A small and adaptive coprocessor for information flow tracking in ARM SoCs

Muhammad Abdul Wahab 1 Pascal Cotret 2 Mounir Nasr Allah 3 Guillaume Hiet 3 Arnab Kumar Biswas 4 Vianney Lapotre 4 Gogniat Guy 4
1 IETR - Institut d'Electronique et de Télécommunications de Rennes
2 Chercheur indépendant
3 CIDRE - Confidentialité, Intégrité, Disponibilité et Répartition
CentraleSupélec, Inria Rennes – Bretagne Atlantique , IRISA-D1 - SYSTÈMES LARGE ÉCHELLE
4 Lab-STICC_UBS_CACS_MOCS
Lab-STICC - Laboratoire des sciences et techniques de l'information, de la communication et de la connaissance
Abstract : DIFT (Dynamic Information Flow Tracking) has been a hot topic for more than a decade. Unfortunately , existing hardware DIFT approaches have not been widely used neither by research community nor by hardware vendors. It is due to two major reasons: current hardware DIFT solutions lack support for multi-threaded applications and implementations for hardcore processors. This work addresses both issues by introducing an approach with some unique features: DIFT for multi-threaded software, virtual memory protection (rather than physical memory as in related works) and Linux kernel support using an information flow monitor called RFBlare. These goals are accomplished by taking advantage of a notable feature of ARM CoreSight components (context ID) combined with a custom DIFT coprocessor and RFBlare. The communication time overhead, major source of slowdown in total DIFT time overhead, is divided by a factor 3.8 compared to existing solutions with similar software constraints as in this work. The area overhead of this work is lower than 1% and power overhead is 16.2% on a middle-class Xilinx Zynq SoC.
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https://hal.archives-ouvertes.fr/hal-01911619
Contributor : Pascal Cotret <>
Submitted on : Tuesday, November 6, 2018 - 10:04:49 PM
Last modification on : Tuesday, November 12, 2019 - 3:58:13 PM
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Muhammad Abdul Wahab, Pascal Cotret, Mounir Nasr Allah, Guillaume Hiet, Arnab Kumar Biswas, et al.. A small and adaptive coprocessor for information flow tracking in ARM SoCs. ReConFig 2018 - International Conference on Reconfigurable Computing and FPGAs, Dec 2018, Cancun, Mexico. pp.1-17, ⟨10.1109/reconfig.2018.8641695⟩. ⟨hal-01911619⟩

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