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Knowledge as a service and knowledge breaching

Authors: Shouhuai Xu; Weining Zhang;

Knowledge as a service and knowledge breaching

Abstract

In this paper, we introduce and explore a new computing paradigm we call knowledge as a service, in which a knowledge service provider, via its knowledge server, answers queries presented by some knowledge consumers. The knowledge server's answers are based on knowledge models that may be expensive or impossible to obtain for the knowledge consumers. While this new paradigm of computing is promising, we must establish a solid foundation to ensure its utility. We focus on the security aspect of the paradigm, and particularly on the problem we call knowledge breaching attack, which may allow an adversary to recover the knowledge underlying a knowledge service. Without being able to adequately handling such an attack, the knowledge service providers would never have any economic incentives to develop such a paradigm. Unfortunately, this paper theoretically shows that any interesting knowledge is subject to the knowledge breaching attack, and empirically shows that some knowledge models could be breached after a very small number of queries (e.g., 0.2-]% portion of the domain). Thus we need to investigate technical means that can alleviate such powerful attacks (at least for most practical knowledge models).

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    popularity
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    influence
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Powered by OpenAIRE graph
Found an issue? Give us feedback
selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
12
Average
Top 10%
Average
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