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public:papers:acsac2017 [2017-12-04 20:14] – [Q&A section] xnemec1public:papers:acsac2017 [2022-10-12 08:52] (current) – xsvenda
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   * Conference page: [[https://www.acsac.org/2017/ | ACSAC 2017]] | [[https://www.acsac.org/2017/openconf/modules/request.php?module=oc_program&action=summary.php&id=106 | Paper page]]   * Conference page: [[https://www.acsac.org/2017/ | ACSAC 2017]] | [[https://www.acsac.org/2017/openconf/modules/request.php?module=oc_program&action=summary.php&id=106 | Paper page]]
   * Download author pre-print of the paper: {{ :public:papers:acsac2017_nemec_rsa_fingerprints.pdf | pdf}}   * Download author pre-print of the paper: {{ :public:papers:acsac2017_nemec_rsa_fingerprints.pdf | pdf}}
-  * Download presentation: {{ fixme | pdf}}+  * Download presentation: {{ :public:papers:acsac-nemec-handout.pdf | Handout-PDF}} | {{ :public:papers:acsac-nemec.pdf | Conference-PDF }}
  
 **Bibtex (regular paper)** **Bibtex (regular paper)**
  
   @inproceedings{2017-acsac-nemec,   @inproceedings{2017-acsac-nemec,
-    Author        = {Matus Nemec and Dusan Klinec and Petr Svenda and Peter Sekan and Vashek Matyas}, +    author = {Nemec, Matus and Klinec, Dusan and Svenda, Petr and Sekan, Peter and Matyas, Vashek}, 
-    Title         = {Measuring Popularity of Cryptographic Libraries in Internet-Wide Scans}, +    title = {Measuring Popularity of Cryptographic Libraries in Internet-Wide Scans}, 
-    BookTitle     = {Proceedings of the 33rd Annual Computer Security Applications Conference (ACSAC'2017)}, +    booktitle = {Proceedings of the 33rd Annual Computer Security Applications Conference}, 
-    Year          = {2017}, +    series = {ACSAC 2017}, 
-    Pages         = {??--??}, +    year = {2017}, 
-    ISBN          = {??}, +    isbn = {978-1-4503-5345-8}, 
-    Publisher     = {ACM}+    pages = {162--175}, 
 +    url = {http://doi.acm.org/10.1145/3134600.3134612}, 
 +    doi = {10.1145/3134600.3134612}, 
 +    publisher = {ACM}
   }   }
  
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   * Measurement (classification) tool: [[https://github.com/crocs-muni/classifyRSAkey | GitHub link]]   * Measurement (classification) tool: [[https://github.com/crocs-muni/classifyRSAkey | GitHub link]]
-  * RSA keys from reference libraries: [[https://drive.google.com/drive/u/3/folders/0B0PpUrsKytcyMllkUHJ0RkZkdzA | Google Drive link]]+  * {{fa>database}}\_//// [[https://owncloud.cesnet.cz/index.php/s/Ihhw3BKKzKTaxB9|Dataset of all collected RSA keys (39GB)]]
   * Data processing (TLS, PGP): [[https://github.com/crocs-muni/acsac2017-data-tools | GitHub link]]   * Data processing (TLS, PGP): [[https://github.com/crocs-muni/acsac2017-data-tools | GitHub link]]
   * Data processing (Certificate Transparency): [[https://github.com/crocs-muni/acsac2017-certificate-transparency-java | GitHub link]]   * Data processing (Certificate Transparency): [[https://github.com/crocs-muni/acsac2017-certificate-transparency-java | GitHub link]]
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 {{:public:papers:acsac2017_dendrogram.png?600|}} {{:public:papers:acsac2017_dendrogram.png?600|}}
 +
 +==Q: Does popularity of libraries change in time?==
 +A: Yes, for one, the number of OpenSSL keys increases significantly.
 +{{:public:papers:acsac2017_intime.png?800|}}
  
 ==Q: I want to know the popularity of library X, why wasn't it included? == ==Q: I want to know the popularity of library X, why wasn't it included? ==
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 A: The features extracted from the keys are not unique. Different (groups of) libraries can produce keys with the same features. Only the distribution of the features differs, as illustrated here: A: The features extracted from the keys are not unique. Different (groups of) libraries can produce keys with the same features. Only the distribution of the features differs, as illustrated here:
  
 +{{:public:papers:acsac2017_reference.png?800|}}
  
 ==Q: What is the accuracy of the measurement?== ==Q: What is the accuracy of the measurement?==
 A: We performed simulations to determine the accuracy. The expected error of the measurement was within 1 percentage point of the estimation (e.g., OpenSSL being estimated at 70% means that we expect it to be between 69% and 71%). The error might be larger in some cases, however the ground truth is not always known. Our estimation of ROCA vulnerable keys in a PGP dataset was at 0.10%, that is within 0.02 percentage points from the correct proportion found by a much more reliable method specific to the ROCA keys. A: We performed simulations to determine the accuracy. The expected error of the measurement was within 1 percentage point of the estimation (e.g., OpenSSL being estimated at 70% means that we expect it to be between 69% and 71%). The error might be larger in some cases, however the ground truth is not always known. Our estimation of ROCA vulnerable keys in a PGP dataset was at 0.10%, that is within 0.02 percentage points from the correct proportion found by a much more reliable method specific to the ROCA keys.