Artificial Intelligence and the Quest to Prevent Lone Wolf Attacks

December 19, 2021

The Lone Wolf attack in the supermarket in Auckland, New Zealand in September 2021 is a disturbing reminder of how unpredictable violence can be. Lone Wolf terrorist attacks have increased in frequency around the world, largely due to global online radicalization, decentralized terrorist structures, and increased technological access. In our contemporary era, someone can be radicalized through indirect contact with online material without ever communicating directly with a terrorist group. Lone Wolves can gain access to information to help them plan and carry out attacks without crossing most of the standard tripwires that are used to detect a potential attack from a traditional terrorist organization. These Lone Wolf attacks often cause fewer casualties than planned attacks by organizations because the individual attackers usually operate with fewer resources. However, the unpredictability of individual, self-directed attacks bring its own element of terror to the public.

In spite of the elusive nature of Lone Wolf terrorists, there are means and methods to detect and prevent their attacks. Modern technologies like Artificial Intelligence (AI) are offering law enforcement and Intelligence professionals new tools for analyzing data that could lead to the identification, disruption, and arrest of Lone Wolves before they can strike. While many of such Lone Wolf actors may not be directly affiliated with a particular terrorist organization, their personal records, online activities, and preparatory actions can be indicators and warning signals that give investigators and analysts a crucial advantage.

In many cases, a Lone Wolf attacker has a trail of documentation that can provide clues to future activities. This may be a record that reflects tendencies towards violence, possession of terrorist-related materials, mental illness, theft or illegal purchase of weapons, hate speech, or other suspicious data. Depending on the laws of the country and the type of data being analyzed, AI systems can cross-reference various types of data to analyze and categorize potential Lone Wolf actors. This is especially useful when linked with the factors listed below.

Lone Wolf attackers do not operate in a complete vacuum. In fact, they often have regular online communications with radical groups through various online platforms. While many Lone Wolf attackers are independent and unpredictable actors, they often still leave a notable, identifiable digital footprint as they develop into threats. Many Lone Wolf terrorists use online platforms to share ideas, find a supportive audience, express their hatreds, and gain information that is crucial to their causes and missions. This is where AI-based technology can comb through oceans of daily-generated publicly available data that would take teams of experts and experienced analysts, countless hours to process and analyze.

In cases in which a Lone Wolf has escalated activity to the planning stage, online purchases are often made to facilitate the operation: vehicles, travel plans, explosive components, and access to venues or weapons. Tailored algorithms can isolate parameters for online purchases and cross-reference them with other data sets to identify violent actors, before they commit their crimes. Without a doubt, AI applications increase the likelihood of detecting, disrupting, and preventing such Lone Wolf attacks.

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