Identify Pain Point
It is hard to find attackers moving from a beechhead machine to more interesting machines in a sea of login data
Every Windows machine has tens to hundreds of logins a day normally
Project datasets
Use a subset of windows event login data most likely to contain attacker movement
Constrain Output
LMs will only be of certain login chain shapes
Localized in time
Identify Algorithms
Use modern classifiers on projected log event set to identify logins that are more or less likely to be in a LM
Use motif search algorithms to find patterns of logins that fit the output constraints
Self-learning and feedback