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The increasing dependence on digital infrastructure leaves individuals, societies and even nations vulnerable in the case of a cyberattack. To prepare for threats and attacks, cyberattacks be simulated in environments called cyber ranges. CYBER RANGE AND TRAINING ENVIRONMENT (CRATE), Sweden's cyber range, is an example of such an environment. This environment is sophisticated and complex, but challenges remain for the operatives in how to interpret the multitude of information items that are produced during a simulation. An emerging field of study is the study of situational awareness in the cyber domain, which describes how an operative can render an accurate mental picture, which enables for quick assessment and decision-making in a situation where a multitude of data or information items are involved. An integral part of situational awareness is effective visualization. Visualization can form the linkage in the human-computer interaction and has been demonstrated in other industries and fields to facilitate situational awareness. However, the linkage between situational awareness and visualization in the unique context of a cyber range was a new topic of study. This thesis aim was to provide insight and advance the knowledge of visualization for situational awareness in the unique context of the cyber range CRATE. Conclusively, in the development of a visualization software, the abstraction levels and time frame of the information items collected should be considered. Each information item is of different relevance depending on both the operative's role and in which time frame through which the information is analyzed. A visualization technique that recognizes the abstraction level and the time frame increases the situational awareness for the operative conducting the simulation because it renders both an estimation of critical core processes, current events that are unfolding and enables for the future projection of events.

The data generated by interconnected technologies has to be protected. Passwords are used to protect many different systems and are considered an essential part of cybersecurity. The system often permits the user to select their password, where the user becomes partly responsible for the security. Selecting a predictable, common, or easily guessed password is considered a human error that affects the security of the system. Security mechanisms are often enforced by websites to try to prevent users from creating weak passwords. However, predictable and weak passwords are still used. This study examines the security and usability of password user interfaces with a qualitative approach including a systematic literature review, where the data is analysed with thematic analysis and evaluation of websites with usability testing. The objective is to provide security and usability recommendations based on previous research and users' opinions. The result identifies successful criteria features, feedback features, and usability features that can be implemented in the user interface. In addition, the usability testing results discover usability issues present on commonly used websites. The study concludes that seven security and usability features are necessary in the password user interface when the aim is to encourage users to create secure passwords.

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Cybersecurity is an emerging subject in the public policy field in Sweden and the European Union. Part of public policy is the underlying ideas that create different approaches and instruments in the policy work. This study aim to answer which underlying ideas are present in writs from the Swedish executive government and the European Commission. The method in use is an comparative descriptive idea analysis. The analytical framework consists of three different dimensions that conceptualize threat, accountable actor and policy-instruments regarding cybersecurity. The studie shows that the commission and the Swedish executive government have similar ideas concerning the accountable actor which is public actors. However, concerning threat and policy-instruments the ideas differ. The idea of threats to cybersecurity is individual actors according to the European Commission while the Swedish executive government defines states as the threat. Concerning policy-instruments the European Commission appears to have a more regulative perspective.

Cyber threat modeling and attack simulations arenew methods to assess and analyze the cybersecurity of ITenvironments. The Meta Attack Language (MAL) was createdto formalize the underlying attack logic of such simulationsby providing a framework to create domain specific languages(DSLs). DSLs can be used in conjunction with modeling softwareto simulate cyber attacks. The goal of this project was to examinehow MAL can be integrated in a wider cybersecurity context bydirectly combining attack simulation results with other tools inthe cybersecurity ecosystem. The result was a proof of conceptwhere a small DSL is created for Amazon EC2. Informationis gathered about a certain EC2 instance and used to create amodel and run an attack simulation. The resulting attack pathwas used to perform an offensive measure in Pacu, an AWSexploitation framework. The result was examined to arrive atconclusions about the proof of concept itself and about integratingMAL in the cybersecurity ecosystem in a more general sense. Itwas found that while the project was successful in showing thatintegrating MAL results in such manner is possible, the CADmodeling process is not an optimal route and that other domainsthan the cloud environment could be targeted. / Cyberhotsmodellering och attacksimuleringar är nya metoder för att bedöma och analysera cybersäkerheten i en IT-miljö. Meta Attack Language (MAL) skapades för att formalisera den underliggande attacklogiken för sådana simuleringar genom att tillhandahålla ett ramverk för att skapa domain-specific languages (DSL). En DSL kan användas tillsammans med modelleringsprogramvara för att simulera cyberattacker. Målet med detta projekt var att undersöka hur MAL kan integreras i ett bredare sammanhang genom att direkt kombinera MAL-resultat med andra verktyg inom IT-säkerhet. Resultatet blev ett koncepttest där en mindre DSL skapades för Amazon EC2. Information samlades in om en viss EC2-instans och användes för att skapa en modell och genomföra en attacksimulering. Den resulterande attackvägen användes för att utföra en offensiv åtgärd i Pacu, ett ramverk för AWS-exploatering. Resultatet undersöktes för att nå slutsatser om konceptet i sig och om att integrera MAL i IT-säkerhetens ekosystem i allmänhet. Det visade sig att även om projektet lyckades visa att det är möjligt att integrera MAL-resultat på ett sådant sätt, är CAD-modelleringsprocessen inte en optimal metodik och lämpar sig illa för syftet. Det visade sig också att andra domäner än molnmiljön skulle vara en givande riktning. / Kandidatexjobb i elektroteknik 2022, KTH, Stockholm

The maritime industry is growing more and more for every year that passes. As the industry grows it also becomes a more attractive target for cyber criminals. The amount ofcyberattacks in the industry are few, but it is growing at an alarming rate. This literaturestudy identifies the most common datacom systems and infrastructure in the maritimeindustry and their vulnerabilities. This paper also identifies possible solutions and improvements that can be made to existing datacom systems to make them less susceptible tocyber attacks. The results show that there are many solutions that could be implementedthat would increase the cyber security in the industry, but many of them require international cooperation to implement. Therefore standards are suggested to be implemented inorder to push organisations to update their systems. Additionally, this paper delves intothe aviation industry to examine how the datacom infrastructure utilized in the maritimeindustry could be adopted to enhance both efficiency and security

Power systems constitute a pillar of the critical infrastructure and, as a result, their cybersecurity is paramount. Traditional power system architectures are moving from their original centralized nature to a distributed paradigm. This transition has been propelled by the rapid penetration of distributed energy resources (DERs) such as rooftop solar panels, battery storage, etc. However, with the introduction of new DER devices, technologies, and operation models, the threat surface of power systems is inadvertently expanding. This dissertation provides a comprehensive overview of the cybersecurity landscape of DER-enabled power systems outlining potential attack entry points, system vulnerabilities, and the corresponding cyberattack impacts. Cyber-physical energy systems (CPES) testbeds are crucial tools to study power systems and perform vulnerability analyses, test security defenses, and evaluate the impact of cyberattacks in a controlled manner without impacting the actual electric grid. This work also attempts to provide bottom-up security solutions to secure power systems from their lowest abstraction layer, i.e., hardware. Specifically, custom-built hardware performance counters (HPCs) are proposed for the detection of malicious firmware, e.g., malware, within DER inverter controllers. The experimental results prove that HPCs are an effective host-based defense and can accurately identify malicious firmware with minimum performance overheads. Also, methodologies to secure communication protocols and ensure the nominal operation of DER devices using physics-informed schemes are presented. First, DERauth, a battery-based secure authentication primitive that can be used to enhance the security of DER communication, is proposed and evaluated in a CPES testbed. Then, a physics-based attack detection scheme that leverages system measurements to construct models of autonomous DER agents is presented. These measurement-based models are then used to discern between nominal and malicious DER behavior. The dissertation concludes by discussing how the proposed defense mechanisms can be used synergistically in an automated framework for grid islanding to improve power system security and resilience, before it provides prospective directions for future research.

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The great advance of communication technology comes with a rapid increase of disinformation in many kinds and shapes; manipulated images are one of the primary examples of disinformation that can affect many users. Such activity can severely impact public behavior, attitude, and belief or sway the viewers' perception in any malicious or benign direction. Additionally, adversarial attacks targeting deep learning models pose a severe risk to computer vision applications. This dissertation explores ways of detecting and resisting manipulated or adversarial attack images. The first contribution evaluates perceptual hashing (pHash) algorithms for detecting image manipulation on social media platforms like Facebook and Twitter. The study demonstrates the differences in image processing between the two platforms and proposes a new approach to find the optimal detection threshold for each algorithm. The next contribution develops a new pHash authentication to detect fake imagery on social media networks, using a self-supervised learning framework and contrastive loss. In addition, a fake image sample generator is developed to cover three major image manipulating operations (copy-move, splicing, removal). The proposed authentication technique outperforms the state-of-the-art pHash methods. The third contribution addresses the challenges of adversarial attacks to deep learning models. A new adversarial-aware deep learning system is proposed using a classical machine learning model as the secondary verification system to complement the primary deep learning model in image classification. The proposed approach outperforms current state-of-the-art adversarial defense systems. Finally, the fourth contribution fuses big data from Extra-Military resources to support military decision-making. The study proposes a workflow, reviews data availability, security, privacy, and integrity challenges, and suggests solutions. A demonstration of the proposed image authentication is introduced to prevent wrong decisions and increase integrity. Overall, the dissertation provides practical solutions for detecting manipulated and adversarial attack images and integrates our proposed solutions in supporting military decision-making workflow.