Revision as of 14:14, 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

Trust on Semantic Sensor Web

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 work, we briefly review existing work on trust networks, pointing out some of its drawbacks. We then propose a local framework to explore two different kinds of trust among agents called referral trust and functional trust, that are modelled 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.

Perception and Analysis of Sensor Data

Currently, there are many sensors collecting information about our environment, leading to an overwhelming number of observations that must be analyzed and explained in order to achieve situation awareness. As perceptual beings, we are also constantly inundated with sensory data; yet we are able to make sense out of our environment with relative ease. This is due, in part, to the bi-directional information flow between our sensory organs and analytical brain. Drawing inspiration from cognitive models of perception, we can improve machine perception by allowing communication from processes that analyze observations to processes that generate observations. Such a perceptual system provides effective utilization of resources by decreasing the cost and number of observations needed for achieving situation awareness.

People

• Pramod Anantharam
• T.K. Prasad
• Cory Henson
• 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), 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

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