Selected papers of the
ACM SAC 2006 TRECK Track
Detailed information about the ACM SAC 2006 ‘Trust, Recommendations, Evidence and other Collaboration Know-how’ (TRECK) track is available at the TRECK website.
Aims and scope
Computational models of trust and mechanisms based on the human notion of trust have been gaining momentum. One reason for this is that traditional security mechanisms are challenged by open, large scale and decentralised environments. The use of an explicit trust management component goes beyond security though.
The goal of the ACM SAC 2006 TRECK track remains to review the set of applications that benefit from the use of computational trust. Computational trust has been used in reputation systems, risk management, collaborative filtering, social/business networking services, dynamic coalitions and virtual organisations. The TRECK track covers all computational trust applications, especially those used in the real world.
Topics of interest
The topics of interest include, but are not limited to:
- Recommender and reputation systems
- Trust-enhanced collaborative applications
- Tangible guarantees given by formal models of trust and risk
- Trust metrics assessment and threat analysis
- Pervasive computational trust and use of context-aware features
- Trade-off between privacy and trust
- Trust/risk-based security frameworks
- Automated collaboration and trust negotiation
- Trust in peer-to-peer systems
- Technical trust evaluation, especially at the identity level
- Impacts of social networks on computational trust
- Evidence gathering and management
- Real-world applications, running prototypes and advanced simulations
- Applicability in large-scale, open and decentralised environments
- Legal and economic aspects related to the use of trust engines
- User-studies and user interfaces of computational trust applications
Track program chairs
- Jean-Marc Seigneur, Trinity College Dublin, Ireland
- Christian Damsgaard Jensen, Technical University of Denmark
Track program committee
- Jean-Marc Seigneur, Trinity College Dublin, Ireland
- Christian D. Jensen, Technical University of Denmark, Denmark
- Stephen Marsh, National Research Council, Canada
- Tanko Ishaya, University of Hull, United Kingdom
- Lalana Kagal, University of Maryland Baltimore County, USA
- Stephane Lo Presti, University of Southampton, United Kingdom
- Paolo Avesani, University of Trento, Italy
- Scott Flinn, National Research Council, Canada
- Charles A. Shoniregun, University of East London, United Kingdom
- Michael Kinateder, University of Stuttgart, Germany
- Sviatoslav Braynov, University of Illinois at Springfield, USA
- Seamus Moloney, Nokia, Finland
- Yanjun Zuo, University of Arkansas at Fayetteville, USA
- Darren P. Mundy, University of Hull, United Kingdom
- Laurence Vignollet, Université de Savoie, France
- Rino Falcone, CNR Institute of Cognitive Sciences and Technologies, Italy
- Paolo Massa, University of Trento, Italy
- Cai-Nicolas Ziegler, University of Freiburg, Germany
- Ciarán Bryce, University of Geneva, Switzerland
- Bruno Crispo, Vrije Universiteit Amsterdam, The Netherlands
- Stefan Weber, Trinity College Dublin, Ireland
- Javier Lopez, University of Malaga, Spain
- Damien Weldon, LoanPerformance, USA
- Ayman Kassi, American University of Beirut, Lebanon
- Sotirios Terzis, University of Strathclyde, United Kingdom
- Hugo Miranda, University of Lisbon, Portugal
- Tobias Mahler, University of Oslo, Norway
- Girish Suryanarayana, University of California, Irvine, USA
- Hiroyuki Kasai, NTT DoCoMo, Japan
- Alex Logvynovskiy, London South Bank University, United Kingdom
