through the online platform Amazon MTurk which garnered 314 responses. Regression analyses were conducted to evaluate support amongst various social groups for the counterterrorism policies and whether or not this support was affected by the presence of either American-born, White, men motivated by the teachings of far-right extremism or American-born, men of Middle Eastern descent motivated by the teachings of Islamic extremism. Using the theoretical approach of "othering" and the minority threat perception that contributes to desires for increased social controls and levels of punitiveness among the public, this research evaluates respondents' willingness to cede their own civil liberties as well as their support for punitive policies that take away the civil liberties of the perpetrators based on the survey/stimuli respondents received. Overall, respondents were more likely to support the policy requiring ceding civil liberties, than support the punitive policy that would take away the civil liberties of the perpetrators. When factoring in survey type, respondents in general were more likely to support the punitive policy when taking the White/Far-right extremism survey and were also the most likely to support the policy requiring the public to cede their civil liberties when taking the Middle Eastern/Islamic extremism survey. The willingness to cede civil liberties increased for Black and Asian respondents with the presence of the White/Far-right extremism survey, while the willingness to cede civil liberties decreased for White respondents with the presence of the White/Far-right extremism survey. In general, conservatives were more likely to cede their civil liberties than liberals, and liberals were more likely to view counterterrorism policies as ineffective. When accounting for the effects of survey type on ideology, the results show that conservatives were the least likely to cede their civil liberties when taking the White/Far-right extremism survey, while liberals were the most likely to cede their civil liberties when taking the Middle Eastern/Islamic extremism survey.

This study aims to understand the relationship between masculinity and the endorsement of attitudes towards guns and violence and aggressive fantasies. I examine threatened masculinity and masculine gender role stress in addition to a newly developed measure, which assesses traits associated with incels, who believe that social liberalism, feminism, and more sexually active men (“Chads”) are to blame for their lack of sex with women. Incels are largely a disorganized group of men interacting online, but a few self-identifying members have been associated with a number of mass violence events in recent years. The data were constructed from an original self-report survey distributed to men aged 18 to 30 years old, the group most responsible for violence against women and mass violence. I hypothesize that men who perceive that men are losing status as a group (status threat) (1), who feel less acceptance as members of that category (acceptance threat) (2), or who exhibit incel traits (3) are more likely to (a) approve of guns, violence, and aggression, and (b) exhibit aggressive fantasies. This study’s findings support three hypotheses: status threat is positively associated with an approval of guns and violence; acceptance threat is positively associated with approval of guns, violence, and aggressive fantasies; and incel traits are positively associated with aggressive fantasies. Men who experience status or acceptance threat or share incel traits exemplify issues of toxicity present in masculinity today. Their support for gun use, violence and aggressive fantasies further show the connection between male insecurity, aggressive attitudes, and fantasizing about violence. / M.S. / This study aims to understand the relationship between masculinity and the endorsement of attitudes towards guns and violence and aggressive fantasies. I examine masculinity and feelings of threat in addition to a newly developed measure, which assesses traits associated with incels (“involuntary celibates”), who believe that social liberalism, feminism, and more sexually active men are to blame for their lack of sex with women. Incels are largely a disorganized group of men interacting online, but a few self-identifying members have been associated with a number of mass violence events in recent years. The data were constructed from a survey distributed to men aged 18 to 30 years old, the group most responsible for violence against women and mass violence. I hypothesize that men who perceive that men are losing status as a group (1), who feel less acceptance as members of that category (2), or who exhibit incel traits (3) are more likely to (a) approve of guns, violence, and aggression, and (b) exhibit aggressive fantasies. This study’s findings support three hypotheses: feelings of group status loss are positively associated with an approval of guns and violence; stress in one’s masculine gender role is positively associated with approval of guns, violence, and aggressive fantasies; and incel traits are positively associated with aggressive fantasies. Their support for gun use, violence and aggressive fantasies further show the connection between male insecurity, aggressive attitudes, and fantasizing about violence.

Acknowledged as the defining challenge of our time, economic inequality has far reaching individual and societal consequences. It negatively affects productivity, decision-making, and health outcomes on the one hand, and political stability and economic growth on the other. Increased competition for resources not allocated at the top skews available reference frames and leads to adoption of unachievable standards, generating stressful social comparisons and anxiety that may intensify inter-group conflicts. Yet, as this dissertation shows on data from surveys from across the world, many of the worse off tend to believe that the social world in general is fair and that large differences in incomes are justified and even necessary. To understand why and how are the widespread and entrenched differences in incomes and wealth not being contested at a larger scale, this dissertations links perceptions and judgments of economic inequalities to their perceived, and often misjudged, normativity. It is argued that there is a need for a greater attention and understanding of people’s beliefs about what are the popular opinions and shared values regarding political issues. It is not only that people not know of inequalities, underestimate them, or attempt to rationalize their existence as fair and deserved. It is that people also need to know that their sentiments are shared by others. Based on results of multiple experimental studies, this thesis explored and supported a possibility that people who believe that the unequal status quo is unsatisfactory and that the standing system should be challenged and changed also tend to believe that their views are not shared by the general population. Even more, such thinking tends to get reinforced when someone else is critical of the system in place. Thus, instead of rising in spirit and assuming that others will finally see at least some of the negative outcomes of the way things are, those hoping for change may get demoralized, feel isolated in their views, and may feel drawn to compromises they shouldn't need to consider. In particular, the dissertation mainly utilizes the framework of conservatism being a motivated political cognition (Jost et al., 2003) which proposes that adoption of system-legitimizing attitudes may be motivated by psychological needs to see the social world as orderly, structured, and generally just and fair. In four chapters, the dissertations explores how the conditions theorized to motivate adoption of status-legitimizing attitudes affect not only these attitudes, but also the perceptions of their normativeness. Chapter 2 presents a comprehensive test of the original reading of status-legitimacy hypothesis (Jost, Pelham, Sheldon, & Ni Sullivan, 2003) which implied that those with lower objective status are the most motivated to system-justify, and of the re-specified version (van der Toorn et al., 2015) that posits subjective powerlessness to be the driver of undue system legitimization. Presented are results of a mixed-effects analysis of ISSP data on social inequality, covering almost 50,000 respondents from 28 countries. The results from analysis testing contextual moderation lend more support for the original, rather than the revised reading of status-legitimacy hypothesis - that it is the objectively disadvantaged who may experience greater motivation to defend the system. Chapter 3 adopts Lane's (1986) perspective explaining that political institutions create more dissonance than market institutions, and tests a proposition that while political institutions will be perceived as legitimate by the members of the lower classes, market institutions will be seen as less legitimate. Second, we hypothesize that those over and under-estimating their social class should report higher or lower perceived legitimacy of the system. Analysis of data from General Social Survey (2010-2016; total n = 4142) shows that those in lower classes report higher confidence in political, but not market institutions compared to those members of the upper classes. Similarly, relative to those under- or correctly estimating their class, those over-estimating their class positioning reported higher confidence in political compared to market institutions. Chapter 4 presents two experimental studies testing, on a sample of 201 students (in Tilburg, the Netherlands), how indirect threat to the country's culture and a direct criticism of the country's economic performance influence people's perceptions of attitudinal similarity with their society in general depending on their prior ideological views. The results suggest that those with views critical of the standing socio-political system imagine their co-nationals as more attitudinally different compared to those who consider the standing system to be fair and desirable. In particular, exposure to economic threat, but not cultural threat, increased the perceived ideological distance from the presumed attitudes of the rest of the society among those critical of the system, but not among those who considered the system to be fair and desirable as it is. Chapter 5 presents data from two studies conducted before and after the 2016 US Presidential election (mTurk, n = 478), and before and after the 2017 UK general election (Prolific Academic, n = 617). Data were gathered in two rounds, utilizing the same between-subjects experimental design to assess whether ideological differences moderate how threat (economic system threat) and uncertainty (outcome uncertainty about election) influence the perceived similarity between people's personal normative attitudes (how things should be) and their estimates of socially normative attitudes (what they believe others would say should be). Furthermore, the effect of the result of the election on beliefs about the legitimacy of the standing economic system among supporters of competing political parties was assessed in two studies using within-subjects design (US n = 80; UK n = 329). The findings support the hypothesis that ideology predicts differences in perception of the generalized other when faced with system threat and that people bolster their ideological commitments following threats to their worldview in form of electoral defeat. While liberals tend to overestimate the strength of conservative values within the society in general, conservatives view others as both more conservative and liberal compared to themselves.

[pt] A pesquisa apresenta uma análise do comportamento dinâmico da barragem de rejeitos Alpamarca localizada em região sismicamente ativa no centro do Peru. Estudos de ameaça sísmica constituem um aspecto fundamental no projeto de barragens de rejeito tendo em vista os grandes prejuízos ambientais, econômicos e sociais que a ruptura da estrutura, por carregamento dinâmico, possa produzir. Nesta pesquisa foram feitos estudos probabilísticos de ameaça sísmica utilizando o software de código aberto Openquake, que inclui leis de atenuação específicas para as condições geológicas do Peru. A simulação do comportamento dinâmico da barragem demandou a geração de terremotos de projeto com base no espectro de acelerações uniformemente provável determinado na investigação de ameaça sísmica e em função da classificação da barragem em relação a níveis de risco. No trabalho também são discutidas técnicas de tratamento dos acelerogramas, com o objetivo de diminuir o esforço computacional dos cálculos no domínio do tempo, porém sem perder precisão requerida para os resultados estimados. / [en] The research presents an analysis of the dynamic behavior of the Alpamarca tailings dam located in Junín, central Peru, because of the catastrophic effects of earthquakes that frequently occur on the western coast of South America. Dam from the 4670 m elevation. Up to the elevation 4703 m. Under the sea level, with the purpose of supplying the demand for tailings generation in the mining area. The tailings dams are important structures due to the storage of contaminant residues that would shave the environment in the event of a collapse or rupture, which is indispensable to carry out studies to characterize their seismic behavior. In this research, probabilistic seismic threat studies were performed using the OpenQuake software, working with the regional seismicity and soil attenuation law of Peru. Dynamic behavior analysis was performed using the FLAC 2D software, based on the finite difference method. The simulation of the seismic behavior of the dam is made by discussing several important aspects that should be considered for a correct analysis such as the selection of the project earthquake, the filtering of high frequencies to minimize the number of elements of the mesh, the introduction of Quiet conditions, the choice of constituent models including the incorporation of hysteretic damping, among other points.

Detta examensarbete ålägger en omfattande studie riktad mot att granska de komplexiteter och utmaningar som förekommer vid utveckling av robusta och effektiva verktyg som upptäcker säkerhetsrisker i kod. Genom att bestyra en jämförande analys av redan existerande säkerhetsverktyg, och engagera sig i ett försök av att utveckla ett säkerhetsverktyg från en grundläggande nivå, strävar detta arbete efter att uppenbara de underliggande anledningarna bakom varför det, inom cybersäkerhet, ännu är en stor utmaning att ligga steget före skadliga aktörer. Inledande bidrar forskningen med en överblick av aktuella säkerhetsverktyg, och samtidigt undersöks deras effektivitet, metoder, samt de typer av sårbarheter som verktygen är designade för att upptäcka. Genom systematiska mätningar betonar studien styrkor och svagheter av säkerhetsverktygen, och samtidigt dokumenteras utvecklingsprocessen av ett nytt säkerhetsverktyg med syfte att upptäcka liknande sårbarheter som de jämförda verktygen. De bemötta utmaningarna vid utvecklande—som att behandla moderna säkerhetshot, och integrera komplexa upptäckningsalgoritmer—diskuteras för att förevisa de övertygande hinder som utvecklare påträffar. Därutöver bedöms viktigheten av att effektivt kunna upptäcka sårbarheter, och hur det kan hjälpa att bevara integritet och pålitlighet av applikationer. Examensarbetet siktar mot att bidra med viktig insyn i området cybersäkerhet, samt stödja fortsatt utveckling i mån av att mildra säkerhetshot. Sammanfattningsvis visar resultatet från denna studie att det krävs både kunskap och ambition för att utveckla ett säkerhetsverktyg från grunden, eftersom nya hot uppstår nästan varenda dag. Studien avslöjar också att skadliga aktörer är kända för att regelbundet leta efter sårbarheter i system, och är en av de ledande anledningarna till varför det är så svårt att bekämpa cyberhot. / This thesis stipulates a comprehensive study aimed at examining the complexities and challenges in developing robust and effective tools for detecting security vulnerabilities in code. By performing a comparative analysis of already existing security tools, and engaging in an attempt of developing a security tool from a foundational level, this work strives to disclose the underlying reasons as to why staying one step ahead of malicious actors remains a difficult challenge in cybersecurity. Introductory, the study provides an overview of current security tools while examining their effectiveness, methodologies, and the types of vulnerabilities they are designed to detect. Through systematic measurements, the study highlights strengths and weaknesses of the security tools while, simultaneously, documenting the process of developing a new security tool designed to detect similar vulnerabilities to the compared tools. The challenges faced during development—such as treating modern security threats, and integrating complex detection algorithms—are discussed to portray the compelling hurdles that developers encounter. Moreover, this thesis assesses the importance of effectively detecting vulnerabilities, and how it can aid in maintaining integrity and trustworthiness of applications. The thesis aims to contribute with valuable insight into the field of cybersecurity and support continued development for mitigating cyber threats. In conclusion, the outcome from this study shows that developing a security tool from a foundational level requires both knowledge and ambition, since new threats occur almost every day. The study also reveals that malicious actors are known for frequently looking for vulnerabilities in systems, making it one of the leading reasons why it is difficult to fight cyber threats.

States commit to military alliances for numerous reasons. Consensus on many variables among the states in these alliances is a key factor in why they form alliances and establish written treaties. However, not all military cooperation results in a written treaty, even when facing an external threat. This study explores the role of consensus on external threats as an explanation for why some states formalize their military cooperation in a written treaty while others do not. Using a case study comparing the Nato-alliance and the Quad-cooperation, this study uncovers how the ideological threat, coupled with shared state security interests, serves as an explanatory factor. This insight has implications at the strategic military level, helping to define common security interests among states and foster consensus on dealing with external threats, ultimately leading to the establishment of written treaties.