| Abstract: | The various technologies presented herein relate to determining a network
attack is taking place, and further to adjust one or more network
parameters such that the network becomes dynamically configured. A
plurality of machine learning algorithms are configured to recognize an
active attack pattern. Notification of the attack can be generated, and
knowledge gained from the detected attack pattern can be utilized to
improve the knowledge of the algorithms to detect a subsequent attack
vector(s). Further, network settings and application communications can
be dynamically randomized, wherein artificial diversity converts control
systems into moving targets that help mitigate the early reconnaissance
stages of an attack. An attack(s) based upon a known static address(es)
of a critical infrastructure network device(s) can be mitigated by the
dynamic randomization. Network parameters that can be randomized include
IP addresses, application port numbers, paths data packets navigate
through the network, application randomization, etc. |