Every day organisations face risks to their security and business continuity. These may include industrial espionage, cyber attacks, protests, union strikes, terrorism, epidemic, natural disasters and the list is endless. Keeping track on all the events potentially hampering business operations and the security of employees and assets is not an easy task, and it all starts with collecting the right information via “threat intelligence”.

Threat intelligence is the process of collecting and elaborating information on existing or emerging risks or hazard to people, assets or operations, with the purpose of informing decision makers and, whenever possible, preventing or mitigating operational or strategic threats if and when they occur.

Since most of the information is collected via openly available media and social media (so called Open Source Intelligence or OSINT), practitioners and threat intelligence solution providers have been looking at Artificial Intelligence (AI) to find more relevant information faster.

In this regard, Machine Learning and Natural Language Processing are being used to automatise all those repetitive tasks that are extremely time-consuming for a human analyst (e.g. searching for relevant information, classifying them by location, topic or severity, etc.). Therefore, AI not only frees time that can be dedicated to qualitative analyses, but it also offers a much more comprehensive dataset of information that allows for more accurate data-driven intelligence. 

Let’s make some examples.

Following the recent outbreak of the coronavirus in Whuan, China, we have used AI to monitor new recorded cases across the globe and if airports or transport networks were being closed to contain the spreading of the virus. As soon as a relevant information was released on a news website or social media outlet, our AI was able to spot it and geotag it in near realtime. Similarly, during the recent crisis between the United States and Iran, AI helped us to monitor the situation in the region and to send notifications when commercial airlines decided to stop flying to Iran or to avoid the Iranian-Iraqi airspace.

It is quite evident how critical these information are for organisations sending employees for business trips, or for planning their supply chain and procurement. 

Nevertheless, it would be quite misleading thinking that the future of threat intelligence will be made by AI alone, rather by the integration of AI into the human workflow. The reason is twofold. First of all, from a technological perspective AI is not yet mature enough to provide the same quality and accuracy as a human, which in a security environment may lead to a cascade of disasters (think of fake news and false positive). Secondly, and most importantly, even if threat intelligence is fully automated via AI, we will still need humans to interpret and provide context to the collected information, and take decisions on real or perceived threats. 

This is why at Hozint – Horizon Intelligence we have developed AI-based threat intelligence systems that enhance the performance and efficiency of human analysts, instead of replacing them with algorithms.

This article was written by Edoardo Camilli, CEO and Co-Founder at Hozint – Horizon Intelligence. He holds a Master degree in International Relation and Diplomacy from Bologna University (Italy) and a second level MA degree in Intelligence and National Security from the University of Malta. Edoardo is alumnus of the International Leadership Visitor Program (IVLP) and European Young Leader Under 40 (EYL40).

 #TheFutureLivesinBrussels by the MIC Brussels. This is a series of curated articles written by experts and partners of the ICT sector and entrepreneurial community. It’s a way for them to communicate their insights on specific topics and share their ideas for a better future in Brussels. If you want to be part of it, get in touch with us!