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Universal privacy‐preserving platform for SecaaS services
Authors:Tytus Kurek  Marcin Niemiec  Artur Lason  Andrzej R Pach
Affiliation:AGH University of Science and Technology, Department of Telecommunications, Mickiewicza 30, Krakow, Poland
Abstract:With the rapid growth of the Security‐as‐a‐Service market, concerns about privacy in exposing customer security policies to Cloud Service Providers have become critical. To resolve these issues, several solutions have been proposed over the past few years, each for a different kind of security service. However, as the number of security services outsourced into a cloud continues to grow, the need for a unified solution has become significant. This article introduces and presents a universal privacy‐preserving platform for SecaaS services that is based on a hybrid cloud architecture for maintaining the confidentiality of the customer's security policy. It is shown that this platform can be applied to all security services whose security policies can be represented in the form of a decision tree. This includes the vast majority of existing cloud‐based security services. With the small number of computationally‐expensive operations performed in a private cloud, the solution also does not require the implementation of a performant security engine on the customer's premises, allowing full advantage to be taken of private cloud offloading. It is also shown that the platform achieves better performance results than other existing solutions of this type. These findings were confirmed by experimental results.
Keywords:decision tree  privacy  SecaaS
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