Rollback and Forking Detection for Trusted Execution Environments Using Lightweight Collective Memory
Brandenburger M, Cachin C, Lorenz M, Kapitza R (2017)
Publication Type: Conference contribution
Publication year: 2017
Publisher: Institute of Electrical and Electronics Engineers Inc.
Pages Range: 157-168
Conference Proceedings Title: Proceedings - 47th Annual IEEE/IFIP International Conference on Dependable Systems and Networks, DSN 2017
Event location: Denver, CO
ISBN: 9781538605417
DOI: 10.1109/DSN.2017.45
Abstract
Novel hardware-aided trusted execution environments, as provided by Intel's Software Guard Extensions (SGX), enable to execute applications in a secure context that enforces confidentiality and integrity of the application state even when the host system is misbehaving. While this paves the way towards secure and trustworthy cloud computing, essential system support to protect persistent application state against rollback and forking attacks is missing. In this paper we present LCM-a lightweight protocol to establish a collective memory amongst all clients of a remote application to detect integrity and consistency violations. LCM enables the detection of rollback attacks against the remote application, enforces the consistency notion of fork-linearizability and notifies clients about operation stability. The protocol exploits the trusted execution environment, complements it with simple client-side operations, and maintains only small, constant storage at the clients. This simplifies the solution compared to previous approaches, where the clients had to verify all operations initiated by other clients. We have implemented LCM and demonstrated its advantages with a key-value store application. The evaluation shows that it introduces low network and computation overhead, in particular, a LCM-protected key-value store achieves 0.72x-0.98x of an SGX-secured key-value store throughput.
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Switzerland (CH)
Germany (DE)How to cite
APA:
Brandenburger, M., Cachin, C., Lorenz, M., & Kapitza, R. (2017). Rollback and Forking Detection for Trusted Execution Environments Using Lightweight Collective Memory. In Proceedings - 47th Annual IEEE/IFIP International Conference on Dependable Systems and Networks, DSN 2017 (pp. 157-168). Denver, CO, US: Institute of Electrical and Electronics Engineers Inc..
MLA:
Brandenburger, Marcus, et al. "Rollback and Forking Detection for Trusted Execution Environments Using Lightweight Collective Memory." Proceedings of the 47th Annual IEEE/IFIP International Conference on Dependable Systems and Networks, DSN 2017, Denver, CO Institute of Electrical and Electronics Engineers Inc., 2017. 157-168.
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