Revision as of 14:40, 16 November 2010

Trust in Interpersonal, Social, and Sensor Networks

Trust relationships occur naturally in many diverse contexts such as ecommerce, social interactions, social networks, ad hoc mobile networks, distributed systems, decision-support systems, (semantic) sensor web, emergency response scenarios, etc. As the connections and interactions between humans and/or machines (collectively called agents) evolve, and as the agents providing content and services become increasingly removed from the agents that consume them, miscreants attempt to corrupt, subvert or attack existing infrastructure. This in turn calls for support for robust trust inference (e.g., gleaning, aggregation, propagation) and update (also called trust management). Unfortunately, there is neither a universal notion of trust that is applicable to all domains nor a clear explication of its semantics in many situations. Because Web, social networking and sensor information often provide complementary and overlapping information about an activity or event that are critical for overall situational awareness, there is a unique need for developing an understanding of and techniques for managing trust that span all these information channels. Currently, we are pursuing research on trust and trustworthiness issues in interpersonal, social, and sensor networks, to potentially unify and integrate them for exploiting their complementary strengths.

Research Topics

A Local Qualitative Approach to Referral and Functional Trust

Trust and confidence are becoming key issues in diverse applications such as ecommerce, social networks, semantic sensor web, semantic web information retrieval systems, etc. Both humans and machines use some form of trust to make informed and reliable decisions before acting. In this research, we reviewed drawbacks of existing approaches to trust and then proposed a new local framework to explore two different kinds of trust among agents, namely, referral trust and functional trust. These have been modeled using local partial orders, to enable qualitative trust personalization. The proposed approach formalizes reasoning with trust, distinguishing between direct and inferred trust. It is also capable of dealing with general trust networks with cycles.

Trust and Trustworthiness Issues for Social and Sensor Web

We explore research issues relevant to trust in social/sensor networks and interactions. We advocate a balanced, iterative approach to trust that marries both theory and practice. On the theoretical side, we investigate models of trust to analyze and specify the nature of trust and trust computation. On the practical side, we propose to uncover aspects that provide a basis for trust formation and techniques to extract trust information from concrete social/sensor networks and interactions. We expect the development of formal models of trust and techniques to glean trust information from social media and sensor web to be fundamental enablers for applying semantic web technologies to trust management.

Trust Ontology

While we all have an intuitive notion of trust, the literature is scattered with a wide assortment of differing definitions and descriptions; often these descriptions are highly dependent on a single domain or application of interest. In addition, they often discuss orthogonal aspects of trust while continuing to use the general term “trust”. In order to make sense of the situation, we have developed an ontology of trust that integrates and relates its various aspects into a single model.

People

• Pramod Anantharam
• Cory Henson
• T.K. Prasad
• Amit Sheth

Publications

• Trust Model for Semantic Sensor and Social Networks: A Preliminary Report
  • Pramod Anantharam,Cory Henson,Krishnaprasad Thirunarayan and Amit Sheth
  • in Proceedings of 2010 National Aerospace & Electronics Conference (NAECON), Dayton Ohio, July 14-16th, 2010
• Provenance Aware Linked Sensor Data
  • Harshal Patni, Satya S. Sahoo, Cory Henson, and Amit Sheth
  • In: Proceedings of 2010 2nd Workshop on Trust and Privacy on the Social and Semantic Web, Co-located with ESWC, Heraklion Greece, 30th May - 03 June 2010.
• Some Trust Issues in Social Networks and Sensor Networks
  • Krishnaprasad Thirunarayan, Pramod Anantharam, Cory Henson, and Amit Sheth
  • In: Proceedings of 2010 International Symposium on Collaborative Technologies and Systems (CTS 2010), Chicago, IL, May 17-21, 2010.
• A Local Qualitative Approach to Referral and Functional Trust
  • Krishnaprasad Thirunarayan, Dharan Althuru, Cory Henson, and Amit Sheth
  • In: Proceedings of the The 4th Indian International Conference on Artificial Intelligence (IICAI-09), pp. 574-588, December 2009.
• Situation Awareness via Abductive Reasoning for Semantic Sensor Data: A Preliminary Report
  • Krishnaprasad Thirunarayan, Cory Henson, and Amit Sheth
  • In: Proceedings of the 2009 International Symposium on Collaborative Technologies and Systems (CTS 2009), Baltimore, MD, May 18-22, 2009.
• A Framework for Trust and Distrust Networks
  • K. Thirunarayan, and R. Verma, A Framework for Trust and Distrust Networks, In: Proceedings of 'Web 2.0 Trust Workshop (W2Trust),' June 2008.

Presentations

• Research in Semantic Web and Information Retrieval: Trust, Sensors, and Search: Krishnaprasad Thirunarayan, Research in Semantic Web and Information Retrieval: Trust, Sensors, and Search, Keynote at GMRIT, Andhra Pradesh, India, December 10 - 11, 2009
• Semantic Web techniques empower perception and comprehension in Cyber Situational Awareness: Amit Sheth delivers talk at the ARO Cyber Situational Awareness Workshop, Fairfax, VA, November 14-15, 2007.

Ontologies

• Trust Ontology

Prototypes, Demos and Tools

• Trusted Perception Cycle: demo
• Semantic Sensor Observation Service (MesoWest): demo

Related Material

Computing for Human Experience

• Semantics-Empowered Sensors, Services, and Social Computing on the Ubiquitous Web (Amit Sheth's article, keynote presentation/video)
• Citizen sensing and Social Signals (Amit Sheth's blog, article, keynote presentation)

Contact Information: Pramod Anantharam