  Multi-access Edge Computing (MEC) is a 5G-enabling solution that aims to
bring cloud-computing capabilities closer to the end-users. This paper focuses
on mitigation techniques against Distributed Denial-of-Service (DDoS) attacks
in the context of 5G MEC, providing solutions that involve the virtualized
environment and the management entities from the MEC architecture. The proposed
solutions aim to reduce the risk of affecting legitimate traffic in the context
of DDoS attacks. Our work supports the idea of using a network flow collector
that sends the data to an anomaly detection system based on artificial
intelligence techniques and, as an improvement over the previous work, it
contributes to redirecting detected anomalies for isolation to a separate
virtual machine. This virtual machine uses deep packet inspection tools to
analyze the traffic and provides services until the final verdict. We decrease
the risk of compromising the virtual machine that provides services to
legitimate users by isolating the suspicious traffic. The management entities
of the MEC architecture allow to re-instantiate or reconfigure the virtual
machines. Hence, if the machine inspecting the isolated traffic crashes because
of an attack, the damaged machine can be restored while the services provided
to legitimate users are not affected.
