Riding on recent advances in computing and networking, our society is now experiencing the evolution into the age of information. While the development of these technologies brings great value to our daily life, the lucrative reward from cyber-crimes has also attracted criminals. As computing continues to play an increasing role in the society, security has become a pressing issue. Failures in computing systems could result in loss of infrastructure or human life, as demonstrated in both academic research and production environment. With the continuing widespread of malicious software and new vulnerabilities revealing every day, protecting the heterogeneous computing systems across the Internet has become a daunting task. Our approach to this challenge consists of two directions. The first direction aims to gain a better understanding of the inner working of both attacks and defenses in the cyber environment. Meanwhile, our other direction is designing secure systems in adversarial environment. / Ph. D.

Nowadays cloud computing systems handle large amounts of data and process this data across different systems. It is essential to considering data security vulnerabilities and data protection. One means of decreasing security vulnerabilities is to partition the code into distinct modules and then isolate the execution of the code together with its data. Intel’s Software Guard Extension (SGX) provides security critical code isolation in an enclave. By isolating the code’s execution from an untrusted zone (an unprotected user platform), code integrity and confidentiality are ensured. Transport Layer Security (TLS) is responsible for providing integrity and confidentiality for communication between two entities. Several TLS libraries support cryptographic functions both for an untrusted zone and an enclave. Different TLS libraries have different performance when used with Intel’s SGX. It is desirable to use the best performance TLS library for specific cryptographic functions. This thesis describes a performance evaluation several popular TLS libraries performance on Intel SGX. Using the evaluation results and combining several different TLS libraries together, the thesis proposes a new solution to improve the performance of TLS libraries on Intel SGX. The performance is best when invoking the best specific TLS library based upon the data size – as there is a crossover in performance between the two best libraries. This solution also maintains the versatility of the existing cryptographic functions. / Numera hanterar molnberäkningssystem stora mängder data och bearbetar dessa data över olika system. Det är viktigt att ta itu med datasäkerhetsproblem och dataskydd. Ett sätt att minska säkerhetsproblem är att partitionera koden i olika moduler och sedan isolera kodens exekvering tillsammans med dess data. Intel’s Software Guard Extension (SGX) tillhandahåller säkerhetskritisk kodisolering i en enklav. Genom att isolera kodens körning från en otillförlitlig zon (en oskyddad användarplattform) säkerställs kodintegritet och sekretess. Transport Layer Security (TLS) ansvarar för att ge integritet och konfidentialitet för kommunikation mellan två enheter. Flera TLS-bibliotek stödjer kryptografiska funktioner både för en osäker zon och en enklav. Olika TLS-bibliotek har olika prestanda när de används med Intel’s SGX. Det är önskvärt att använda TLS-bibliotekets bästa prestanda för specifika kryptografiska funktioner. Denna avhandling beskriver en prestationsutvärdering av flera populära TLS-bibliotekens prestanda på Intel SGX. Genom att använda utvärderingsresultaten och kombinera flera olika TLS-bibliotek tillsammans, presenterar avhandlingen en ny design och lösning för att förbättra prestanda för TLS-bibliotek på Intel SGX. Den resulterande prestanda åberopar TLS-bibliotekets bästa prestanda inom en viss datastorlek samtidigt som krypteringsfunktionerna är mångsidiga.

Secure enclave technology has during the last decade emerged as an important hardware security primitive in server computer cores, and increasingly also in chips intended for consumer devices like mobile phones and PCs. The Linux Confidential Compute Consortium has taken a leading role in defining the host APIs for enclave access (e.g. OpenEnclave APIs). Earlier solutions for security isolation in mobile phones relied on so called Trusted Execution Environments, which are similar in hardware isolation, but serve primarily OEM device security use-cases, and the environments are access controlled by remote trust roots (code signatures). This thesis examines the security requirements for enclaves, visible through APIs and SDKs. An augmented IDE / SDK interface that accounts for security, including legacy considerations present with TEEs is also proposed. This thesis also attempts to improve developer experience related to development of trusted application by providing a tight integration with IDE and an expressive way to select methods which can be carved out of an existing rust application into a seperate trusted application. Furthermore, this thesis also discusses some common pitfalls while developing code for trusted applications and attempts to mitigate several of the discussed risks. The work plan includes a background study on existing TEE and enclave SDKs, a novel SDK augmentation that accounts for the features listed above, and a prototype implementation that highlights the enclave security needs beyond mere isolated execution. An IDE plugin is also implemented, that exemplifies how software engineers (with potentially limited security knowledge) can implement a trusted application service with enclave support such that the end result (enclave code) will run without information leakage or interface security problems. / Säker enklavteknologi har under S senaste decenniet framstått som en viktig hårdvarusäkerhets primitiv i serverdatorkärnor och i allt högre grad även i chips avsedda för konsumentenheter som mobiltelefoner och datorer. Linux Confidential Compute Consortium har tagit en ledande roll i att definiera värdAPI:erna för enklavåtkomst (t.ex. OpenEnclave APIs). Tidigare lösningar för säkerhetsisolering i mobiltelefoner förlitade sig på så kallade Trusted Execution Environments, som liknar hårdvaruisolering, men som i första hand tjänar OEMenhetssäkerhetsanvändning, och miljöerna är åtkomstkontrollerade av fjärrstyrda förtroenderötter (kodsignaturer). Denna avhandling undersöker säkerhetskraven för enklaver, synliga genom API:er och SDK:er. Ett utökat IDE/SDK-gränssnitt som står för säkerhet, inklusive äldre överväganden som finns med TEE, föreslås också. Detta examensarbete försöker också förbättra utvecklarupplevelsen relaterad till utveckling av betrodda applikationer genom att tillhandahålla en tät integration med IDE och ett uttrycksfullt sätt att välja metoder som kan skäras ut ur en befintlig rostapplikation till en separat betrodd applikation. Dessutom diskuterar denna avhandling också några vanliga fallgropar samtidigt som man utvecklar kod för betrodda applikationer och försöker mildra flera av de diskuterade riskerna. Arbetsplanen inkluderar en bakgrundsstudie av befintliga TEE- och enklav-SDK:er, en ny SDK-förstärkning som står för funktionerna som anges ovan, och en prototypimplementering som belyser enklavens säkerhetsbehov utöver enbart isolerad exekvering. En IDE-plugin är också implementerad, som exemplifierar hur mjukvaruingenjörer (med potentiellt begränsad säkerhetskunskap) kan implementera en betrodd applikationstjänst med enklavstöd så att slutresultatet (enklavkoden) kommer att köras utan informationsläckage eller gränssnittssäkerhetsproblem.

In the context of cloud computing, Trusted Execution Environments (TEE) are isolated areas of application software that can be executed with better security, building a trusted and secure environment that is detached from the rest of the memory. Trusted Execution Environment is a technology that become available only in the last few years, and it is not widespread yet. This thesis investigates the most popular approaches to build a TEE, namely the process-based and the virtualization-based, and will abstract them as much as possible to design a common infrastructure that can deploy TEEs on an external cloud provider, no matter which technology approach is used. The thesis is relevant and novel because the project will give the possibility to use different technologies for the deployment, such as Intel SGX and AMD SEV, which are the two main solutions, but without being reliant on any particular one. If in the future new technologies or vendors’ solutions will become popular, they can be simply added to the list of options. The same can be said for the cloud provider choice. The results show that it is possible to abstract the common features of different TEE’s technologies and to use a unique Application Programming Interface (API) to deploy different TEE´s technologies. We will also ran a performance and quality evaluation, and the results show that the API is performant and respect the common standard quality. This tool is useful for the problem owner and future works on the topic of cloud security. / I samband med cloud computing är Trusted Execution Environments (TEE) isolerade områden av applikationsprogramvara som kan köras med bättre säkerhet, bygga en pålitlig och säker miljö som är frikopplad från resten av minnet. Trusted Execution Environment är en teknik som blivit tillgänglig först under de senaste åren, och den är inte utbredd ännu. Denna avhandling undersöker de mest populära metoderna för att bygga en TEE, nämligen den processbaserade och den virtualiseringsbaserade, och kommer att abstrahera dem så mycket som möjligt för att designa en gemensam infrastruktur som kan distribuera TEEs på en extern molnleverantör, oavsett vilken teknik tillvägagångssätt används. Avhandlingen är relevant och ny eftersom projektet kommer att ge möjligheten att använda olika teknologier för implementeringen, såsom Intel SGX och AMD SEV, som är de två huvudlösningarna, men utan att vara beroende av någon speciell. Om i framtiden nya teknologier eller leverantörers lösningar kommer att bli populära kan de helt enkelt läggas till i listan över alternativ. Detsamma kan sägas om valet av molnleverantör. Resultaten visar att det är möjligt att abstrahera de gemensamma egenskaperna hos olika TEE:s teknologier och att använda ett unikt Application Programming Interface (API) för att distribuera olika TEE:s teknologier. Vi kommer också att göra en prestanda- och kvalitetsutvärdering, och resultaten visar att API:et är prestanda och respekterar den gemensamma standardkvaliteten. Det här verktyget är användbart för problemägaren och framtida arbeten på ämnet molnsäkerhet.

The rapid development of Internet of Things (IoT) devices has brought unparalleled convenience and efficiency to our daily lives. However, with this exponential growth comes the pressing need to address the critical security challenges posed by these interconnected devices. IoT devices are typically resource-constrained, lacking the robust computing power and memory capacity of traditional computing systems, which often leads to a lack of adequate security mechanisms and leaves them vulnerable to various attacks. This master’s thesis contributes by investigating a secure mechanism that utilizes the hardware isolation provided by the TrustZone technology found in ARM’s Cortex-M processors. TrustZone is a hardware-based security extension in ARM processors that enables a secure, isolated environment for executing sensitive code alongside a regular, non-secure operating system. This thesis uses this mechanism and implements a Trusted Execution Environment (TEE) in the secure environment of TrustZone that monitors the resource usage of applications running in the non-secure operating system. The aim of the TEE is to monitor the network communication and the CPU usage of the applications running on the IoT device, protecting its integrity and detecting any abnormal behavior. The implementation is done inside the Contiki-NG operating system, a well-known operating system designed for constrained IoT devices. The thesis conducts a comprehensive evaluation of the developed security solution through extensive experiments using two micro-benchmarks. It analyzes the impact of the security mechanism on various aspects of the IoT device, such as runtime overhead, energy consumption, and memory requirements, while taking into account the resource constraints. Furthermore, the effectiveness of the security solution in identifying malicious activities and abnormal behaviors is thoroughly assessed. The findings demonstrate that the TrustZone-based security mechanism introduces relatively minimal overhead to the device’s operation, making it a viable option for IoT devices that can accommodate such slight performance impacts. The research sheds light on the critical issue of IoT device security, emphasizing the need for tailored solutions that consider the resource constraints of these devices. It presents an alternative solution that utilizes TrustZone’s hardware isolation to effectively monitor the applications running in IoT devices and opens a new approach to securing such kinds of devices. / Den snabba utvecklingen av Internet of Things (IoT)-enheter har gett oöverträffad bekvämlighet och effektivitet i våra dagliga liv. Men med denna exponentiella tillväxt kommer det trängande behovet att ta itu med de kritiska säkerhetsutmaningarna som dessa sammankopplade enheter utgör. IoT-enheter är vanligtvis resursbegränsade och saknar den robusta datorkraften och minneskapaciteten hos traditionella datorsystem, vilket ofta leder till brist på adekvata säkerhetsmekanismer och gör dem sårbara för olika attacker. Denna rapport bidrar genom att undersöka en säker mekanism som använder hårdvaruisoleringen som tillhandahålls av TrustZone-teknologin som finns i ARMs Cortex-M-processorer. TrustZone är ett hårdvarubaserad säkerhetstillägg i ARM-processorer som möjliggör en säker, isolerad miljö för exekvering av känslig kod tillsammans med ett vanligt, osäkrat operativsystem. Denna rapport använder denna mekanism och implementerar ett Trusted Execution Environment (TEE) i den säkra miljön i TrustZone som övervakar resursanvändningen av applikationer som körs i det osäkra operativsystemet. Syftet med TEE är att övervaka nätverkskommunikationen och CPU-användningen för de applikationer som körs på IoT-enheten, skydda dess integritet och upptäcka eventuellt onormalt beteende. Implementeringen görs i operativsystemet Contiki-NG, ett välkänt operativsystem designat för begränsade IoT-enheter. Rapporten genomför en omfattande utvärdering av den utvecklade säkerhetslösningen genom omfattande experiment med två mikroriktmärken. Den analyserar effekten av säkerhetsmekanismen på olika aspekter av IoTenheten, såsom overhead under drift, energiförbrukning och minneskrav, samtidigt som resursbegränsningarna tas i beaktande. Dessutom utvärderas effektiviteten grundligt hos säkerhetslösningen för att identifiera skadliga aktiviteter och onormala beteenden. Resultaten visar att den TrustZonebaserade säkerhetsmekanismen introducerar relativt minimal overhead för enhetens drift, vilket gör det till ett genomförbart alternativ för IoT-enheter som kan hantera en liten prestandapåverkan. Forskningen belyser den kritiska frågan om IoT-enhetssäkerhet och betonar behovet av skräddarsydda lösningar som tar hänsyn till dessa enheters resursbegränsningar. Den presenterar en alternativ lösning som använder TrustZones hårdvaruisolering för att effektivt övervaka applikationer som körs i IoT-enheter och öppnar ett nytt tillvägagångssätt för att säkra sådana typer av enheter.

A trusted execution environment (TEE) is an isolated environment used for trusted execution. TEE solutions are usually proprietary and specific for a certain hardware specification, thereby limiting developers that use those TEEs. A potential solution to this issue is the use of open-source alternatives such as the TEE framework Keystone and the Reduced Instruction Set Computer V (RISC-V) hardware. These alternatives are rather young and are not as well established as the variants developed by ARM and Intel. To this end, the assurance in Keystone and RISC-V are analysed by studying a remote attestation assurance use case using the goal structuring notation (GSN) method. The aim is to investigate how GSN can be utilised to build assurance cases for TEEs on RISC-V. This thesis presents a process of how GSNs can be created to argue assurance for a TEE solution. Furthermore, Keystone operates under a specific threat model with made assumptions that may have a large impact depending on the use case. Therefore, Keystone is analysed to understand whether the framework mitigates existing vulnerabilities in TEEs. It is concluded that GSN is a viable method for arguing assurance in TEEs, providing great freedom in the creation of the GSN model. The freedom is also its weakness since the argument composition has a high impact on the argument. Furthermore, we conclude that Keystone mitigates multiple known vulnerabilities primarily through made assumptions in its threat model. These cases need to be considered by developers utilising Keystone to determine whether or not the assumptions are valid for their use case.

The rapid increase in the number of IoT devices and their widespread applications demands secure and scalable solutions for managing and executing IoT workflows. This thesis investigates the security of IoT workflows created in Node-RED, an open-source visual programming tool, and deployed on untrusted hosts managed by a major cloud service provider, Azure. The hypothesis was that the security of IoT workflows could be improved by utilizing a trusted execution environment, such as Intel SGX. Additionally, an assessment of consequent performance degradation was proposed. A threat model for an IoT workflow system scenario was established using the STRIDE threat modeling framework. An evaluation of the security guarantees provided by the prototype system was performed using an analysis comparing the security guarantees of underlying technologies, predominantly Intel SGX, and aggregating them to establish the security promises of the final system. The performance evaluation of the system was conducted using a set of experimental workflows, executed both natively on Linux and inside Intel SGX. The proposed prototype system was deemed to be capable of mitigating 15 out of 18 potential threats defined in the threat model, which indicates a significant threat risk reduction. However, the added security resulted in degraded performance, which was considerable when executing system calls and significantly noticeable for workflows requiring multi-threading. The results showed that node execution time inside SGX was 4.8 times slower and the mean round trip time for workflow execution was 6 times slower than the native execution. The thesis aims to provide a starting point for estimating performance degradation for potential future applications requiring secure IoT workflow deployment on untrusted hosts. / Den snabba ökningen av antalet IoT-enheter i dagens samhälle och deras breda användningsområden kräver säkra och skalbara lösningar för exekvering av IoT-arbetsflöden. Detta examensarbete undersöker säkerheten för IoT-arbetsflöden skapade i Node-RED, ett öppen källkodsverktyg för visuell programmering, i kontexten att dessa arbetsflöden exekveras på opålitliga enheter som hanteras av molntjänstföretag, som i detta fall är Azure. Hypotesen var att säkerhetsgarantin för IoT-arbetsflöden kunde förbättras genom att använda en betrodd exekveringmiljö, såsom Intel SGX. Dessutom krävdes en utvärdering av påföljderna på systemets prestanda som en konsekvens av den betrodda exekveringmiljöns användning. En hotmodell för ett IoT-arbetsflödesystem etablerades med hjälp av ramverket STRIDE. En bedömning av säkerhetsgarantierna som tillhandahålls av prototypsystemet genomfördes med hjälp av en kvalitativ analys som jämförde säkerhetsgarantier för underliggande teknologier, främst Intel SGX, och aggregerade dessa för att etablera säkerhetsgarantin för det slutgiltiga systemet. Prestandautvärderingen av systemet genomfördes med hjälp av ett antal experimentella arbetsflöden, som exekverades både direkt på Linux och inuti den betrodda exekveringsmiljön Intel SGX. I det föreslagna prototypsystemet ansågs 15 utav 18 potentiella hot som definierats i hotmodellen vara försumbara, vilket indikerar en signifikant reduktion av hotbilden. Dock resulterade den ökade säkerheten i en försämrad prestanda, som var betydande när systemanrop användes och synnerligen märkbar för flöden som krävde parallellisering. Resultaten visade att nodexekveringstiden inuti SGX var 4,8 gånger långsammare och medelvärdet för rundturstiden för exekvering av ett arbetsflöde var 6 gånger långsammare än den direkta exekveringen. Examensarbetet syftar till att ge en utgångspunkt för att bedöma prestandaförsämringen för potentiella framtida applikationer som kräver säkra IoT-arbetsflöden exekverade på opålitliga enheter.

Exfiltrating or tampering with certain business logic, algorithms, and data can harm the security and privacy of both organizations and end users. Collectively referred to as sensitive program information (SPI), these building blocks are part and parcel of modern software systems in domains ranging from enterprise applications to cyberphysical setups. Hence, protecting SPI has become one of the most salient challenges of modern software development. However, several fundamental obstacles stand on the way of effective SPI protection: (1) understanding and locating the SPI for any realistically sized codebase by hand is hard; (2) manually isolating SPI to protect it is burdensome and error-prone; (3) if SPI is passed across distributed components within and across devices, it becomes vulnerable to security and privacy attacks. To address these problems, this dissertation research innovates in the realm of automated program analysis, code transformation, and novel programming abstractions to improve the state of the art in SPI protection. Specifically, this dissertation comprises three interrelated research thrusts that: (1) design and develop program analysis and programming support for inferring the usage semantics of program constructs, with the goal of helping developers understand and identify SPI; (2) provide powerful programming abstractions and tools that transform code automatically, with the goal of helping developers effectively isolate SPI from the rest of the codebase; (3) provide programming mechanism for distributed managed execution environments that hides SPI, with the goal of enabling components to exchange SPI safely and securely. The novel methodologies, techniques, and software tools, supported by programming abstractions, automated program analysis, and code transformation of this dissertation research lay the groundwork for establishing a secure, understandable, and efficient foundation for protecting SPI. This dissertation is based on 4 conference papers, presented at TrustCom'20, GPCE'20, GPCE'18, and ManLang'17, as well as 1 journal paper, published in Journal of Computer Languages (COLA). / Doctor of Philosophy / Some portions of a computer program can be sensitive, referred to as sensitive program information (SPI). By compromising SPI, attackers can hurt user security/privacy. It is hard for developers to identify and protect SPI, particularly for large programs. This dissertation introduces novel methodologies, techniques, and software tools that facilitate software developments tasks concerned with locating and protecting SPI.

Trusted execution environments (TEEs) are an emerging technology that provides a protected hardware environment for processing and storing sensitive information. By using TEEs, developers can bolster the security of software systems. However, incorporating TEE into existing software systems can be a costly and labor-intensive endeavor. Software maintenance—changing software after its initial release—is known to contribute the majority of the cost in the software development lifecycle. The first step of making use of a TEE requires that developers accurately identify which pieces of code would benefit from being protected in a TEE. For large code bases, this identification process can be quite tedious and time-consuming. To help reduce the software maintenance costs associated with introducing a TEE into existing software, this thesis introduces ML-TEE, a recommendation tool that uses a deep learning model to classify whether an input function handles sensitive information or sensitive code. By applying ML-TEE, developers can reduce the burden of manual code inspection and analysis. ML-TEE's model was trained and tested on functions from GitHub repositories that use Intel SGX and on an imbalanced dataset. The accuracy of the final model used in the recommendation system has an accuracy of 98.86% and an F1 score of 80.00%. In addition, we conducted a pilot study, in which participants were asked to identify functions that needed to be placed inside a TEE in a third-party project. The study found that on average, participants who had access to the recommendation system's output had a 4% higher accuracy and completed the task 21% faster. / Master of Science / Improving the security of software systems has become critically important. A trusted execution environment (TEE) is an emerging technology that can help secure software that uses or stores confidential information. To make use of this technology, developers need to identify which pieces of code handle confidential information and should thus be placed in a TEE. However, this process is costly and laborious because it requires the developers to understand the code well enough to make the appropriate changes in order to incorporate a TEE. This process can become challenging for large software that contains millions of lines of code. To help reduce the cost incurred in the process of identifying which pieces of code should be placed within a TEE, this thesis presents ML-TEE, a recommendation system that uses a deep learning model to help reduce the number of lines of code a developer needs to inspect. Our results show that the recommendation system achieves high accuracy as well as a good balance between precision and recall. In addition, we conducted a pilot study and found that participants from the intervention group who used the output from the recommendation system managed to achieve a higher average accuracy and perform the assigned task faster than the participants in the control group.

An increasing number of software systems must safeguard their confidential data and code, referred to as critical program information (CPI). Such safeguarding is commonly accomplished by isolating CPI in a trusted execution environment (TEE), with the isolated CPI becoming a trusted computing base (TCB). TEE protection incurs heavy performance costs, as TEE-based functionality is expensive to both invoke and execute. Despite these costs, projects that use TEEs tend to have unnecessarily large TCBs. As based on our analysis, developers often put code and data into TEE for convenience rather than protection reasons, thus not only compromising performance but also reducing the effectiveness of TEE protection. In order for TEEs to provide maximum benefits for protecting CPI, their usage must be systematically incorporated into the entire software engineering process, starting from Requirements Engineering. To address this problem, we present a novel approach that incorporates TEEs in the Requirements Engineering phase by using natural language processing (NLP) to classify those software requirements that are security critical and should be isolated in TEE. Our approach takes as input a requirements specification and outputs a list of annotated software requirements. The annotations recommend to the developer which corresponding features comprise CPI that should be protected in a TEE. Our evaluation results indicate that our approach identifies CPI with a high degree of accuracy to incorporate safeguarding CPI into Requirements Engineering. / Master of Science / An increasing number of software systems must safeguard their confidential data like passwords, payment information, personal details, etc. This confidential information is commonly protected using a Trusted Execution Environment (TEE), an isolated environment provided by either the existing processor or separate hardware that interacts with the operating system to secure sensitive data and code. Unfortunately, TEE protection incurs heavy performance costs, with TEEs being slower than modern processors and frequent communication between the system and the TEE incurring heavy performance overhead. We discovered that developers often put code and data into TEE for convenience rather than protection purposes, thus not only hurting performance but also reducing the effectiveness of TEE protection. By thoroughly examining a project's features in the Requirements Engineering phase, which defines the project's functionalities, developers would be able to understand which features handle confidential data. To that end, we present a novel approach that incorporates TEEs in the Requirements Engineering phase by means of Natural Language Processing (NLP) tools to categorize the project requirements that may warrant TEE protection. Our approach takes as input a project's requirements and outputs a list of categorized requirements defining which requirements are likely to make use of confidential information. Our evaluation results indicate that our approach performs this categorization with a high degree of accuracy to incorporate safeguarding the confidentiality related features in the Requirements Engineering phase.