Memorias de investigación
Otras publicaciones:
RELOAD+REFRESH: Abusing Cache Replacement Policies to Perform Stealthy Cache Attacks
Año:2019

Áreas de investigación
  • Tecnología electrónica y de las comunicaciones

Datos
Descripción
Caches have become the prime method for unintended information extraction across logical isolation boundaries. Even Spectre and Meltdown rely on the cache side channel, as it provides great resolution and is widely available on all major CPU platforms. As a consequence, several methods to stop cache attacks by detecting them have been proposed. Detection is strongly aided by the fact that observing cache activity of co-resident processes is not possible without altering the cache state and thereby forcing evictions on the observed processes. In this work, we show that this widely held assumption is incorrect. Through clever usage of the cache replacement policy it is possible to track a victims process cache accesses without forcing evictions on the victim's data. Hence, online detection mechanisms that rely on these evictions can be circumvented as they do not detect be the introduced RELOAD+REFRESH attack. The attack requires a profound understanding of the cache replacement policy. We present a methodology to recover the replacement policy and apply it to the last five generations of Intel processors. We further show empirically that the performance of RELOAD+REFRESH on cryptographic implementations is comparable to that of other widely used cache attacks, while its detectability becomes extremely difficult, due to the negligible effect on the victims cache access pattern.
Internacional
Si
Entidad
Lugar
Páginas
Referencia/URL
https://arxiv.org/abs/1904.06278
Tipo de publicación
Pre-Print (Under review for USENIX 2020)

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Participantes

Grupos de investigación, Departamentos, Centros e Institutos de I+D+i relacionados
  • Creador: Grupo de Investigación: Laboratorio de Sistemas Integrados (LSI)
  • Departamento: Ingeniería Electrónica
  • Centro o Instituto I+D+i: Centro de Investigación en Simulación Computacional