This paper investigates memory carving techniques for embedded devices. Given that cryptographic material in memory dumps makes carving techniques inefficient, we introduce a methodology to distinguish meaningful information from cryptographic material in smallsized memory dumps. The proposed methodology uses an adaptive boosting technique with statistical tests. Experimented on EMV cards, the methodology recognized 92% of meaningful information and 98% of cryptographic material.
CITATION STYLE
Gougeon, T., Barbier, M., Lacharme, P., Avoine, G., & Rosenberger, C. (2016). Memory carving in embedded devices: Separate the wheat from the chaff. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 9696, pp. 592–608). Springer Verlag. https://doi.org/10.1007/978-3-319-39555-5_32
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