Demystifying AMD SEV Performance Penalty for NFV Deployment

<p dir="ltr">Network Function Virtualization (NFV) has shifted communication networks towards more adaptable software solutions, but this transition raises new security concerns, particularly in public cloud deployments. While Intel’s Software Guard Extensions (SGX) offers a potential remedy, it requires complex application adaptations. This paper investigates AMD’s Secure Encrypted Virtualization (SEV) as an alternative approach for securing NFV. SEV encrypts virtual machine (VM) memory, protecting it from threats, including those at the hypervisor level, without requiring application modifications. We explore the practicality and performance implications of executing native Network Function (NF) implementations in AMD SEV-SNP, the latest iteration of SEV at the time of writing this paper. Our study focuses on running an unmodified Snort NF within SEV. Results show an average performance penalty of approximately 20% across various traffic and packet configurations, showing a trade-off between security and performance that may or may not be acceptable for different NFV deployments.

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Publication Details

Published
2024-12-20
DOI
https://doi.org/10.1145/3711650.3711651
Citations
3
Primary Topic
Advanced Memory and Neural Computing
Type
article
Field-Weighted Citation Impact
0.63
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article

Demystifying AMD SEV Performance Penalty for NFV Deployment

Syafiq Al Atiiq, Aris Cahyadi Risdianto
3 citations
Advanced Memory and Neural Computing
0.63
article

Demystifying AMD SEV Performance Penalty for NFV Deployment

Syafiq Al Atiiq, Aris Cahyadi Risdianto
article en
3 citations

Abstract

<p dir="ltr">Network Function Virtualization (NFV) has shifted communication networks towards more adaptable software solutions, but this transition raises new security concerns, particularly in public cloud deployments. While Intel’s Software Guard Extensions (SGX) offers a potential remedy, it requires complex application adaptations. This paper investigates AMD’s Secure Encrypted Virtualization (SEV) as an alternative approach for securing NFV. SEV encrypts virtual machine (VM) memory, protecting it from threats, including those at the hypervisor level, without requiring application modifications. We explore the practicality and performance implications of executing native Network Function (NF) implementations in AMD SEV-SNP, the latest iteration of SEV at the time of writing this paper. Our study focuses on running an unmodified Snort NF within SEV. Results show an average performance penalty of approximately 20% across various traffic and packet configurations, showing a trade-off between security and performance that may or may not be acceptable for different NFV deployments.

Singapore Institute of Technology (SG), Lund University (SE)
Openalex Percentile: Top 30%
Advanced Memory and Neural Computing
0.63
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Demystifying AMD SEV Performance Penalty for NFV Deployment — Syafiq Al Atiiq, Aris Cahyadi Risdianto · (2024) | TGRS Research Map | TGRS