01287nas a2200265   4500000000100000000000100001008004100002260000900043653001800052653002900070653001800099653001100117653001800128653002900146653002100175653002700196100001400223700001800237700001900255700001900274245005000293300001200343490000700355520065900362       2020                            d  c202010aauto-encoding10aclustering with outliers10aCybersecurity10aDBSCAN10adeep learning10aKNIME Analytics Platform10amachine learning10aMITRE ATT@CK framework1 aArvid Kok1 aIvana Mestric1 aGiavid Valiyev1 aMichael Street00aCyber Threat Prediction with Machine Learning  a203-2200 v473 a<p>In this paper we address the approaches, techniques and results of applying machine learning techniques for cyber threat prediction. Timely discovery of advanced persistent threats is of utmost importance for the protection of NATO’s and its allies’ networks. Therefore, NATO and NATO Communication and Information Agency’s Cyber Security service line is constantly looking for improvements. During Coalition Warrior Interoperability Exercise (CWIX) event data was captured on a Red-Blue Team Simulation. The data set was then used to apply a variety of Machine Learning techniques: deep-learning, auto-encoding and clustering with outliers.</p>