Auflistung nach Autor:in "Uellenbeck, Sebastian"
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- KonferenzbeitragContinuous authentication on mobile devices by analysis of typing motion behavior(Sicherheit 2014 – Sicherheit, Schutz und Zuverlässigkeit, 2014) Gascon, Hugo; Uellenbeck, Sebastian; Wolf, Christopher; Rieck, KonradSmartphones have become the standard personal device to store private or sensitive information. Widely used as every day gadget, however, they are susceptible to get lost or stolen. To protect information on a smartphone from being physically accessed by attackers, a lot of authentication methods have been proposed in recent years. Each one of them suffers from certain drawbacks, either they are easy to circumvent, vulnerable against shoulder surfing attacks, or cumbersome to use. In this paper, we present an alternative approach for user authentication that is based on the smartphone's sensors. By making use of the user's biometrical behavior while entering text into the smartphone, we transparently authenticate the user in an ongoing-fashion. In a field study, we asked more than 300 participants to enter some short sentences into a smartphone while all available sensor events were recorded to determine a typing motion fingerprint of the user. After the proper feature extraction, a machine learning classifier based on Support Vector Machines (SVM) is used to identify the authorized user. The results of our study are twofold: While our approach is able to continuously authenticate some users with high precision, there also exist participants for which no accurate motion fingerprint can be learned. We analyze these difference in detail and provide guidelines for similar problems.
- KonferenzbeitragGraphneighbors: hampering shoulder-surfing attacks on smartphones(Sicherheit 2014 – Sicherheit, Schutz und Zuverlässigkeit, 2014) Altiok, Irfan; Uellenbeck, Sebastian; Holz, ThorstenToday, smartphones are widely used and they already have a growing market share of more than 70 % according to recent studies. These devices often contain sensitive data like contacts, pictures, or even passwords that can easily be accessed by an attacker if the phone is not locked. Since they are mobile and used as everyday gadgets, they are susceptible to get lost or stolen. Hence, access control mechanisms such as user authentication are required to prevent the data from being accessed by an attacker. However, commonly used authentication mechanisms like PINs, passwords, and Android Unlock Patterns suffer from the same weakness: they are all vulnerable against different kinds of attacks, most notably shoulder-surfing. A promising strategy to prevent shoulder-surfing is to only enter a derivation of the secret during the authentication phase. In this paper, we present a novel authentication mechanism based on the concept of graphical neighbors to hamper shoulder-surfing attacks. Results of a usability evaluation with 100 participants show that our implementation called GRAPHNEIGHBORS is applicable in comparison to commonly used authentication mechanisms.