Artificial Intelligence in Cybersecurity

Experts believe that Artificial Intelligence (AI) and Machine Learning (ML) have both negative and positive effects on cybersecurity. AI algorithms use training data to learn how to respond to different situations. They learn by copying and adding additional information as they go along.

Attacks are becoming more and more dangerous despite the advancements in cybersecurity. The main challenges of cybersecurity include: Geographically-distant IT systems — geographical distance makes manual tracking of incidents more difficult. Cybersecurity experts need to overcome differences in infrastructure to successfully monitor incidents across regions. Manual threat hunting — can be expensive and time-consuming, resulting in more unnoticed attacks. Reactive nature of cybersecurity — companies can resolve problems only after they have already happened. Predicting threats before they occur is a great challenge for security experts.

Cybersecurity is one of the multiple uses of artificial intelligence. A report by Norton showed that the global cost of typical data breach recovery is $3.86 million. The report also indicates that companies need 196 days on average to recover from any data breach. For this reason, organizations should invest more in AI to avoid waste of time and financial losses.

References: 1: Artificial Intelligence in Cybersecurity | IEEE CS — IEEE Computer Society 2: The Impact of AI on Cybersecurity | IEEE Computer Society 3: Artificial Intelligence: The Future Of Cybersecurity? — Forbes