Using AI to face covert attacks in IoT and softwarized scenarios: challenges and opportunities

Recently, the number of attacks aiming at breaching networked and softwarized environments has been growing exponentially. In particular, information hiding methods and covert attacks have been proven to be able to elude traditional detection systems and exfiltrate sensitive data without producing visible network flows or data exchanges. In this context, Artificial Intelligence techniques can play a key role in detecting these new emerging attacks, owing to their capability of quickly processing huge amounts of data without the necessity of expert intervention. In this work, we discuss the main challenges to face covert attacks in IoT and softwarized environments and we describe some preliminary results obtained by adopting Deep Learning architectures.