Biased RSA Private Keys: Origin Attribution of GCD-Factorable Keys
Biased RSA Private Keys: Origin Attribution of GCD-Factorable Keys
复制标题
有偏差的 RSA 私钥：GCD 可分解密钥的来源归属
DOI：
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发表时间：
2020
期刊：
影响因子：
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通讯作者：
Vashek Matyás
中科院分区：
文献类型：
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作者：
Adam Janovsky;Matús Nemec;P. Švenda;Peter Sekan;Vashek Matyás
2016年，Svenda等人（USENIX 2016，百万密钥问题）报告说，加密库中的实现选择允许对RSA公钥的起源进行有条件的猜测。我们将该技术扩展到两个新的场景时，不仅公共，而且私钥可用于起源属性-分析的GCD-可分解的密钥在IPv4范围内的TLS扫描和法医调查的未知来源的来源。我们从私钥中学习了几个代表偏见的代表，以从70个加密库，硬件安全模块和加密智能卡中收集的超过1.5亿个密钥来训练模型。我们的模型不仅使可区分的库组的数量增加了一倍（与Svenda等人的公钥相比）。而且在精度w.r.t.方面也提高了两倍以上。随机猜测时，一个单一的关键是分类。对于来自同一来源的至少10个密钥可用的取证场景，正确的原始库被正确识别，平均准确率为89%，而随机猜测的准确率为4%。该技术还用于识别产生GCD因子化TLS密钥的库，表明只有三组是可能的嫌疑人。
In 2016, Svenda 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 Svenda 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.
过多的 SSH 密码套件
DOI：
10.1145/2976749.2978364
发表时间：
2016
期刊：
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影响因子：
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作者：
Albrecht M
通讯作者：
Albrecht M