Reference number : GC-2017-Q4-01862, amendment number : , agreement type : G, recipient legal name : Wang, Lingyu (Concordia University)|Wang, Lingyu (Université Concordia), recipient country : CA, recipient province : nan, recipient city : Quebec|Québec, recipient postal code : nan, program name english : Collaborative Research and Development Grants - Project, program name french : Subventions de recherche et développement coopérative - projet, program purpose english : The primary objective of the proposed research is to develop a novel and comprehensive solution for automating the security auditing and monitoring of emerging Network Functions Virtualisation (NFV) and Software-Defined Networking (SDN)-based cloud networks. New knowledge and technologies that would be transferred to Canadian industry through this project comprise a series of solutions designed specifically for NFV and SDN-based cloud networks, including a quantitative approach to auditing security properties of such networks, a machine learning-based proactive solution to security monitoring, an active probing-based method for securely verifying security compliance without accessing network traces, and novel techniques for addressing various privacy issues in auditing and monitoring. The key benefits expected to accrue to both the industry and academia include novel research ideas and methodology that could advance the state of the art in cloud security, NFV and SDN security, a research prototype and related demos that would be valuable to security practitioners, including those at our industrial partner (Ericsson Canada), and finally the training of HQP for an emerging industry which increasingly demands highly specialized expertise., program purpose french : The primary objective of the proposed research is to develop a novel and comprehensive solution for automating the security auditing and monitoring of emerging Network Functions Virtualisation (NFV) and Software-Defined Networking (SDN)-based cloud networks. New knowledge and technologies that would be transferred to Canadian industry through this project comprise a series of solutions designed specifically for NFV and SDN-based cloud networks, including a quantitative approach to auditing security properties of such networks, a machine learning-based proactive solution to security monitoring, an active probing-based method for securely verifying security compliance without accessing network traces, and novel techniques for addressing various privacy issues in auditing and monitoring. The key benefits expected to accrue to both the industry and academia include novel research ideas and methodology that could advance the state of the art in cloud security, NFV and SDN security, a research prototype and related demos that would be valuable to security practitioners, including those at our industrial partner (Ericsson Canada), and finally the training of HQP for an emerging industry which increasingly demands highly specialized expertise., agreement title english : Auditing and monitoring the security of NFV and SDN-based cloud environments, agreement title french : Auditing and monitoring the security of NFV and SDN-based cloud environments, agreement number : CRDPJ, agreement value : 313050.0, agreement start date : 2018-02-07, agreement end date : nan, description english : nan, description french : nan, expected results english : nan, expected results french : nan, additional information english : Grant or Award spanning more than one fiscal year (2017-2018 to 2020-2021)., additional information french : Subvention ou bourse octroyée s'appliquant à plus d'un exercice financier (2017-2018 à 2020-2021)., owner organization : nserc-crsng, owner organization title : Natural Sciences and Engineering Research Council of Canada | Conseil de recherches en sciences naturelles et en génie du Canada