Hardware-Assisted Trusted Execution Environment technologies have become a crucial component in providing security for cloud-based computing. One of such hardware-assisted countermeasures is Intel Software Guard Extension (SGX). Using additional dedicated hardware and a new set of CPU instructions, SGX is able to provide isolated execution of code within trusted hardware containers called enclaves. By utilizing private encrypted memory and various integrity authentication mechanisms, it can provide confidentiality and integrity guarantees to protected data. In spite of dedicated hardware, these extra layers of security add a significant performance overhead. Decryption of data using secret OTPs, which are generated by modified Counter Mode Encryption AES blocks, results in a significant latency overhead that contributes to the overall SGX performance loss. This thesis introduces a metadata prediction extension to SGX based on local metadata releveling and prediction mechanisms. Correct prediction of metadata allows to speculatively precompute OTPs, which can be immediately used in decryption of incoming ciphertext data. This hides a significant part of decryption latency and results in faster SGX performance without any changes to the original SGX security guarantees. / Master of Science / With the exponential growth of cloud computing, where critical data processing is happening on third-party computer systems, it is important to ensure data confidentiality and integrity against third-party access. Sometimes that may include not only external attackers, but also insiders, like cloud computing providers themselves. While software isolation using Virtual Machines is the most common method of achieving runtime security in cloud computing, numerous shortcomings of software-only countermeasures force companies to demand extra layers of security. Recently adopted general purpose hardware-assisted technology like Intel Software Guard Extension (SGX) add that extra layer of security at the significant performance overhead. One of the major contributors to the SGX performance overhead is data decryption latency. This work proposes a novel algorithm to speculatively predict metadata that is used during decryption. This allows the processor to hide a significant portion of decryption latency, thus improving the overall performance of Intel SGX without compromising security.

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.

As enterprises migrate their data to cloud infrastructure, they increasingly need a flexible, scalable, and secure marketplace for collaborative data creation, analysis, and exchange among enterprises. Security is a prominent research challenge in this context, with a specific question on how two mutually distrusting data owners can share their data. Confidential Computing helps address this question by allowing to perform data computation inside hardware-based Trusted Execution Environments (TEEs) which we refer to as enclaves, a secured memory that is allocated by CPU. Examples of hardware-based TEEs are Advanced Micro Devices (AMD)-Secure Encrypted Virtualization (SEV), Intel Software Guard Extensions (SGX) and Intel Trust Domain Extensions (TDX). Intel SGX is considered as the most popular hardware-based TEEs since it is widely available in processors targeting desktop and server platforms. Intel SGX can be programmed using Software Development Kit (SDK) as development framework and Library Operating Systems (Library OSes) as runtimes. However, communication with software in the enclave such as the Library OS through system calls may result in performance overhead. In this project, we design confidential data transactions among multiple users, using Intel SGX as TEE hardware and Occlum as Library OS. We implement the design by allowing two clients as data owners share their data to a server that owns Intel SGX capable platform. On the server side, we run machine learning model inference with inputs from both clients inside an enclave. In this case, we aim to evaluate Occlum as a memory-safe Library Operating System (OS) that enables secure and efficient multitasking on Intel SGX by measuring two evaluation aspects such as performance overhead and security benefits. To evaluate the measurement results, we compare Occlum with other runtimes: baseline Linux and Graphene-SGX. The evaluation results show that our design with Occlum outperforms Graphene-SGX by 4x in terms of performance. To evaluate the security aspects, we propose 11 threat scenarios potentially launched by both internal and external attackers toward the design in SGX platform. The results show that Occlum security features succeed to mitigate 10 threat scenarios out of 11 scenarios overall. / När företag migrerar sin data till molninfrastruktur behöver de i allt högre grad en flexibel, skalbar och säker marknadsplats för gemensam dataskapande, analys och utbyte mellan företag. Säkerhet är en framstående forskningsutmaning i detta sammanhang, med en specifik fråga om hur två ömsesidigt misstroende dataägare kan dela sina data. Confidential Computing hjälper till att ta itu med den här frågan genom att tillåta att utföra databeräkning i hårdvarubaserad TEEs som vi kallar enklaver, ett säkert minne som allokeras av CPU. Exempel på maskinvarubaserad TEEs är AMD-SEV, Intel SGX och Intel TDX. Intel SGX anses vara den mest populära maskinvarubaserade TEEs eftersom det finns allmänt tillgängligt i processorer som riktar sig mot stationära och serverplattformar. Intel SGX kan programmeras med hjälp av SDK som utvecklingsram och Library Operating System (Library OSes) som körtid. Kommunikation med programvara i enklaven, till exempel Library OS via systemanrop, kan dock leda till prestandakostnader. I det här projektet utformar vi konfidentiella datatransaktioner mellan flera användare, med Intel SGX som TEE-hårdvara och Occlum som Library OS. Vi implementerar designen genom att låta två klienter som dataägare dela sina data till en server som äger Intel SGX-kompatibel plattform. På serversidan kör vi maskininlärningsmodell slutsats med ingångar från båda klienterna i en enklav. I det här fallet strävar vi efter att utvärdera Occlum som ett minnessäkert Library OS som möjliggör säker och effektiv multitasking på Intel SGX genom att mäta två utvärderingsaspekter som prestandakostnader och säkerhetsfördelar. För att utvärdera mätresultaten jämför vi Occlum med andra driftstider: baslinjen Linux och Graphene-SGX. Utvärderingsresultaten visar att vår design med Occlum överträffar Graphene-SGX av 4x när det gäller prestanda. För att utvärdera säkerhetsaspekterna föreslår vi elva hotscenarier som potentiellt lanseras av både interna och externa angripare mot designen i SGX-plattformen. Resultaten visar att Occlums säkerhetsfunktioner lyckas mildra 10 hotscenarier av 11 scenarier totalt.

Cloud computing has become a default choice for data processing by both large corporations and individuals due to its economy of scale and ease of system management. However, the question of trust and trustoworthy computing inside the Cloud environments has been long neglected in practice and further exacerbated by the proliferation of AI and its use for processing of sensitive user data. Attempts to implement the mechanisms for trustworthy computing in the cloud have previously remained theoretical due to lack of hardware primitives in the commodity CPUs, while a combination of Secure Boot, TPMs, and virtualization has seen only limited adoption. The situation has changed in 2016, when Intel introduced the Software Guard Extensions (SGX) and its enclaves to the x86 ISA CPUs: for the first time, it became possible to build trustworthy applications relying on a commonly available technology. However, Intel SGX posed challenges to the practitioners who discovered the limitations of this technology, from the limited support of legacy applications and integration of SGX enclaves into the existing system, to the performance bottlenecks on communication, startup, and memory utilization. In this thesis, our goal is enable trustworthy computing in the cloud by relying on the imperfect SGX promitives. To this end, we develop and evaluate solutions to issues stemming from limited systems support of Intel SGX: we investigate the mechanisms for runtime support of POSIX applications with SCONE, an efficient SGX runtime library developed with performance limitations of SGX in mind. We further develop this topic with FFQ, which is a concurrent queue for SCONE's asynchronous system call interface. ShieldBox is our study of interplay of kernel bypass and trusted execution technologies for NFV, which also tackles the problem of low-latency clocks inside enclave. The two last systems, Clemmys and T-Lease are built on a more recent SGXv2 ISA extension. In Clemmys, SGXv2 allows us to significantly reduce the startup time of SGX-enabled functions inside a Function-as-a-Service platform. Finally, in T-Lease we solve the problem of trusted time by introducing a trusted lease primitive for distributed systems. We perform evaluation of all of these systems and prove that they can be practically utilized in existing systems with minimal overhead, and can be combined with both legacy systems and other SGX-based solutions. In the course of the thesis, we enable trusted computing for individual applications, high-performance network functions, and distributed computing framework, making a <vision of trusted cloud computing a reality.

Organizations in highly regulated industries have an increasing need to protect their intellectual assets, because Advanced Persistent Threat (APT) entities are capable of using supply chain attacks to bypass traditional defenses. This work investigates the feasibility of preventing supply chain attacks by isolating the build environment of the software using hardware isolation. Specifically, this work analyzes the extent to which the Intel SGX can guarantee the integrity and authenticity of software produced in Highly Regulated Environments. A theoretical evaluation using assurance cases shows that a hardware isolation approach has the potential to guarantee the integrity and authenticity of the produced software. Security weaknesses in Intel SGX significantly limit the confidence in its ability to secure the build environment. Directions for future work to secure a build environment with a hardware isolation approach are suggested. Most importantly, the guarantees from hardware isolation should be improved, suggestively by choosing a more secure hardware isolation solution, and a proof-of-concept of the approach should be implemented. / Organisationer i mycket reglerade industrier har ett ökat behov av att skydda sina intellektuella tillgångar, eftersom avancerade långvariga hot (APT) har förmågan att använda sig av distributionskedjeattacker för att ta sig förbi existerande skydd. Det här arbetet undersöker möjligheten att skydda sig mot distributionskedjeattacker genom att isolera mjukvarans byggmiljö med hjälp av hårdvaruisolering. Specifikt analyseras till vilken grad Intel SGX kan garantera integriteten och autenticiteten av mjukvara som produceras i mycket reglerade miljöer. En teoretisk evaluering genom assurans visar att hårdvaruisolering har möjligheten att garantera integriteten och autenticiteten hos den producerade mjukvaran. Säkerhetsbrister i Intel SGX begränsar i hög grad förtroendet för dess förmåga att säkra byggmiljön. För vidare forskning föreslås att garantierna från hårdvaruisolering förbättras, förslagsvis genom att välja säkrare hårdvaruisoleringslösningar, samt att en prototyp av lösningen implementeras.

The aim of this thesis is to create a concept of semi-centralized cryptocurrency that supports external interoperability. It is assumed that semi-centralized cryptocurrency is the future of cryptocurrencies in the banking sector, because even at the cost of partial centralization, the concept brings the benefits of a decentralized ledger. Since the simultaneous deployment of their own cryptocurrencies by various central authorities, such as central bank, it is necessary to establish a communication protocol for interbank transactions. The work is thus focused on extending the existing Aquareum solution with an interoperability protocol.

No description available.

The Internet of Things (IoT) consists of a network of physical devices that are connected over the internet for the purpose of exchanging data with other devices and systems. IoT platforms, such as Node-RED, have been introduced in recent times to facilitate communication between different IoT devices. Hosting Node-RED on a cloud service provider might result in the confidentiality of sensitive data on Node-RED being violated by malicious attackers, since users are forced to entrust their sensitive data with the cloud service providers. Using trusted execution environments, such as AMD-SEV and Intel SGX, can mitigate several potential attacks from exposing sensitive information in Node-RED. This thesis investigates if AMD-SEV and Intel SGX are viable options to protect sensitive data in Node-RED when hosted on a cloud service provider. The work in this thesis investigates difficulties encountered when deploying Node-RED on AMD-SEV and Intel SGX, from a usability perspective. Usability is measured by running Node-RED in AMDSEV and Intel SGX, and then recording the complexity of the process. Several performance tests are conducted to measure the performance overhead of Node-RED caused by AMD-SEV. A literature review is also conducted to investigate potential vulnerabilities in AMD-SEV and Intel SGX that could undermine the security of user’s data in Node-RED. The results from this thesis finds that AMD-SEV is a viable option to protect sensitive data in Node-RED when hosted on a cloud service provider. Deploying Node-RED on AMD-SEV is found to be a relatively simple process from a usability perspective. There are some noticeable performance overhead with regards to CPU utilization and TCP throughput, but all other metrics show marginal performance overhead. The potential vulnerabilities in AMD-SEV are not found to be significant enough to make AMD-SEV unviable. The thesis finds Intel SGX to be an unviable solution primarily due to usability. The process of running Node-RED in an Intel SGX enclave is extremely complex and the results show that for most users of Node-RED, this is not viable. The security vulnerabilities found from the literature review, are not significant enough to make Intel SGX an unviable option to protect sensitive user data inNode-RED. / Internet of Things (IoT) är en nätverk av fysiska enheter som är sammankopplade via internet för att kunna skicka data till andra fysiska enheter eller system. IoTplattformar, som Node-RED, har utvecklats för att förenkla kommunikationen mellan olika IoT- enheter. Att köra Node-RED på en molntjänst kan leda till att sekretessen av känslig data på Node-RED blir kränkt av en attack mot molntjänsten. Det är på grund av att användarna av Node-RED är tvungna att tillförlita deras känsliga data till molntjänsten, som deras data kan bli kränkt. Detta problem kan förminskas genom att användarna utnyttjar trusted execution environments som AMD-SEV och Intel SGX för att skydda sin känsliga data på molntjänsten. I denna avhandling, undersöks det om AMDSEV och Intel SGX kan användas för att skydda data i Node-RED när den körs på en molntjänst. Användarvänligheten av att köra Node-RED med AMD-SEV och Intel SGX undersöks genom att uppskatta hur komplicerad denna process är. Flera tester genomförs också för att mäta vilken påverkan AMD-SEV har på prestandan av Node-RED. En litteraturöversikt genomförs också för att undersöka potentiella sårbarheter i AMD-SEV och Intel SGX som skulle kunna utnyttjas för att komma åt känslig data i Node-RED. Resultaten från avhandlingen visar att AMD-SEV kan vara användbart för att skydda känslig data i Node-RED när den körs på en molntjänst. AMDSEV är väldigt användarvänlig när Node-RED ska köras. AMD-SEV har en märkbar påverkan på prestandan av processorn och TCP- genomströmning, men för de andra faktorerna som mäts har AMD-SEV ingen större påverkan. Litteraturöversikten finner inga sårbarheter som är tillräckligt farliga för att göra AMD-SEV oanvändbar för att skydda känslig data iNode-RED. Resultaten från avhandlingen visar dock att Intel SGX inte är särskilt användbar för att skydda känslig data i Node-RED när den körs på en molntjänst. Detta är främst för att det är väldigt komplicerat att köra Node-RED i en Intel SGX enklav från en användarvänlighet synpunkt. De flesta av Node-REDs användare skulle finna det för komplicerat att använda Intel SGX för att skydda sin känsliga data. Litteraturöversikten finner inga sårbarheter allvarliga nog för att göra Intel SGX oanvändbar.

In recent years, trusted execution environments (TEEs) have seen increasing deployment in computing devices to protect security-critical software from run-time attacks and provide isolation from an untrustworthy operating system (OS). A trusted party verifies the software that runs in a TEE using remote attestation procedures. However, the publication of transient execution attacks such as Spectre and Meltdown revealed fundamental weaknesses in many TEE architectures, including Intel Software Guard Exentsions (SGX) and Arm TrustZone. These attacks can extract cryptographic secrets, thereby compromising the integrity of the remote attestation procedure. In this work, we design and develop a TEE architecture that provides remote attestation integrity protection even when confidentiality of the TEE is compromised. We use the formally verified seL4 microkernel to build the TEE, which ensures strong isolation and integrity. We offload cryptographic operations to a secure co-processor that does not share any vulnerable microarchitectural hardware units with the main processor, to protect against transient execution attacks. Our design guarantees integrity of the remote attestation procedure. It can be extended to leverage co-processors from Google and Apple, for wide-scale deployment on mobile devices. / Under de senaste åren används betrodda exekveringsmiljöer (TEE) allt mera i datorutrustning för att skydda säkerhetskritisk programvara från attacker och för att isolera dem från ett opålitligt operativsystem. En betrodd part verifierar programvaran som körs i en TEE med hjälp av fjärrattestering. Nyliga mikroarkitekturella anfall, t.ex. Spectre och Meltdown, har dock visat grundläggande svagheter i många TEE-arkitekturer, inklusive Intel SGX och Arm TrustZone. Dessa attacker kan avslöja kryptografiska hemligheter och därmed äventyra integriteten av fjärrattestning. I det här arbetet utvecklar vi en arkitektur för en betrodd exekveringsmiljö (TEE) som ger integritetsskydd genom fjärrattestering även när TEE:s konfidentialitet äventyras. Vi använder den formellt verifierade seL4-mikrokärnan för att bygga TEE:n som garanterar stark isolering och integritet. För att skydda kryptografiska operationer, overför vi dem till en säker samprocessor som inte delar någon sårbar mikroarkitektur med huvudprocessorn. Vår arktektur garanterar fjärrattesteringens integritet och kan utnyttja medprocessorer från Google och Apple för att användas i stor skala på mobila enheter.

Submitted by Emanuel Varela Cardoso (emanuel.varela@ufcg.edu.br) on 2018-09-06T19:24:24Z No. of bitstreams: 1 RODOLFO DE ANDRADE MARINHO SILVA – DISSERTAÇÃO (PPGCC) 2018.pdf: 798016 bytes, checksum: 4dfd41c1185e692e1c3b8a11f541a6a6 (MD5) / Made available in DSpace on 2018-09-06T19:24:24Z (GMT). No. of bitstreams: 1 RODOLFO DE ANDRADE MARINHO SILVA – DISSERTAÇÃO (PPGCC) 2018.pdf: 798016 bytes, checksum: 4dfd41c1185e692e1c3b8a11f541a6a6 (MD5) Previous issue date: 2018-03-01 / No decorrer das últimas décadas, uma quantidade de dados de usuários cada vez maior vem sendo enviada para ambientes não controlados pelos mesmos. Em alguns casos esses dados são enviados com o objetivo de tornar esses dados públicos, mas na grande maioria das vezes há a necessidade de manter esses dados seguros e privados, ou autorizar o seu acesso apenas em usos bem específicos. Considerando o caso onde os dados devem ser mantidos privados, entidades devem tomar cuidados especiais para manter a segurança e privacidade de tais dados tanto durante a transmissão quanto durante o armazenamento e processamento dos mesmos. Com esse objetivo, vários esforços vêm sendo feitos, inclusive o desenvolvimento de componentes de hardware que provêem ambientes de execução confiável,TEEs, como o Intel Software Guard Extensions(SGX). O uso dessa tecnologia, porém, pode ser feito de forma incorreta ou ineficiente, devido a cuidados não observados durante o desenvolvimento de aplicações. O trabalho apresentado nessa dissertação aborda os principais desafios enfrentados no desenvolvimento de aplicações que façam uso deSGX, e propõe boas práticas e um conjunto de ferramentas (DynSGX) que ajudam a fazer melhor uso das capacidades da tecnologia. Tais desafios incluem, mas não são limitados a, particionamento de aplicações de acordo com o modelo de programação do SGX, colocação de aplicações em ambientes de computação na nuvem, e, sobretudo, gerência de memória. Os estudos apresentados neste trabalho apontam que o mal uso da tecnologia pode acarretar em uma perda de performance considerável se comparado com implementações que levam em conta as boas práticas propostas. O conjunto de ferramentas proposto neste trabalho também mostrou possibilitar a proteção de código de aplicações em ambientes de computação na nuvem, com uma sobrecarga desprezível em comparação com o modelo de programação padrão de SGX. / During the last few decades, an increasing amount of user data have been sent to environments not controlled by data owners. In some cases these data are sent with the objective to turn them public, but in the vast majority of times, these data need to be kept safe and private, or to be allowed access only in very specific use cases. Considering the case where data need to be kept private, entities must take specific measures to maintain the data security and privacy while transmitting, storing and processing them. With this objective many efforts have been made, including the specification of hardware components that provide a trusted execution environment (TEEs), like the Intel Software Guard Extensions (SGX). The use of this technology , though, can be made in incorrect or ineffective ways, due to not taking some considerations into account during the development of applications. In this work, we approach the main challenges faced in the development of applications that use SGX, and propose good practices and a toolset (DynSGX) that help making better use of the capabilities of this technology. Such challenges include, but are not limited to, application partitioning, application colocation in cloud computing environments, and memory management. The studies presented in this work show that the bad use of this technology can result in a considerable performance loss when compared to implementations that take into account the good practices proposed. The toolset proposed in this work also showed to enable protecting application code in cloud computing environments, having a negligible performance overhead when compared to the regular SGX programming model.