Subject: TWO GUEST LECTURES by Rene Mayrhofer, 31.1 and 2.2 Date: Wed, 18 Jan 2006 15:14:11 +0200 From: Teija Kujala To: tktl-list@cs.helsinki.fi, hiitbru-all-list@cs.helsinki.fi, staff@hiit.fi       TWO GUEST LECTURES PhD Rene Mayrhofer (University of Lancaster, http://www.mayrhofer.eu.org/) will give the following two guest lectures  on Tuesday January 31th at 14:15    'Context prediction based on learning user habits: A next step towards  "smart" systems' and  on Thursday February 2nd  at 12:15.   'Context authentication: making secure communication more user-friendly' Both lectures are in room C221 (Exactum, Gustaf Hällströmin katu 2b).   Rene Mayrhofer is currently a post doc researcher at the Lancaster University  (UK) and explores the possibilities of context-based authentication in ubiquitous computing. Previously, he was with the Johannes Kepler University  of Linz (AT), where he submitted his PhD on context prediction. TITLE: Context prediction based on learning user habits: A next step towards "smart" systems ABSTRACT: Pervasive Computing is a new research area at the intersection between human/computer interaction, embedded and distributed systems and networking technology. Its aim - the disappearance of computer technology into the periphery of daily life - necessitates an adaption of systems to the respective context in which they are used. Context-based interaction is therefore one of the building blocks of Pervasive Computing. Within the last five years, a number of seminal publications on the recognition of current context from a combination of different sensors have been written. The next logical step is the prediction of future contexts, with the general concept of predicting abstract contexts to allow computer systems to proactively prepare for future situations. This high-level context prediction allows - in contrast to the autonomous prediction of individual aspects like the geographical position - to consider patterns and interrelations in the user behavior which are not apparent at the lower levels of raw sensor data. In this talk, user-centered prediction of context is analyzed and an architecture for autonomous, background context recognition and prediction is presented, building upon established methods for data based prediction. Especial attention is turned to implicit user interaction to prevent disruptions of users during their normal tasks, to continuous adaption of systems to changed conditions, and to economical use of resources. TITLE: Context authentication: making secure communication more user-friendly ABSTRACT: Mobile users depend heavily on ad-hoc connections for many, if not most, of their communication. The need for ad-hoc communication without any prior knowledge about the potential communication partners is often seen as a security risk and is certainly difficult to tackle, as is evident by the typical struggles that mobile users face when trying to connect via established communication technologies like WLAN or Bluetooth. For widespread use of secure communication in settings where no administrator can be expected to configure devices, but where users are on their own, more intuitive means of establishing secure channels are necessary. The security of such a channel usually rests on one seemingly simple property: authentication. Without proper authentication, one can not be sure who it is that the connection is made to. By solving the authentication problem, secure channels can be constructed easily by using one of the well-known standard protocols. Authentication based on context common to two or more devices or based on properties of the current context promises to make authentication more intuitive and simpler to use. WELCOME!