AI and Machine Learning Become Essential Weapons Against Rising Cyberattacks
As cyberattacks grow faster and more complex, organizations increasingly rely on artificial intelligence and machine learning to detect threats and lure hackers into simulated environments.
Cyberattacks are occurring at a rapid pace as threat actors use social engineering, phishing, and ransomware to steal privileged access credentials and bypass security systems. Once attackers infiltrate a corporate network, they move laterally to find and exfiltrate valuable data, with IBM reporting that it takes an average of 287 days to identify and contain a breach at a cost of $3.61 million in hybrid cloud environments.
Artificial intelligence and machine learning serve as perfect tools for analyzing millions of concurrent data connections to identify potential anomalies before they fully manifest. Security teams are increasingly using these advanced technologies to lure attackers into simulated honeypot environments, where they can study attack strategies, reverse engineer malicious payloads, and analyze executable files down to the smallest component.
Machine-speed transaction attacks present a significant challenge for security teams because they are incredibly quick and difficult to predict or stop. With 43 percent of executives reporting an increase in these fast-paced attacks and 70 percent stating they cannot thwart advanced cyber threats without AI, the demand for machine learning-based cybersecurity systems continues to surge across the industry.