Big Data Analytics: How Computer Algorithms Can Help Fight Terrorism

Aug 27, 2017

How can big data analytics help fight terrorism? Let’s build a little prelude first. The act of terrorism has recently taken many forms including mass shootings, vehicle ramming attacks, and bioterrorism. Such coordinated attacks require an intricate level of planning along with the effective communication of such plans across all hierarchical levels and networks. However, they cannot use a public platform to communicate and leave a digital footprint as government and intelligence agencies constantly monitor such platforms.

How Terrorists Communicate?

In order to communicate, terrorists resort to using codes, disposable sim cards, dead drops, steganography, satellite phones, and the dark web. For instance, a group of terrorists can join a chat room inside a game to exchange messages. It may seem like an impossible task to go through all data and identify terrorist activities in such a vast digital world. However, big data analytics can help filter through all the data to not only identify terrorist threats but also to accurately predict future terrorist activities.

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Predictive Analytics to Identify Risks

A controversial debate that has picked up traction in recent times is that of aggressive government surveillance. It is widely believed that government agencies operating across the globe are constantly monitoring the digital activities of every individual. This may lead to the accumulation of a large amount of data, which is difficult of analyze due to its sheer volume. However, with the advent of big data analytics and predictive analytics, security agencies can analyze such data and identify patterns to predict terrorist activities.

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Large Scale Big Data Analytics

With recent advancements in big data analytics, it has become possible to stop a terrorist act during its inception. The analytical tools used today can analyze banking information, travel records, analysis of social media, and other classified materials sophisticated algorithms to identify patterns in a person’s behavior and predict future threats. For instance, in a recent study, it was found that around 19 of the terrorists involved in the September 11 attacks had some common behavior:

  • They all opened accounts at well-known US banks
  • Received frequent wire transfers from other countries with transactions below the banking limit to prevent triggering the bank’s reporting system
  • Made one large deposit and frequent small withdrawals
  • Banking didn’t include normal living expenses like utility payment, rent, and insurance
  • Unusually high cash withdrawals to checks issued ratio

With the help of big data analytics, security agencies will be able to identify terrorist threats and act swiftly to make the world a lot safer.

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