The diploma thesis is focused on the design implementation of information security management system in a small business and is applying theoretical knowledge to real-life situations in a manufacturing company. First of all is performed analysis of current status and the consequent threats which can affect the company's assets. Thereafter are proposed measures based on identified risks and requirements of the owner.

Cloud computing allows on-demand provision, configuration and assignment of computing resources with minimum cost and effort for users and administrators. Managing the physical infrastructure that underlies cloud computing services relies on the need to provision and manage bare-metal computer hardware. Hence there is a need for quick loading of operating systems in bare-metal and virtual machines to service the demands of users. The focus of the study is on developing a technique to load these machines remotely, which is complicated by the fact that the machines can be present in different Ethernet broadcast domains, physically distant from the provisioning server. The use of available bare-metal provisioning frameworks require significant skills and time. Moreover, there is no easily implementable standard method of booting across separate and different Ethernet broadcast domains. This study proposes a new framework to provision bare-metal hardware remotely using layer 2 services in a secure manner. This framework is a composition of existing tools that can be assembled to build the framework.

This report describes a study aimed at uncovering flaws and finding potential improvements from when the modelling tool EAAT is used in conjunction with the modelling language CySeMoL. The study was performed by developing a framework and applying it on CySeMoL and EAAT in real life context networks. The framework was developed in order to increase the number of flaws uncovered as well as gather potential improvements to both EAAT and CySeMoL. The basis of the framework is a modified version of the Quality in use model from ISO/IEC 25010:2011 standard. Upon the characteristics and sub characteristics of this modified model different values for measuring usability where attached. The purpose of these values is to measure usability from the perspectives of both creating and interpreting models. Furthermore these values are based on several different sources on how to measure usability. The complete contents of the framework and the underlying ideas, upon which the framework is based, are presented in this report. The framework in this study was designed in order to enable it to be used universally with any modelling language in conjunction with a modelling tool. Its design is also not limited to the field of computer security and computer networks, although that is the intended context of CySeMoL as well as the context described in this report. However, utilization outside the intended area of usage will most likely require some modifications, in order to work in a fully satisfying. Several flaws where uncovered regarding the usability of CySeMoL and EAAT, but this is also accompanied by several recommendations on how to improve both CySeMoL and EAAT. Because of the outline of the framework, the most severe flaws have been identified and recommendations on how to rectify these shortcomings have been suggested.

Detta examensarbete är en utvärdering av nätverkssäkerheten hos J BiL AB, både på social och teknisk nivå. Företaget är beroende av säkra Internet-anslutningar för att nå externa tjänster och interna servrar lokaliserade på olika geografiska platser. Företaget har ingen IT-ansvarig som aktivt underhåller och övervakar nätverket, utan konsulterar ett externt dataföretag. Syftet med examensarbetet är att utvärdera säkerheten, upptäcka brister, ge förbättringsförslag och till viss del implementera lösningar. För att undersöka säkerheten har observationer och intervjuer med personalen gjorts och ett flertal attacker mot nätverket har utförts. Utifrån den data som samlats in kunde slutsatsen dras att företaget har brister vad gäller IT-säkerheten. Framförallt den sociala säkerheten visade sig ha stora luckor vilket till stor del beror på att de anställda varken har blivit utbildade eller fått någon information om hur de ska hantera lösenord, datorer och IT-frågor i allmänt. Förbättringsförslag har getts och viss implementation har genomförts för att eliminera bristerna. De anställda har även med hjälp av en IT-policy och föreläsning blivit utbildade i hur de ska agera och tänka kring IT-relaterade säkerhetsfrågor. / The aim of this project is to evaluate the network security at J Bil AB. The focus will be on both social and technical issues. For the employees to be able to con-nect to remote servers and external services and perform their daily work tasks, secure connections is needed. J Bil Ab has no IT manager who actively maintains and monitors the network; rather they consult a computer company when changes and implementations are required. The projects’ goal is to identify gaps, come up with suggestions for improvement and to some extent implement so-lutions. To do this, an observation of the employees hav been made, an inter-view have been held, and several attacks on the network have been performed. Based on the data collected, it was concluded that the company has shortcom-ings in IT security. Above all, the social security appeared to have major gaps in it and that is mainly because the lack of knowledge among the employees and they have never been informed of how to manage their passwords, computers and IT issues in general. Suggestions for improvement have been given and some implementations have been performed to eliminate the deficiencies.

A growing problem in network security stems from the fact that both attack methods and target systems constantly evolve. This problem makes it difficult for human operators to keep up and manage the security problem. To deal with this challenge, a promising approach is to use reinforcement learning to adapt security policies to a changing environment. However, a drawback of this approach is that traditional reinforcement learning methods require a large amount of data in order to learn effective policies, which can be both costly and difficult to obtain. To address this problem, this thesis investigates ways to incorporate prior knowledge in learning systems for network security. Our goal is to be able to learn security policies with less data compared to traditional reinforcement learning algorithms. To investigate this question, we take a Bayesian approach and consider Bayesian reinforcement learning methods as a complement to current algorithms in reinforcement learning. Specifically, in this work, we study the following algorithms: Bayesian Q-learning, Bayesian REINFORCE, and Bayesian Actor-Critic. To evaluate our approach, we have implemented the mentioned algorithms and techniques and applied them to different simulation scenarios of intrusion prevention. Our results demonstrate that the Bayesian reinforcement learning algorithms are able to learn more efficiently compared to their non-Bayesian counterparts but that the Bayesian approach is more computationally demanding. Further, we find that the choice of prior and the kernel function have a large impact on the performance of the algorithms. / Ett växande problem inom cybersäkerhet är att både attackmetoder samt system är i en konstant förändring och utveckling: å ena sidan så blir attackmetoder mer och mer sofistikerade, och å andra sidan så utvecklas system via innovationer samt uppgraderingar. Detta problem gör det svårt för mänskliga operatörer att hantera säkerhetsproblemet. En lovande metod för att hantera denna utmaning är förstärkningslärande. Med förstärkningslärande kan en autonom agent automatiskt lära sig att anpassa säkerhetsstrategier till en föränderlig miljö. En utmaning med detta tillvägagångsätt är dock att traditionella förstärkningsinlärningsmetoder kräver en stor mängd data för att lära sig effektiva strategier, vilket kan vara både kostsamt och svårt att erskaffa. För att lösa detta problem så undersöker denna avhandling Bayesiska metoder för att inkorporera förkunskaper i inlärningsalgoritmen, vilket kan möjliggöra lärande med mindre data. Specifikt så studerar vi följande Bayesiska algoritmer: Bayesian Q-learning, Bayesian REINFORCE och Bayesian Actor- Critic. För att utvärdera vårt tillvägagångssätt har vi implementerat de nämnda algoritmerna och utvärderat deras prestanda i olika simuleringsscenarier för intrångsförebyggande samt analyserat deras komplexitet. Våra resultat visar att de Bayesiska förstärkningsinlärningsalgoritmerna kan användas för att lära sig strategier med mindre data än vad som kravs vid användande av icke-Bayesiska motsvarigheter, men att den Bayesiska metoden är mer beräkningskrävande. Vidare finner vi att metoden för att inkorporera förkunskap i inlärningsalgoritmen, samt val av kernelfunktion, har stor inverkan på algoritmernas prestanda.

Les cyber-attaques pourraient engendrer des pertes qui sont de plus en plus importantes pour les utilisateurs finaux et les fournisseurs de service. Ces attaques sont, en outre, élevées par une myriade des ressources infectées et comptent surtout sur les réseaux pour être contrôlées, se propager ou endommager. Face à ces risques, il y a un besoin essentiel qui se manifeste dans la réponse à ces nombreuses attaques par des stratégies de défense efficaces. Malgré les multitudes efforts dévouées pour mettre en œuvre des techniques de défense complètes afin de se protéger contre les attaques réseaux; les approches proposées n’ont pas parvenus à satisfaire toutes les exigences. Les stratégies de défense impliquent un processus de détection complété par des actions de mitigation. Parallèlement à l’importance accordée à la conception des stratégies de détection, il est essentiel de fermer la boucle de sécurité avec des techniques efficaces permettant d’atténuer les impacts des différentes attaques. Dans cette thèse, nous proposons une technique pour réagir aux attaques qui abusent les ressources du réseau, par exemple, DDoS, botnet, distribution des vers, etc. La technique proposée s’appuie sur des approches de gestion du trafic et utilise le standard Multiprotocol Label Switching (MPLS) pour gérer le trafic diagnostiqué comme abusant du réseau, tout en invoquant les processus de détection. Les objectifs de notre technique peuvent être résumés comme suit: d’une part, fournir les moyens — par la qualité de service et schémas de routage — à séparer les flux suspects des légitimes, et d’autre part de prendre le contrôle des flux suspects. Nous bénéficions de l’extension du MPLS au niveau d’inter-domaine pour permettre une coopération entre les fournisseurs, permettant par suite la construction d’un mécanisme de défense à grande échelle. Nous développons un système afin de compléter les aspects de gestion de la technique proposée. Ce système effectue plusieurs tâches telles que l’extraction de données d’alerte, l’adaptation de la stratégie et la configuration des équipements. Nous modélisons le système en utilisant une approche de regroupement et un langage de politiques de sécurité afin de gérer de manière cohérente et automatique le contexte et l’environnement dans lequel la technique de mitigation est exécutée. Enfin, nous montrons l’applicabilité de la technique et du système à travers des différentes simulations tout en évaluant la qualité de service dans des réseaux MPLS. L’application de la technique a démontré son efficacité dans non seulement la mitigation des impacts des attaques mais aussi dans l’offre des avantages financiers aux acteurs de la chaîne de sécurité, à savoir les fournisseurs de service / Cyber attacks cause considerable losses not only for end-users but also service providers. They are fostered by myriad of infected resources and mostly rely on network resources for whether propagating, controlling or damaging. There is an essential need to address these numerous attacks by efficient defence strategies. Researchers have dedicated large resources without reaching a comprehensive method to protect from network attacks. Defence strategies involve first a detection process, completed by mitigation actions. Research on detection is more active than on mitigation. Yet, it is crucial to close the security loop with efficient technique to mitigate counter attacks and their effects. In this thesis, we propose a novel technique to react to attacks that misuse network resources, e.g., DDoS, Botnet, worm spreading, etc. Our technique is built upon network traffic management techniques. We use the Multiprotocol Label Switching (MPLS) technology to manage the traffic diagnosed to be part of a network misuse by detection processes. The goals of our technique can be summarized as follows: first to provide the means — via QoS and routing schemes — to segregate the suspicious flows from the legitimate traffic; and second, to take control over suspicious flows. We profit from the enhancement on the inter-domain MPLS to permit a cooperation among providers building a large-scale defence mechanism. We develop a system to complete the management aspects of the proposed technique. This system performs tasks such as alert data extraction, strategy adaptation and equipments configurations. We model the system using a clustering method and a policy language in order to consistently and automatically manage the mitigation context and environment in which the proposed technique is running. Finally, we show the applicability of the technique and the system through simulation. We evaluate and analyse the QoS and financial impacts inside MPLS networks. The application of the technique demonstrates its effectiveness and reliability in not only alleviating attacks but also providing financial benefits for the different players in the mitigation chain, i.e., service providers

Nous abordons des problèmes de sécurité dans des systèmes cyber-physiques industriels. Les attaques contre ces systèmes doivent être traitées à la fois en matière de sûreté et de sécurité. Les technologies de contrôles imposés par les normes industrielles, couvrent déjà la sûreté. Cependant, du point de vue de la sécurité, la littérature a prouvé que l’utilisation de techniques cyber pour traiter la sécurité de ces systèmes n’est pas suffisante, car les actions physiques malveillantes seront ignorées. Pour cette raison, on a besoin de mécanismes pour protéger les deux couches à la fois. Certains auteurs ont traité des attaques de rejeu et d’intégrité en utilisant une attestation physique, p. ex., le tatouage des paramètres physiques du système. Néanmoins, ces détecteurs fonctionnent correctement uniquement si les adversaires n’ont pas assez de connaissances pour tromper les deux couches. Cette thèse porte sur les limites mentionnées ci-dessus. Nous commençons en testant l’efficacité d’un détecteur qui utilise une signature stationnaire afin de détecter des actions malveillantes. Nous montrons que ce détecteur est incapable d’identifier les adversaires cyber-physiques qui tentent de connaître la dynamique du système. Nous analysons son ratio de détection sous la présence de nouveaux adversaires capables de déduire la dynamique du système. Nous revisitons le design original, en utilisant une signature non stationnaire, afin de gérer les adversaires visant à échapper à la détection. Nous proposons également une nouvelle approche qui combine des stratégies de contrôle et de communication. Toutes les solutions son validées à l’aide de simulations et maquettes d’entraînement / We address security issues in cyber-physical industrial systems. Attacks against these systems shall be handled both in terms of safety and security. Control technologies imposed by industrial standards already cover the safety dimension. From a security standpoint, the literature has shown that using only cyber information to handle the security of cyber-physical systems is not enough, since physical malicious actions are ignored. For this reason, cyber-physical systems have to be protected from threats to their cyber and physical layers. Some authors handle the attacks by using physical attestations of the underlying processes, f.i., physical watermarking to ensure the truthfulness of the process. However, these detectors work properly only if the adversaries do not have enough knowledge to mislead crosslayer data. This thesis focuses on the aforementioned limitations. It starts by testing the effectiveness of a stationary watermark-based fault detector, to detect, as well, malicious actions produced by adversaries. We show that the stationary watermark-based detector is unable to identify cyber-physical adversaries. We show that the approach only detects adversaries that do not attempt to get any knowledge about the system dynamics. We analyze the detection performance of the original design under the presence of adversaries that infer the system dynamics to evade detection. We revisit the original design, using a non-stationary watermark-based design, to handle those adversaries. We also propose a novel approach that combines control and communication strategies. We validate our solutions using numeric simulations and training cyber-physical testbeds

<p><em>Imbulgoda Liyangahawatte, Gihan Janith Mendis Ph.D., Purdue University, May</em></p> <p><em>2023. Deep learning for securing critical infrastructure with the emphasis on power</em></p> <p><em>systems and wireless communication. Major Professor: Dr. Jin Kocsis.</em></p> <p><br></p> <p><em>Critical infrastructures, such as power systems and communication</em></p> <p><em>infrastructures, are of paramount importance to the welfare and prosperity of</em></p> <p><em>modern societies. Therefore, critical infrastructures have a high vulnerability to</em></p> <p><em>attacks from adverse parties. Subsequent to the advancement of cyber technologies,</em></p> <p><em>such as information technology, embedded systems, high-speed connectivity, and</em></p> <p><em>real-time data processing, the physical processes of critical infrastructures are often</em></p> <p><em>monitored and controlled through cyber systems. Therefore, modern critical</em></p> <p><em>infrastructures are often viewed as cyber-physical systems (CPSs). Incorporating</em></p> <p><em>cyber elements into physical processes increases efficiency and control. However, it</em></p> <p><em>also increases the vulnerability of the systems to potential cybersecurity threats. In</em></p> <p><em>addition to cyber-level attacks, attacks on the cyber-physical interface, such as the</em></p> <p><em>corruption of sensing data to manipulate physical operations, can exploit</em></p> <p><em>vulnerabilities in CPSs. Research on data-driven security methods for such attacks,</em></p> <p><em>focusing on applications related to electrical power and wireless communication</em></p> <p><em>critical infrastructure CPSs, are presented in this dissertation. As security methods</em></p> <p><em>for electrical power systems, deep learning approaches were proposed to detect</em></p> <p><em>adversarial sensor signals targeting smart grids and more electric aircraft.</em></p> <p><em>Considering the security of wireless communication systems, deep learning solutions</em></p> <p><em>were proposed as an intelligent spectrum sensing approach and as a primary user</em></p> <p><em>emulation (PUE) attacks detection method on the wideband spectrum. The recent</em></p> <p><em>abundance of micro-UASs can enable the use of weaponized micro-UASs to conduct</em></p> <p><em>physical attacks on critical infrastructures. As a solution for this, the radio</em></p> <p><em>frequency (RF) signal-analyzing deep learning method developed for spectrum</em></p> <p><em>sensing was adopted to realize an intelligent radar system for micro-UAS detection.</em></p> <p><em>This intelligent radar can be used to provide protection against micro-UAS-based</em></p> <p><em>physical attacks on critical infrastructures.</em></p>

<p> As cyber threats become highly damaging and complex, a new cybersecurity compliance certification model has been developed by the Department of Defense (DoD) to secure its Defense Industrial Base (DIB), and communication with its private partners. These partners or contractors are obligated by the Defense Federal Acquisition Regulations (DFARS) to be compliant with the latest standards in computer and data security. The Cybersecurity Maturity Model Certification (CMMC), and it is built upon existing DFARS 252.204-7012 and the NIST SP 800-171 controls. As of 2020, the DoD has incorporated DFARS and the National Institute of Standards and Technology (NIST) recommended security practices into what is now the CMMC. This thesis examines the most commonly identified security control deficiencies faced, the attacks mitigated by addressing these deficiencies, and suggested remediations, to 127 DoD contractors in order to bring them into compliance with the CMMC guidelines. By working with a compliance service provider, an analysis is done on how companies are undergoing and implementing important changes in their processes, to protect crucial information from ever-growing and looming cyber threats. </p>

The global Covid-19 pandemic have led to a lot of people working remote, the number of attacks on organizations also increased with teleworking, which means that organizations need to secure their networks to telework safely. The study examines how IT managers at small and medium-sized enterprises (SMEs) communicate to their end users about new and changed threats in telework, how the IT-responsible guide end users on how to work safely in telework and what other methods have been implemented to secure teleworking. The study was carried out by examining previous literature in the field to compile an interview guide with relevant questions. The study had a qualitative approach where semi-structured interviews were used to collect the empirical data, after which the data was thematically analyzed. The result from the study shows that IT managers used a lot of emails and referred to their intranet to inform their end users about new and changed threats, but also used meetings and seminars to inform end users. To guide end users when working remotely the IT managers implemented policies on what they could and couldn’t do. There were also guides to show end users how they should work properly. Additional key aspects were to educate their end users and to offer the end users IT support with eventual problems with help from a service desk.  The study contributes with a deeper understanding of the various methods and solutions that the IT managers at SME have implemented. Based on the results of the study, the following recommendations were given to small and medium-sized companies: To implement multifactor authentication and that all devices must have updated antivirus and secure remote access to local resources. You should also get a service that enables digital communication and document sharing. Additional recommendations were to inform end users about new and changing threats using intranets, emails or additional mediation methods. Implement policies and guides that guide end users around how to work safely and what they may and may not do while teleworking. Final recommendations are to educate end users to recognize common threats such as phishing by e-mail and to provide IT support to end users with the help of a service desk. As well as providing end users with the hardware that they need for teleworking such as printers. / På grund av den globala Covid-19 pandemin har ett stort antal människor jobbat på distans. Med distansarbete ökade även antalet angrepp mot organisationer vilket medförde att organisationer behövde säkra upp sina nätverk för att utföra distansarbete på ett säkert sätt. Studien undersöker hur IT-ansvariga på små och medelstora företag (SMF) förmedlar till sina slutanvändare om nya och förändrade hot vid distansarbete, hur IT-ansvariga vägleder slutanvändare kring hur de skall jobba säkert vid distansarbete samt vilka övriga metoder som har implementerats för att säkra upp distansarbete.  Studien utfördes genom att tidigare litteratur inom området granskades för att kunna sammanställa en intervjuguide med relevanta frågor. Studien har utförts med en kvalitativ ansats där semistrukturerade intervjuer har använts för att samla in empirin, därefter analyserades den insamlade empiri tematiskt.  Resultatet från studien visar att IT-ansvariga använde sig mycket av mejl och hänvisade till deras intranät för att informera sina slutanvändare kring nya och förändrade hot, men även i mindre grad möten och seminarium. För att vägleda slutanvändare vid arbete på distans hade IT-ansvariga implementerat policyer om vad man fick och inte fick göra. Det fanns även guider för att visa hur slutanvändare skulle arbeta rätt. Ytterligare nyckelaspekter var att utbilda sina slutanvändare och att vid problem kunna erbjuda slutanvändare IT-stöd med hjälp av tillexempel en servicedesk. Studien bidrar med djupare förståelse över de olika metoderna och lösningarna som IT-ansvariga på SMF har implementerat. Utifrån studiens resultat ges följande rekommendationer till små och medelstora företag: Att implementera multifaktorautentisering samt att alla enheter skall ha uppdaterat antivirus och säker fjärråtkomst till lokala resurser. Bör även skaffa en tjänst som möjliggör digital kommunikation och dokumentdelning. Ytterligare rekommendationer var att informera slutanvändare om nya och förändrade hot med hjälp av intranät, mejl eller ytterligare förmedlingsmetoder. Implementera policys och guider som vägleder slutanvändare runt hur de skall arbeta säkert och vad de får och inte får göra vid distansarbete. Slutliga rekommendationer är att utbilda slutanvändare att känna igen vanligare hot som nätfiske via e-post och ge IT-stöd till slutanvändare vid problem med hjälp av en servicedesk. Samt att slutanvändare har den hårdvara som krävs för att kunna arbeta på distans som tillexempel printers.