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With the recent trend of "network softwarisation", enabled by emergingtechnologies such as Software-Defined Networking (SDN) and Network FunctionVirtualisation (NFV), system administrators of data centres and enterprisenetworks have started replacing dedicated hardware-based middleboxes withvirtualised network functions running on servers and end hosts. This radicalchange has facilitated the provisioning of advanced and flexible networkservices, ultimately helping system administrators and network operators tocope with the rapid changes in service requirements and networking workloads.This thesis investigates the challenges of provisioning network securityservices in "softwarised" networks, where the security of residential andbusiness users can be provided by means of sets of software-based networkfunctions running on high performance servers or on commodity compute devices.The study is approached from the perspective of the telecom operator, whosegoal is to protect the customers from network threats and, at the same time,maximize the number of provisioned services, and thereby revenue. Specifically,the overall aim of the research presented in this thesis is proposing noveltechniques for optimising the resource usage of software-based securityservices, hence for increasing the chances for the operator to accommodate moreservice requests while respecting the desired level of network security of itscustomers. In this direction, the contributions of this thesis are thefollowing: (i) a solution for the dynamic provisioning of security servicesthat minimises the utilisation of computing and network resources, and (ii)novel methods based on Deep Learning and Linux kernel technologies for reducingthe CPU usage of software-based security network functions, with specific focuson the defence against Distributed Denial of Service (DDoS) attacks.

Methods and Techniques for Dynamic Deployability of Software-Defined Security Services