Today's societies are enveloped in an ever-growing telecommunication infrastructure. This infrastructure offers important opportunities for sensing and recording a multitude of human behaviors. Human mobility patterns are a prominent example of such a behavior which has been studied based on cell phone towers, Bluetooth beacons, and WiFi networks as proxies for location. However, while mobility is an important aspect of human behavior, understanding complex social systems requires studying not only the movement of individuals, but also their interactions. Sensing social interactions on a large scale is a technical challenge and many commonly used approaches-including RFID badges or Bluetooth scanning-offer only limited scalability. Here we show that it is possible, in a scalable and robust way, to accurately infer person-to-person physical proximity from the lists of WiFi access points measured by smartphones carried by the two individuals. Based on a longitudinal dataset of approximately 800 participants with ground-truth interactions collected over a year, we show that our model performs better than the current state-of-the-art. Our results demonstrate the value of WiFi signals in social sensing as well as potential threats to privacy that they imply.

In this paper we analyze the security and usability of the state-of-the-art secure mobile messenger SIGNAL. In the first part of this paper we discuss the threat model current secure mobile messengers face. In the following, we conduct a user study to examine the usability of SIGNAL's security features. Specifically, our study assesses if users are able to detect and deter man-in-the-middle attacks on the SIGNAL protocol. Our results show that the majority of users failed to correctly compare keys with their conversation partner for verification purposes due to usability problems and incomplete mental models. Hence users are very likely to fall for attacks on the essential infrastructure of today's secure messaging apps: the central services to exchange cryptographic keys. We expect that our findings foster research into the unique usability and security challenges of state-of-theart secure mobile messengers and thus ultimately result in strong protection measures for the average user.• We performed a user study with 28 participants on the usability of SIGNAL's security features, the state-ofthe-art application for secure mobile messaging.• Our results showed that 21 of 28 participants failed to Permission to freely reproduce all or part of this paper for noncommercial purposes is granted provided that copies bear this notice and the full citation on the first page. Reproduction for commercial purposes is strictly prohibited without the prior written consent of the Internet Society, the first-named author (for reproduction of an entire paper only), and the author's employer if the paper was prepared within the scope of employment.

We consider string matching with variable length gaps. Given a string T and a pattern P consisting of strings separated by variable length gaps (arbitrary strings of length in a specified range), the problem is to find all ending positions of substrings in T that match P . This problem is a basic primitive in computational biology applications. Let m and n be the lengths of P and T , respectively, and let k be the number of strings in P . We present a new algorithm achieving time O(n log k + m + α) and space O(m + A), where A is the sum of the lower bounds of the lengths of the gaps in P and α is the total number of occurrences of the strings in P within T . Compared to the previous results this bound essentially achieves the best known time and space complexities simultaneously. Consequently, our algorithm obtains the best known bounds for almost all combinations of m, n, k, A, and α. Our algorithm is surprisingly simple and straightforward to implement. We also present algorithms for finding and encoding the positions of all strings in P for every match of the pattern. * An extended abstract of this paper appeared in proceedings of the 17th Symposium on String Processing and Information Retrieval.

Let d ≥ 3 be a fixed integer. We give an asympotic formula for the expected number of spanning trees in a uniformly random d-regular graph with n vertices. (The asymptotics are as n → ∞, restricted to even n if d is odd.) We also obtain the asymptotic distribution of the number of spanning trees in a uniformly random cubic graph, and conjecture that the corresponding result holds for arbitrary (fixed) d. Numerical evidence is presented which supports our conjecture.

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