  Terrorist attacks carried out by individuals or single cells have
significantly accelerated over the last 20 years. This type of terrorism,
defined as lone-actor (LA) terrorism, stands as one of the greatest security
threats of our time. Research on LA behavior and characteristics has emerged
and accelerated over the last decade. While these studies have produced
valuable information on demographics, behavior, classifications, and warning
signs, the relationship among these characters are yet to be addressed.
Moreover, the means of radicalization and attacking have changed over decades.
This study first identifies 25 binary behavioral characteristics of LAs and
analyzes 192 LAs recorded on three different databases. Next, the
classification is carried out according to first ideology, then to incident
scene behavior via a virtual attacker-defender game, and, finally, according to
the clusters obtained from the data. In addition, within each class,
statistically significant associations and temporal relations are extracted
using the A-priori algorithm. These associations would be instrumental in
identifying the attacker type and intervene at the right time. The results
indicate that while pre-9/11 LAs were mostly radicalized by the people in their
environment, post-9/11 LAs are more diverse. Furthermore, the association
chains for different LA types present unique characteristic pathways to
violence and after-attack behavior.
