Refereed journal articles

Small, mobile devices or infrastructure devices without user interfaces, such as Bluetooth headsets, wireless LAN access points, or printers, often need to communicate securely over wireless networks. Active attacks can only be prevented by authenticating wireless communication, which is problematic when devices do not have any a priori information about each other. In this article, we describe three different authentication methods for device-to-device authentication based on sensor data from various physical out-of-band channels: shaking devices together, authentication based on spatial reference, and transmission via visible laser.

Spontaneous interaction in wireless ad-hoc networks is often desirable not only between users or devices in direct contact, but also with devices that are accessible only via a wireless network. Secure communication with such devices is difficult because of the required authentication, which is often either password- or certificate-based. An intuitive alternative is context-based authentication, where device authenticity is verified by shared context, and often by direct physical evidence. Devices that are physically separated cannot experience the same context and thus cannot benefit directly from context authentication. We introduce a context authentication proxy that is pre-authenticated with one of the devices and can authenticate with the other by shared context. This concept is applicable to a wide range of application scenarios, context sensing technologies, and trust models. We show its practicality in an implementation for setting up IPSec connections based on spatial reference. Our specific scenario is ad-hoc access of mobile devices to secure 802.11 WLANs using a mobile device as authentication proxy. A user study shows that our method and implementation are intuitive to use and compare favourably to a standard, password-based approach.

Current mobile devices like mobile phones or personal digital assistants have become more and more powerful; they already offer features that only few users are able to exploit to their whole extent. With a number of upcoming mobile multimedia applications, ease of use becomes one of the most important aspects. One way to improve usability is to make devices aware of the user’s context, allowing them to adapt to the user instead of forcing the user to adapt to the device. Our work is taking this approach one step further by not only reacting to the current context, but also predicting future context, hence making the devices proactive. Mobile devices are generally suited well for this task because they are typically close to the user even when not actively in use. This allows such devices to monitor the user context and act accordingly, like automatically muting ring or signal tones when the user is in a meeting or selecting audio, video or text communication depending on the user’s current occupation. This article presents an architecture that allows mobile devices to continuously recognize current and anticipate future user context. The major challenges are that context recognition and prediction should be embedded in mobile devices with limited resources, that learning and adaptation should happen on-line without explicit training phases and that user intervention should be kept to a minimum with non-obtrusive user interaction. To accomplish this, the presented architecture consists of four major parts: feature extraction, classification, labeling and prediction. The available sensors provide a multi-dimensional, highly heterogeneous input vector as input to the classification step, realized by data clustering. Labeling associates recognized context classes with meaningful names specified by the user, and prediction allows forecasting future user context for proactive behavior.

Abstract—Mobile Peer-to-Peer (P2P) computing applications involve collections of heterogeneous and resource-limited devices (such as PDAs or embedded sensor-actuator systems), typically operated in ad-hoc completely decentralized networks and without requiring dedicated infrastructure support. Short-range wireless communication technologies together with P2P networking capabilities on mobile devices are responsible for a proliferation of such applications, yet these applications are often complex and monolithic in nature due to the lack of lightweight component/container support in these resource-constrained devices. A threatening field of application is “smart space” control, i.e. software architectures to control various home appliances and embedded home facilities in a personalized, spontaneous and intuitive way. Future home environments are expected to be highly populated by ubiquitous computing technology, allowing to integrate various aspects of home activities seamlessly into walls, floors, furniture, appliances, and even clothing – thus raising the need for lightweight, versatile and component based software architectures to harness such technology rich environments.

In this paper we describe our lightweight software component model P2Pcomp that addresses the development needs for mobile P2P applications. An abstract, flexible, and high-level communication mechanism among components is developed via a ports concept, supporting protocol independence, location independence, and (a)synchronous invocations; dependencies are not hard-coded in the components, but can be defined at deployment or runtime, providing late-binding and dynamic rerouteability capabilities. Peers can elect to provide services as well as consume them, services can migrate between containers, and services are ranked to support Quality-of-Service choices. Our lightweight container realization leverages the OSGi platform and can utilize various P2P communication mechanisms such as JXTA. A “smart space” application scenario demonstrates how P2Pcomp supports flexible and highly tailorable mobile P2P applications.

Secure association of mobile devices is difficult because of inherently insecure wireless communication and lack of a priori information about communication partners during spontaneous interaction. This article introduces simultaneous shaking as a method to effect shared movement, which devices sense independently with embedded accelerometers and use as a fuzzy shared secret for mutual authentication. Two methods, ShaVe and ShaCK, combine cryptographic protocols with accelerometer data analysis to the effect of generating authenticated, secret keys. ShaVe generates a key using conservative key exchange methods and verifies device authenticity by comparing the similarity of sensor data streams, while ShaCK interactively generates cryptographic keys directly out of sufficiently similar sensor data streams. An evaluation of the classification algorithms used in the methods shows that simultaneous shaking of two devices can be robustly separated from other concurrent movement of a pair of devices, with a false negative rate of under 12%. An on-line user experiment further shows that the pairing method is intuitive and that most users can apply it successfully without being shown how to hold and move devices for best effect.