Constructing Inference-Proof Belief Mediators
An information owner might interact with cooperation partners regarding its belief, which is derived from a collection of heterogeneous data sources and can be changed according to perceptions of the partners’ actions. While interacting, the information owner willingly shares some information with a...
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          | Published in | Data and Applications Security and Privacy XXIX Vol. 9149; pp. 188 - 203 | 
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| Main Authors | , | 
| Format | Book Chapter | 
| Language | English | 
| Published | 
        Switzerland
          Springer International Publishing AG
    
        2015
     Springer International Publishing  | 
| Series | Lecture Notes in Computer Science | 
| Subjects | |
| Online Access | Get full text | 
| ISBN | 3319208098 9783319208091  | 
| ISSN | 0302-9743 1611-3349 1611-3349  | 
| DOI | 10.1007/978-3-319-20810-7_12 | 
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| Summary: | An information owner might interact with cooperation partners regarding its belief, which is derived from a collection of heterogeneous data sources and can be changed according to perceptions of the partners’ actions. While interacting, the information owner willingly shares some information with a cooperation partner but also might want to keep selected pieces of information confidential. This requirement should even be satisfied if the partner as an intelligent and only semi-honest attacker attempts to infer hidden information from accessible data, also employing background knowledge. For this problem of inference control, we outline and discuss a solution by means of a sophisticated mediator agent. Based on forming an integrated belief from the underlying data sources, the design adapts and combines known approaches to language-based information flow control and controlled interaction execution for logic-based information systems. | 
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| Bibliography: | This work has been supported by the Deutsche Forschungsgemeinschaft (German Research Council) under grant SFB 876/A5 within the framework of the Collaborative Research Center “Providing Information by Resource-Constrained Data Analysis”. | 
| ISBN: | 3319208098 9783319208091  | 
| ISSN: | 0302-9743 1611-3349 1611-3349  | 
| DOI: | 10.1007/978-3-319-20810-7_12 |