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Article Dans Une Revue Digital Investigation Année : 2022

A forensic analysis of the Google Home: repairing compressed data without error correction

David Naccache
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  • PersonId : 928358
Hadrien Barral
Fabien Thomas-Brans
  • Fonction : Auteur
Matthieu Regnery
  • Fonction : Auteur
Rémi Géraud-Stewart
Thibaut Heckmann
Thomas Souvignet
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  • PersonId : 950005

Résumé

This paper provides a detailed explanation of the steps taken to extract and repair a Google Home's internal data. Starting with reverse engineering the hardware of a commercial off-the-shelf Google Home, internal data is then extracted by desoldering and dumping the flash memory. As error correction is performed by the CPU using an undisclosed method, a new alternative method is shown to repair a corrupted SquashFS filesystem, under the assumption of a single or double bitflip per gzip-compressed fragment. Finally, a new method to handle multiple possible repairs using three-valued logic is presented.
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Dates et versions

hal-03932223 , version 1 (10-01-2023)

Licence

Paternité - Pas d'utilisation commerciale

Identifiants

  • HAL Id : hal-03932223 , version 1

Citer

David Naccache, Hadrien Barral, Georges-Axel Jaloyan, Fabien Thomas-Brans, Matthieu Regnery, et al.. A forensic analysis of the Google Home: repairing compressed data without error correction. Digital Investigation, 2022, 42 (00), pp.00. ⟨hal-03932223⟩
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