The document discusses strategies for privacy-preserving reasoning on the semantic web by hiding private knowledge as if it is incomplete knowledge under the open world assumption. It presents an approach where queries are answered with "unknown" for both incomplete knowledge and hidden knowledge, so the querying agent cannot distinguish between them. The hidden knowledge is protected as if it is incomplete knowledge. It ensures the answers to queries will not provide knowledge beyond the critical visible knowledge.

1. Incomplete knowledge Center for Computational Intelligence, Learning, and Discovery Artificial Intelligence Research Laboratory Department of Computer Science Acknowledgements : This work is supported in part by grants from the National Science Foundation (IIS-0639230). Privacy-Preserving Reasoning on the Semantic Web Jie Bao, Giora Slutzki, and Vasant Honavar 3- Concrete Strategies 2 – General Strategy Highlights : The Problem: can we share knowledge / answer queries about a knowledge base without compromising its privacy The Solution: hiding private knowledge as if it is incomplete knowledge under the open world assumption 1 – Problem Description WEB PRIVACY : Required by Copyright, Commercial Needs, Personal Privacy … Applications: Web Service, Medical System, E- Commerce… Syntactical specification: Policy languages, e.g., KAoS, xACML. REASONING WITH HIDDEN KNOWLEDGE : To verify the correctness and consistency of security policies To avoid overly restrictive protection on data or knowledge To allow flexible safe usage of the same knowledge base to multiple users Locally visible : Has date Query: Has date? Answer : Unknown Query: Has travel? Answer: Unknown Query: Busy (has activity)? Answer : Yes Hidden knowledge STRATEGY : Open World Assumption: knowledge base may be incomplete Answer “Unknown” to both incomplete knowledge and hidden knowledge Querying agent cannot distinguish between them Hidden knowledge is protected as if it is incomplete knowledge EXAMPLE : a calendar ontology FOR HIERARCHIES : FOR DESCRIPTION LOGICS (AND OWL) : Reasoning Strategy : Safety Scope : “ safe” graph “ unsafe” graph Basic idea : Problem reduces to graph reachability analysis Basic idea : Ensure that answers to queries will NOT give knowledge beyond Critical visible knowledge (i.e., K v about the signature of K h .) K h K v Critical visible knowledge K vc C ⊑ D C ⊑  R. D G ⊑ H Reasoning Strategy & Safety Scope : ensure that K v -K vc + Q Y is local w.r.t. Sig( K vc ) (locality defined by [Grau et al., 2007] ) Reference: Bao, J., Slutzki, G., and Honavar, V. (2007). Privacy-Preserving Reasoning on the Semantic Web . In Web Intelligence 2007. a b c d e a b c d e