Biased RSA private keys: Origin attribution of GCD-factorable keys
Identifikátory výsledku
Kód výsledku v IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14330%2F20%3A00115914" target="_blank" >RIV/00216224:14330/20:00115914 - isvavai.cz</a>
Výsledek na webu
<a href="https://link.springer.com/chapter/10.1007%2F978-3-030-59013-0_25" target="_blank" >https://link.springer.com/chapter/10.1007%2F978-3-030-59013-0_25</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/978-3-030-59013-0_25" target="_blank" >10.1007/978-3-030-59013-0_25</a>
Alternativní jazyky
Jazyk výsledku
angličtina
Název v původním jazyce
Biased RSA private keys: Origin attribution of GCD-factorable keys
Popis výsledku v původním jazyce
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.
Název v anglickém jazyce
Biased RSA private keys: Origin attribution of GCD-factorable keys
Popis výsledku anglicky
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.
Klasifikace
Druh
D - Stať ve sborníku
CEP obor
—
OECD FORD obor
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Návaznosti výsledku
Projekt
—
Návaznosti
S - Specificky vyzkum na vysokych skolach
Ostatní
Rok uplatnění
2020
Kód důvěrnosti údajů
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Údaje specifické pro druh výsledku
Název statě ve sborníku
Computer Security – ESORICS 2020
ISBN
9783030590123
ISSN
0302-9743
e-ISSN
—
Počet stran výsledku
20
Strana od-do
505-524
Název nakladatele
Springer
Místo vydání
Cham, Switzerland
Místo konání akce
Cham, Switzerland
Datum konání akce
1. 1. 2020
Typ akce podle státní příslušnosti
CST - Celostátní akce
Kód UT WoS článku
—