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We propose a new method for automatic generation of secrecy amplification protocols for wireless sensor networks, utilizing evolutionary algorithms. We were able to rediscover all published protocols for secrecy amplification we are aware of, and found a new protocol that outperforms the existing ones. An alternative construction of secrecy amplification protocols with a comparable fraction of secure links to that of the original "node-oriented" approach was also designed. This new construction exhibits only linear (instead of exponential) increase of necessary messages when the number of communication neighbours grows. This efficient protocol can significantly reduce the sensor battery power consumption because of the decreased message transmission rate. We used a combination of linear genetic programming and a network simulator in this work.

We measure the popularity of cryptographic libraries in large datasets of RSA public keys. We do so by improving a recently proposed method based on biases introduced by alternative implementations of prime selection in different cryptographic libraries. We extend the previous work by applying statistical inference to approximate a share of libraries matching an observed distribution of RSA keys in an inspected dataset (e.g., Internet-wide scan of TLS handshakes). The sensitivity of our method is sufficient to detect transient events such as a periodic insertion of keys from a specific library into Certificate Transparency logs and inconsistencies in archived datasets.\ud \ud We apply the method on keys from multiple Internet-wide scans collected in years 2010 through 2017, on Certificate Transparency logs and on separate datasets for PGP keys and SSH keys. The results quantify a strong dominance of OpenSSL with more than 84% TLS keys for Alexa 1M domains, steadily increasing since the first measurement. OpenSSL is even more popular for GitHub client-side SSH keys, with a share larger than 96%. Surprisingly, new certificates inserted in Certificate Transparency logs on certain days contain more than 20% keys most likely originating from Java libraries, while TLS scans contain less than 5% of such keys.\ud \ud Since the ground truth is not known, we compared our measurements with other estimates and simulated different scenarios to evaluate the accuracy of our method. To our best knowledge, this is the first accurate measurement of the popularity of cryptographic libraries not based on proxy information like web server fingerprinting, but directly on the number of observed unique keys

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In our paper, we analyze possibilities to generate true random data in mobile devices such as mobile phones or pocket computers. We show how to extract arguably true random data with a probability distribution = 2 −64 close to the uniform distribution in the trace distance. To postprocess the random data acquired from the camera we use a randomness extractor based on the Carter-Wegman universal 2 families of hashing functions. We generate the data at the bit rate approximatively 36 bits per second -we used such a low bit rate only to allow statistical testing at a reasonable level of confidence.