Other formats:
BibTeX
LaTeX
RIS
@inproceedings{1669278,
author = {Janovský, Adam and Nemec, Matúš and Švenda, Petr and Sekan, Peter and Matyáš, Václav},
address = {Cham, Switzerland},
booktitle = {Computer Security – ESORICS 2020},
doi = {http://dx.doi.org/10.1007/978-3-030-59013-0_25},
editor = {Liqun Chen and Ninghui Li and Kaitai Liang and Steve Schneider},
keywords = {Cryptographic library; RSA factorization; Measurement; RSA key classification; Statistical model},
howpublished = {tištěná verze "print"},
language = {eng},
location = {Cham, Switzerland},
isbn = {978-3-030-59012-3},
pages = {505-524},
publisher = {Springer},
title = {Biased RSA private keys: Origin attribution of GCD-factorable keys},
url = {https://link.springer.com/chapter/10.1007%2F978-3-030-59013-0_25},
year = {2020}
}
TY - JOUR
ID - 1669278
AU - Janovský, Adam - Nemec, Matúš - Švenda, Petr - Sekan, Peter - Matyáš, Václav
PY - 2020
TI - Biased RSA private keys: Origin attribution of GCD-factorable keys
PB - Springer
CY - Cham, Switzerland
SN - 9783030590123
KW - Cryptographic library
KW - RSA factorization
KW - Measurement
KW - RSA key classification
KW - Statistical model
UR - https://link.springer.com/chapter/10.1007%2F978-3-030-59013-0_25
L2 - https://link.springer.com/chapter/10.1007%2F978-3-030-59013-0_25
N2 - In 2016, Švenda et al. (USENIX 2016, The Million-key Question) reported that the implementation choices in cryptographic libraries allow for qualified guessing about the origin of public RSA keys. We extend the technique to two new scenarios when not only public but also private keys are available for the origin attribution -- analysis of a source of GCD-factorable keys in IPv4-wide TLS scans and forensic investigation of an unknown source. We learn several representatives of the bias from the private keys to train a model on more than 150 million keys collected from 70 cryptographic libraries, hardware security modules and cryptographic smartcards. Our model not only doubles the number of distinguishable groups of libraries (compared to public keys from Švenda et al.) but also improves more than twice in accuracy w.r.t. random guessing when a single key is classified. For a forensic scenario where at least 10 keys from the same source are available, the correct origin library is correctly identified with average accuracy of 89\% compared to 4\% accuracy of a random guess. The technique was also used to identify libraries producing GCD-factorable TLS keys, showing that only three groups are the probable suspects.
ER -
JANOVSKÝ, Adam, Matúš NEMEC, Petr ŠVENDA, Peter SEKAN and Václav MATYÁŠ. Biased RSA private keys: Origin attribution of GCD-factorable keys. In Liqun Chen and Ninghui Li and Kaitai Liang and Steve Schneider. \textit{Computer Security – ESORICS 2020}. Cham, Switzerland: Springer, 2020, p.~505-524. ISBN~978-3-030-59012-3. Available from: https://dx.doi.org/10.1007/978-3-030-59013-0\_{}25.
|
