How AI security enhances detection and analytics for today’s sophisticated cyberthreats

With the constant evolution of new technologies in the cybersecurity landscape, malicious actors and cyber bad guys are exploiting new ways to plot shrewder and more successful attacks.

According to a report by IBM, the global average cost of a data breach is $4.35 million, and the United States holds the title for the highest data breach cost at $9.44 million, more than double the global average.

In the same study, IBM found that organizations using artificial intelligence (AI) and automation had a 74-day shorter breach life cycle and saved an average of $3 million more than those without. As the global market for AI cybersecurity technologies is predicted to grow at a compound growth rate of 23.6% through 2027, AI in cybersecurity can be considered a welcome ally, aiding data-driven organizations in deciphering the incessant torrent of incoming threats.

AI technologies like machine learning (ML) and natural language processing provide rapid real-time insights for analyzing potential cyberthreats. Furthermore, using algorithms to create behavioral models can aid in predicting cyber assaults as newer data is collected. Together, these technologies are assisting businesses in improving their security defenses by enhancing the speed and accuracy of their cybersecurity response, allowing them to comply with security best practices.

Can AI and cybersecurity go hand-in-hand?

As more businesses are embracing digital transformation, cyberattacks have been equally proliferating. Since hackers conduct increasingly complex attacks on business networks, AI and ML can protect against these sophisticated attacks. Indeed, these technologies are increasingly becoming commonplace tools for cybersecurity professionals in their continuous war against malicious actors.

AI algorithms can also automate many tedious and time-consuming tasks in cybersecurity, freeing up human analysts to focus on more complex and vital tasks. This can improve the overall efficiency and effectiveness of security operations. In addition, ML algorithms can automatically detect and evaluate security issues. Some can even respond to threats automatically. Many modern security tools, like threat intelligence, anomaly detection and fraud detection, already utilize ML.[…]