abstract: With the increasing complexity of computing systems and the rise in the number of risks and vulnerabilities, it is necessary to provide a scalable security situation awareness tool to assist the system administrator in protecting the critical assets, as well as managing the security state of the system. There are many methods to provide security states' analysis and management. For instance, by using a Firewall to manage the security state, and/or a graphical analysis tools such as attack graphs for analysis. Attack Graphs are powerful graphical security analysis tools as they provide a visual representation of all possible attack scenarios that an attacker may take to exploit system vulnerabilities. The attack graph's scalability, however, is a major concern for enumerating all possible attack scenarios as it is considered an NP-complete problem. There have been many research work trying to come up with a scalable solution for the attack graph. Nevertheless, non-practical attack graph based solutions have been used in practice for realtime security analysis. In this thesis, a new framework, namely 3S (Scalable Security Sates) analysis framework is proposed, which present a new approach of utilizing Software-Defined Networking (SDN)-based distributed firewall capabilities and the concept of stateful data plane to construct scalable attack graphs in near-realtime, which is a practical approach to use attack graph for realtime security decisions. The goal of the proposed work is to control reachability information between different datacenter segments to reduce the dependencies among vulnerabilities and restrict the attack graph analysis in a relative small scope. The proposed framework is based on SDN's programmable capabilities to adjust the distributed firewall policies dynamically according to security situations during the running time. It apply white-list-based security policies to limit the attacker's capability from moving or exploiting different segments by only allowing uni-directional vulnerability dependency links between segments. Specifically, several test cases will be presented with various attack scenarios and analyze how distributed firewall and stateful SDN data plan can significantly reduce the security states construction and analysis. The proposed approach proved to achieve a percentage of improvement over 61% in comparison with prior modules were SDN and distributed firewall are not in use. / Dissertation/Thesis / Masters Thesis Computer Engineering 2018

Master of Science / Department of Computing and Information Sciences / Xinming Ou / Attack graphs present a visual representation of all the potential vulnerabilities and attack paths in a network. They act as a vital security tool in finding the critical attack paths in the enterprise wide networks. Generated attack graphs for complex networks present thousands of attack paths to visualize and represent to the end user. Enhancing the visualization of attack graphs by adding user interactivity will greatly improve in analyzing attack graphs and identifying the critical attack paths in the enterprise network. The layout of the attack graph can be adjusted to represent the layout of the real world enterprise network. Adding user interactivity to attack graphs is done using Prefuse, a software framework written in Java for information visualization. Prefuse is flexible and got the ability to render large amounts of data in an efficient manner. The visualization framework for the attack graphs provides a GUI tool for interacting with attack graph. The framework is a layered architecture with two important layers, the static layer and the dynamic layer. The static layer translates the attack graph trace generated from MuLVAL into a standard graphviz dot language descriptive file. The dynamic layer translates the graphviz dot file into a graph object that can be interpreted and visualized using the prefuse software framework. Preliminary result in this work has been published in [19].

In today's digital world, cybersecurity is becoming increasingly critical. Essential services that we rely on every day such as finance, transportation, and healthcare all rely on complex networks and computer systems. As these systems and networks become larger and more complex, it becomes increasingly challenging to identify and protect against potential attacks. This thesis addresses the problem of efficiently analysing large attack graphs and prioritizing defences in the field of cybersecurity. The research question guiding this study is whether PageRank, originally designed for ranking the importance of web pages, can be extended with additional parameters to effectively analyze large vulnerability-based attack graphs. To address this question, a modified version of the PageRank algorithm is proposed, which considers additional parameters present in attack graphs such as Time-To-Compromise values. The proposed algorithm is evaluated on various attack graphs to assess its accuracy, efficiency, and scalability. The evaluation shows that the algorithm exhibits relatively short running times even for larger attack graphs, demonstrating its efficiency and scalability. The algorithm achieves a reasonably high level of accuracy when compared to an optimal defence selection, showcasing its ability to effectively identify vulnerable nodes within the attack graphs. In conclusion, this study demonstrates that PageRank is a viable alternative for the security analysis of attack graphs. The proposed algorithm shows promise in efficiently and accurately analyzing large-scale attack graphs, providing valuable insight for identifying threats and defence prioritization. / I dagens digitala värld blir cybersäkerhet allt viktigare. Viktiga tjänster som vi förlitar oss på varje dag, inom t.ex. finans, transport och hälsovård, är alla beroende av komplexa nätverk och datorsystem. I takt med att dessa system och nätverk blir större och mer komplexa blir det allt svårare att identifiera och skydda sig mot potentiella attacker. Denna uppsats studerar problemet med att effektivt analysera stora attackgrafer och prioritera försvar inom cybersäkerhet. Den forskningsfråga som styr denna studie är om PageRank, ursprungligen utformad för att rangordna webbsidor, kan utökas med ytterligare parametrar för att effektivt analysera stora attackgrafer. För att besvara denna fråga föreslås en modifierad version av PageRank-algoritmen, som beaktar ytterligare parametrar som finns i attackgrafer, såsom ”Time-To-Compromise”-värden. Den föreslagna algoritmen utvärderas på olika attackgrafer för att bedöma dess noggrannhet, effektivitet och skalbarhet. Utvärderingen visar att den föreslagna algoritmen uppvisar relativt korta körtider även för större attackgrafer, vilket visar på hög effektivitet och skalbarhet. Algoritmen uppnår en rimligt hög nivå av noggrannhet jämfört med det optimala valet av försvar, vilket visar på dess förmåga att effektivt identifiera sårbara noder inom attackgraferna. Sammanfattningsvis visar denna studie att PageRank är ett potentiellt alternativ för säkerhetsanalys av attackgrafer. Den föreslagna algoritmen visar lovande resultat när det gäller att effektivt och noggrant analysera storskaliga attackgrafer, samt erbjuda värdefull information för att identifiera hot och prioritera försvar.

It is widely accepted that modern computer networks (often presented as a heterogeneous collection of functioning organisations, applications, software, and hardware) contain vulnerabilities. This research proposes a new methodology to compute a dynamic severity cost for each state. Here a state refers to the behaviour of a system during an attack; an example of a state is where an attacker could influence the information on an application to alter the credentials. This is performed by utilising a modified variant of the Common Vulnerability Scoring System (CVSS), referred to as a Dynamic Vulnerability Scoring System (DVSS). This calculates scores of intrinsic, time-based, and ecological metrics by combining related sub-scores and modelling the problem’s parameters into a mathematical framework to develop a unique severity cost. The individual static nature of CVSS affects the scoring value, so the author has adapted a novel model to produce a DVSS metric that is more precise and efficient. In this approach, different parameters are used to compute the final scores determined from a number of parameters including network architecture, device setting, and the impact of vulnerability interactions. An attack graph (AG) is a security model representing the chains of vulnerability exploits in a network. A number of researchers have acknowledged the attack graph visual complexity and a lack of in-depth understanding. Current attack graph tools are constrained to only limited attributes or even rely on hand-generated input. The automatic formation of vulnerability information has been troublesome and vulnerability descriptions are frequently created by hand, or based on limited data. The network architectures and configurations along with the interactions between the individual vulnerabilities are considered in the method of computing the Cost using the DVSS and a dynamic cost-centric framework. A new methodology was built up to present an attack graph with a dynamic cost metric based on DVSS and also a novel methodology to estimate and represent the cost-centric approach for each host’ states was followed out. A framework is carried out on a test network, using the Nessus scanner to detect known vulnerabilities, implement these results and to build and represent the dynamic cost centric attack graph using ranking algorithms (in a standardised fashion to Mehta et al. 2006 and Kijsanayothin, 2010). However, instead of using vulnerabilities for each host, a CostRank Markov Model has developed utilising a novel cost-centric approach, thereby reducing the complexity in the attack graph and reducing the problem of visibility. An analogous parallel algorithm is developed to implement CostRank. The reason for developing a parallel CostRank Algorithm is to expedite the states ranking calculations for the increasing number of hosts and/or vulnerabilities. In the same way, the author intends to secure large scale networks that require fast and reliable computing to calculate the ranking of enormous graphs with thousands of vertices (states) and millions of arcs (representing an action to move from one state to another). In this proposed approach, the focus on a parallel CostRank computational architecture to appraise the enhancement in CostRank calculations and scalability of of the algorithm. In particular, a partitioning of input data, graph files and ranking vectors with a load balancing technique can enhance the performance and scalability of CostRank computations in parallel. A practical model of analogous CostRank parallel calculation is undertaken, resulting in a substantial decrease in calculations communication levels and in iteration time. The results are presented in an analytical approach in terms of scalability, efficiency, memory usage, speed up and input/output rates. Finally, a countermeasures model is developed to protect against network attacks by using a Dynamic Countermeasures Attack Tree (DCAT). The following scheme is used to build DCAT tree (i) using scalable parallel CostRank Algorithm to determine the critical asset, that system administrators need to protect; (ii) Track the Nessus scanner to determine the vulnerabilities associated with the asset using the dynamic cost centric framework and DVSS; (iii) Check out all published mitigations for all vulnerabilities. (iv) Assess how well the security solution mitigates those risks; (v) Assess DCAT algorithm in terms of effective security cost, probability and cost/benefit analysis to reduce the total impact of a specific vulnerability.

Information Technology (IT) is a cornerstone of our modern society and essential for governments' management of public services, economic growth and national security. Consequently, it is of importance that IT systems are kept in a dependable and secure state. Unfortunately, as modern IT systems typically are composed of numerous interconnected components, including personnel and processes that use or support it (often referred to as an enterprise architecture), this is not a simple endeavor. To make matters worse, there are malicious actors who seek to exploit vulnerabilities in the enterprise architecture to conduct unauthorized activity within it. Various models have been proposed by academia and industry to identify and mitigate vulnerabilities in enterprise architectures, however, so far none has provided a sufficiently comprehensive scope. The contribution of this thesis is a modeling framework and calculation engine that can be used as support by enterprise decision makers in regard to cyber security matters, e.g., chief information security officers. In summary, the contribution can be used to model and analyze the vulnerability of enterprise architectures, and provide mitigation suggestions based on the resulting estimates. The contribution has been tested in real-world cases and has been validated on both a component level and system level; the results of these studies show that it is adequate in terms of supporting enterprise decision making. This thesis is a composite thesis of eight papers. Paper 1 describes a method and dataset that can be used to validate the contribution described in this thesis and models similar to it. Paper 2 presents what statistical distributions that are best fit for modeling the time required to compromise computer systems. Paper 3 describes estimates on the effort required to discover novel web application vulnerabilities. Paper 4 describes estimates on the possibility of circumventing web application firewalls. Paper 5 describes a study of the time required by an attacker to obtain critical vulnerabilities and exploits for compiled software. Paper 6 presents the effectiveness of seven commonly used automated network vulnerability scanners. Paper 7 describes the ability of the signature-based intrusion detection system Snort at detecting attacks that are more novel, or older than its rule set. Finally, paper 8 describes a tool that can be used to estimate the vulnerability of enterprise architectures; this tool is founded upon the results presented in papers 1-7. / Informationsteknik (IT) är en grundsten i vårt moderna samhälle och grundläggande för staters hantering av samhällstjänster, ekonomisk tillväxt och nationell säkerhet. Det är därför av vikt att IT-system hålls i ett tillförlitligt och säkert tillstånd. Då moderna IT-system vanligen består av en mångfald av olika integrerade komponenter, inklusive människor och processer som nyttjar eller stödjer systemet (ofta benämnd organisationsövergripande arkitektur, eller enterprise architecture), är detta tyvärr ingen enkel uppgift. För att förvärra det hela så finns det även illvilliga aktörer som ämnar utnyttja sårbarheter i den organisationsövergripande arkitekturen för att utföra obehörig aktivitet inom den. Olika modeller har föreslagits av den akademiska världen och näringslivet för att identifiera samt behandla sårbarheter i organisationsövergripande arkitekturer, men det finns ännu ingen modell som är tillräckligt omfattande. Bidraget presenterat i denna avhandling är ett modelleringsramverk och en beräkningsmotor som kan användas som stöd av organisatoriska beslutsfattare med avseende på säkerhetsärenden. Sammanfattningsvis kan bidraget användas för att modellera och analysera sårbarheten av organisationsövergripande arkitekturer, samt ge förbättringsförslag baserat på dess uppskattningar. Bidraget har testats i fallstudier och validerats på både komponentnivå och systemnivå; resultaten från dessa studier visar att det är lämpligt för att stödja organisatoriskt beslutsfattande. Avhandlingen är en sammanläggningsavhandling med åtta artiklar. Artikel 1 beskriver en metod och ett dataset som kan användas för att validera avhandlingens bidrag och andra modeller likt detta. Artikel 2 presenterar vilka statistiska fördelningar som är bäst lämpade för att beskriva tiden som krävs för att kompromettera en dator. Artikel 3 beskriver uppskattningar av tiden som krävs för att upptäcka nya sårbarheter i webbapplikationer. Artikel 4 beskriver uppskattningar för möjligheten att kringgå webbapplikationsbrandväggar. Artikel 5 beskriver en studie av den tid som krävs för att en angripare skall kunna anskaffa kritiska sårbarheter och program för att utnyttja dessa för kompilerad programvara. Artikel 6 presenterar effektiviteten av sju vanligt nyttjade verktyg som används för att automatiskt identifiera sårbarheter i nätverk. Artikel 7 beskriver förmågan av det signatur-baserade intrångsdetekteringssystemet Snort att upptäcka attacker som är nyare, eller äldre, än dess regeluppsättning. Slutligen beskriver artikel 8 ett verktyg som kan användas för att uppskatta sårbarheten av organisationsövergripande arkitekturer; grunden för detta verktyg är de resultat som presenteras i artikel 1-7. / <p>QC 20140203</p>

The technological advancements in the automotive industry as well as in thefield of communication technologies done the last years have transformed thevehicles to complex machines that include not only electrical and mechanicalcomponents but also a great number of electronic components. Furthermore,modern vehicles are now connected to the Wide Area Network (WAN) and inthe near future communications will also be present between the cars (Vehicleto-Vehicle, V2V) and between cars and infrastructure (Vehicle-to-Infrastructure, V2I), something that can be found as Internet of Vehicles (IoV)in the literature. The main motivations towards all the aforementioned changesin modern vehicles are of course the improvement of road safety, the higherconvenience of the passengers, the increase in the efficiency and the higher userfriendliness.On the other hand, having vehicles connected to the Internet opens them up toa new domain of interest, this no other than the domain of cyber security. Thispractically means that while previously we were only considering cyber-attackson computational systems, now we need to start thinking about it also forvehicles. This, as a result, creates a new field of research, namely the vehicularcyber security. However, this field does not only include the possible vehicularcyber-attacks and their corresponding defenses but also the modeling andsimulation of them with the use of vehicular security analysis tools, which isalso recommended by the ENISA report titled “Cyber Security and Resilienceof smart cars: Good practices and recommendations”.Building on this need for vehicular security analysis tools, this work aims tocreate and evaluate a domain-specific, probabilistic modeling and simulationlanguage for cyber-attacks on modern connected vehicles. The language will bedesigned based on the existing threat modeling and risk management toolsecuriCAD® by foreseeti AB and more specifically based on its underlyingmechanisms for describing and probabilistically evaluating the cyber threats ofthe models.The outcome/final product of this work will be the probabilistic modeling andsimulation language for connected vehicles, called vehicleLang, that will beready for future use in the securiCAD® software. / De tekniska framstegen inom fordonsindustrin såväl som inomkommunikationsteknik som gjorts de senaste åren har omvandlat fordon tillkomplexa maskiner som inte bara omfattar elektriska och mekaniskakomponenter utan också ett stort antal elektroniska komponenter. Dessutom ärmoderna fordon nu anslutna till Internet (WAN) och inom den närmasteframtiden kommer kommunikation också att etableras mellan bilarna (Vehicleto-Vehicle, V2V) och mellan bilar och infrastruktur (Vehicle-to-Infrastructure,V2I). Detta kan också kallas fordonens internet (Internet of Vehicles - IoV) ilitteraturen. De främsta motiven för alla ovannämnda förändringar i modernafordon är förstås förbättringen av trafiksäkerheten, ökad bekvämlighet förpassagerarna, ökad effektivitet och högre användarvänlighet.Å andra sidan, att ha fordon anslutna till Internet öppnar dem för en ny domän,nämligen cybersäkerhet. Då vi tidigare bara övervägde cyberattacker påtraditionella datorsystem, måste vi nu börja tänka på det även för fordon. Dettaområde omfattar emellertid inte bara de möjliga fordonsattackerna och derasmotsvarande försvar utan även modellering och simulering av dem med hjälpav verktyg för analys av fordonssäkerhet, vilket också rekommenderas avENISA-rapporten med titeln ”Cyber Security and Resilience of smart cars: Goodpractices and recommendations”.På grund av detta behov av verktyg för fordonssäkerhetsanalys syftar dettaarbete till att skapa och utvärdera ett domänspecifikt, probabilistisktmodelleringsspråk för simulering av cyberattacker på moderna anslutna fordon.Språket har utformats utifrån det befintliga hotmodellerings- ochriskhanteringsverktyget securiCAD® av foreseeti AB och mer specifikt baseratpå dess underliggande mekanismer för att beskriva och probabilistiskt utvärderamodellernas cyberhot.Resultatet/slutprodukten av detta arbete är ett probabilistisktmodelleringsspråk för uppkopplade fordon, vehicleLang.

A (self-) adaptive system is a system that can dynamically adapt its behavior or structure during execution to "adapt" to changes to its environment or the system itself. From a security standpoint, there has been some research pertaining to (self-) adaptive systems in general but not enough care has been shown towards the adaptation itself. Security of systems can be reasoned about using threat models to discover security issues in the system. Essentially that entails abstracting away details not relevant to the security of the system in order to focus on the important aspects related to security. Threat models often enable us to reason about the security of a system quantitatively using security metrics. The structural adaptation process of a (self-) adaptive system occurs based on a reconfiguration plan, a set of steps to follow from the initial state (configuration) to the final state. Usually, the reconfiguration plan consists of multiple strategies for the structural adaptation process and each strategy consists of several steps steps with each step representing a specific configuration of the (self-) adaptive system. Different reconfiguration strategies have different security levels as each strategy consists of a different sequence configuration with different security levels. To the best of our knowledge, there exist no approaches which aim to guide the reconfiguration process in order to select the most secure available reconfiguration strategy, and the explicit security of the issues associated with the structural reconfiguration process itself has not been studied. In this work, based on an in-depth literature survey, we aim to propose several metrics to measure the security of configurations, reconfiguration strategies and reconfiguration plans based on graph-based threat models. Additionally, we have implemented a prototype to demonstrate our approach and automate the process. Finally, we have evaluated our approach based on a case study of our making. The preliminary results tend to expose certain security issues during the structural adaptation process and exhibit the effectiveness of our proposed metrics.

Cybersecurity is still one of the main challenges of the digital era for organizations and individuals alike. Threat modeling is an important tool for building systems that are reliable and secure. The research question for this study is to create a domain specific language (DSL) with the Meta Attack Language (MAL), STRIDE and DREAD. One of the main challenges is to choose a DSL that is suitable for threat modeling. The purpose of the study is to provide people with threat modeling with additional tools that can be used in attack simulations. MAL is a meta language used for creating DSL that can be used for attack simulations. An example of a MAL project that usually serves as a template for other DSL is coreLang, which models the general IT infrastructure. STRIDE is a model used in threat modeling to enumerate and categorization of cyberthreats. DREAD is a model used for risk assessment that scores each threat by a value between one and ten. The proposed method for answering the research question is the Design Research Science Method (DRSM), which is often used for creating artifacts. Evaluation of the results is done with tests written in Java using the Junit framework. The result of the study is the creation of strideLang that maps attack steps in coreLang (MAL implementation of the general IT infrastructure DSL) to STRIDE and DREAD models. The primary source of error in the investigation is the risk assessment with DREAD, which can be somewhat inaccurate depending on what specific DSL is used. It would have been valuable if the study incorporated feedback from domain experts specifically with risk assessment. The nature of the STRIDE and DREAD models is that the models are very subjective in practice. However, this study does provide insights in how a DSL can be created based on DREAD and STRIDE. Future work might investigate a different DSL, incorporate tools such as SecuriCAD and compare different threat models. / Cybersäkerhet är fortfarande en av de främsta utmaningarna i den digitala eran för såväl organisationer som individer. Hotmodellering är ett viktigt verktyg för att bygga tillförlitliga och säkra system. Huvudmålet för denna studie är att skapa ett domänspecifikt språk (DSL) med Meta Attack Language (MAL), STRIDE och DREAD. En av de främsta utmaningarna för att nå målet med studien är att hitta ett domänspecifikt språk som är lämpligt för denna typ av hotmodellering. Syftet med studien är att förse personer som arbetar med hotmodellering med ytterligare verktyg för att kunna använda i sina attacksimuleringar. MAL är ett metaspråk som används för att skapa domän-specifika språk och utföra attacksimuleringar. Ett exempel på ett MAL projekt som oftast används som en mall för att skapa nya domänspecifika och modellerar den generella IT infrastrukturen. STRIDE modellen används för att lista och kategorisera digitala hot. DREAD brukar användas tillsammans med STRIDE och används för att risk bedöma digitala hot genom att betygsätta hoten med ett värde mellan ett och tio. Den valda metoden för att lösa forskningsfrågan är Design Research Science Method (DSRM), som används oftast i samband med skapandet av artefakter. Evaluering av resultatet gjordes med tester skrivna i Java med ramverket JUnit. Studien resulterade med skapande av strideLang som mappar attack steg i coreLang till STRIDE och DREAD modellerna. Den främsta felkällan i denna studie är riskbedömningen med DREAD eftersom noggrannheten på riskbedömningen kan variera från specifika domän i IT infrastrukturen. Det hade varit värdefullt om studien integrera domänexperters bedömning i studien främst för DREAD bedömningen. STRIDE och DREAD modellerna är subjektiva vilket betyder att olika experter kan komma till olika slutsatser för samma hot. Däremot så kan studien förse med intressanta insikter om hur ett domän-specifikt språk kan skapas baserat på DREAD och STRIDE modellerna. Framtida studier kan undersöka en mer specifik domän inom IT infrastrukturen, integrera verktyg som SecuriCAD och jämföra olika modeller som används inom hotmodelleringen

Attack simulations provide a viable means to test the cyber security of a system. The simulations trace the steps taken by the attacker to compromise sensitive assets within the system. In addition to this, they can also estimate the time taken by the attacker for the same, measuring from the initial step up to the final. One common approach to implement such simulations is the use of attack graph, which trace the various dependencies of every step and their connection to one another in a formal way. To further facilitate attack simulations and to reduce the effort of creating new attack graphs for each system of a given type, domain-specific languages are employed. Another advantage of utilizing such a language is that they organize the common attack logics of the domain in a systematic way, allowing for both ease of use and reuse of models. MAL (the Meta Attack Language) has been proposed by Johnson et al. to serve as a framework to develop domain-specific languages [1]. My work is based upon the same. This thesis report presents AWSLang, which can be used to design IT system models in context to the AWS (Amazon Web Services) environment and analyse their weaknesses. The domain specifics of the language are inspired from and based on existing literature. A Systematic Literature Review (SLR) is performed to identify possible attacks against the elements in an AWS environment. These attacks are then used as groundwork to write test cases and validate the specification. / Attacksimuleringar är ett användbart sätt att testa cybersäkerheten i ett system. Simuleringarna spårar de steg som angriparen tog för att försvaga säkerheten av känsliga tillgångar inom systemet. Utöver detta kan de uppskatta hur länge attacken varade, mätt från första till sista steget. Ett gemensamt tillvägagångssätt för att implementera sådana simuleringar är användningen av attackgrafer, som spårar olika beroenden av varje steg och deras koppling till varandra på ett formellt sätt.För att ytterligare underlätta attacksimuleringar och minska ansträngningen att skapa nya attackgrafer för varje system av en given typ, används domänspecifika språk. En annan fördel med att använda ett sådant språk är att det organiserar domänens gemensamma attacklogiker på ett systematiskt sätt, vilket möjliggör både en enkel användning och återanvändning av modeller. MAL (Meta Attack Language) har föreslagits av Johnson et al. att fungera som ramverk för utvecklingen av domänspecifika språk [1]. Mitt arbete är baserat på detsamma.I denna uppsats presenteras AWSLang, som kan användas för att utforma IT-systemmodeller i kontexten av AWS-miljön (Amazon Web Services) och analysera deras svagheter. Språkets domänspecifikationer är inspirerade av och baserade på befintlig litteratur. En systematisk litteraturöversikt görs för att identifiera möjliga attacker mot elementen i en AWS-miljö. Dessa attacker används sedan som grund för att skriva testfall och validera specifikationen.

Cyber-attack simulation is a suitable method used for assessing the security ofnetwork systems. An attack simulation advances step-wise from a certain systementry-point to explore the attack paths that lead to dierent weaknesses inthe model. Each step is analyzed, and the time to compromise is calculated.Attack simulations are primarily based on attack graphs. The graphs areemployed to model attack steps where nodes can represent assets in the system,and edges can represent the attack steps. To reduce the computational cost associatedwith building an attack graph for each specic system, domain-specicattack languages, or DSL for short, are used.The nal product of this thesis work is azureLang, a probabilistic modelingand simulation language for modeling Microsoft Azure cloud infrastructure.AzureLang is a DSL which denes a generic attack logic for MicrosoftAzure systems. Using azureLang, system administrators can easily instantiatespecic-system scenarios which emulate their Microsoft Azure cloud system infrastructure.After creating the model, attack simulation can be run to assessthe security of the model. / Cyberattacksimulering är en lämplig metod som används för att bedöma säkerhetenhos nätverkssystem. En angrepsimulering går stegvis från ett visst systeminmatningspunkt för att utforska angreppsbanorna som leder till olika svagheter i modellen. Varje steg analyseras och tiden för kompromettera beräknas.Attack-simuleringar baseras huvudsakligen på attackgrafer. Graferna används för att modellera angreppssteg där noder kan representera tillgångar i systemet, och kanterna kan representera attackenstegen. För att minska kostnaden för att skapa attackgrafer för varje specifikt system används domänspecifika språk eller DSL förkortat.Den slutliga produkten av detta examensarbete är azureLang, ett probabilistisk hotmodelleringsoch attacksimuleringsspråk för analys av Microsoft Azure Cloud Infrastructure. AzureLang är en DSL som definierar en generisk attacklogik för Microsoft Azure-system. Med hjälp av azureLang kan systemadministratörer enkelt ordna specifika systemscenarier som efterliknar deras Microsoft Azure cloudsystem infrastruktur. Efter att ha skapat modellen kan attack simu-lering köras för att bedöma modellens säkerhet.