Privacy-Preserving Reasoning on the Semantic Web (Poster)
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Incomplet e 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 Highligh ts: • 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 U ser H idden know ledge (K h ) V isible know ledge (K v ) Safe? 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: a b c d e a b c d e “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.
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Transcript of Privacy-Preserving Reasoning on the Semantic Web (Poster)
Incomplete knowledge
Center for Computational Intelligence, Learning, and DiscoveryArtificial Intelligence Research LaboratoryDepartment 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 WebJie Bao, Giora Slutzki, and Vasant Honavar
3- Concrete Strategies2 – 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
User
Hidden knowledge (Kh)
Visible knowledge (Kv)
Safe?
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:
a
b
c
d
e
a
b
c
d
e
“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., Kv about the signature of Kh.)
Kh
Kv Critical visible knowledge Kvc
C ⊑ D
C ⊑ R.D
G ⊑ H
Reasoning Strategy & Safety Scope : ensure that Kv-Kvc+QY is local w.r.t. Sig(Kvc)
(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.
