Enabling Usable and Performant Trusted Execution

A plethora of major security incidents---in which personal identifiers belonging to hundreds of millions of users were stolen---demonstrate the importance of improving the security of cloud systems. To increase security in the cloud environment, where resource sharing is the norm, we need to rethink existing approaches from the ground-up. This thesis analyzes the feasibility and security of trusted execution technologies as the cornerstone of secure software systems, to better protect users' data and privacy. Trusted Execution Environments (TEE), such as Intel SGX, has the potential to minimize the Trusted Computing Base (TCB), but they also introduce many challenges for adoption. Among these challenges are TEE's significant impact on applications' performance and non-trivial effort required to migrate legacy systems to run on these secure execution technologies. Other challenges include managing a trustworthy state across a distributed system and ensuring these individual machines are resilient to micro-architectural attacks. In this thesis, I first characterize the performance bottlenecks imposed by SGX and suggest optimization strategies. I then address two main adoption challenges for existing applications: managing permissions across a distributed system and scaling the SGX's mechanism for proving authenticity and integrity. I then analyze the resilience of trusted execution technologies to speculative execution, micro-architectural attacks, which put cloud infrastructure at risk. This analysis revealed a devastating security flaw in Intel's processors which is known as Foreshadow/L1TF. Finally, I propose a new architectural design for out-of-order processors which defeats all known speculative execution attacks.PHDComputer Science & EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttps://deepblue.lib.umich.edu/bitstream/2027.42/155139/1/oweisse_1.pd

Secure Cloud Storage with Client-Side Encryption Using a Trusted Execution Environment

With the evolution of computer systems, the amount of sensitive data to be stored as well as the number of threats on these data grow up, making the data confidentiality increasingly important to computer users. Currently, with devices always connected to the Internet, the use of cloud data storage services has become practical and common, allowing quick access to such data wherever the user is. Such practicality brings with it a concern, precisely the confidentiality of the data which is delivered to third parties for storage. In the home environment, disk encryption tools have gained special attention from users, being used on personal computers and also having native options in some smartphone operating systems. The present work uses the data sealing, feature provided by the Intel Software Guard Extensions (Intel SGX) technology, for file encryption. A virtual file system is created in which applications can store their data, keeping the security guarantees provided by the Intel SGX technology, before send the data to a storage provider. This way, even if the storage provider is compromised, the data are safe. To validate the proposal, the Cryptomator software, which is a free client-side encryption tool for cloud files, was integrated with an Intel SGX application (enclave) for data sealing. The results demonstrate that the solution is feasible, in terms of performance and security, and can be expanded and refined for practical use and integration with cloud synchronization services

Time Protection: the Missing OS Abstraction

Timing channels enable data leakage that threatens the security of computer systems, from cloud platforms to smartphones and browsers executing untrusted third-party code. Preventing unauthorised information flow is a core duty of the operating system, however, present OSes are unable to prevent timing channels. We argue that OSes must provide time protection in addition to the established memory protection. We examine the requirements of time protection, present a design and its implementation in the seL4 microkernel, and evaluate its efficacy as well as performance overhead on Arm and x86 processors

Measuring the Impact of Spectre and Meltdown

The Spectre and Meltdown flaws in modern microprocessors represent a new class of attacks that have been difficult to mitigate. The mitigations that have been proposed have known performance impacts. The reported magnitude of these impacts varies depending on the industry sector and expected workload characteristics. In this paper, we measure the performance impact on several workloads relevant to HPC systems. We show that the impact can be significant on both synthetic and realistic workloads. We also show that the performance penalties are difficult to avoid even in dedicated systems where security is a lesser concern