Modern cybercrime poses an unparalleled threat to the entire planet. As more of our personal and commercial lives move online, sophisticated, internationally dispersed individuals who are getting harder to track find themselves in a gold mine.
Cybercriminals took advantage of the panic, uncertainty, and sharp rises in internet traffic during the epidemic to hack and steal anywhere they could.
The analysis of data access, transfer, and traffic as well as the identification of outliers or abnormalities in data patterns are all excellent tasks for more recent AI algorithms. If something odd is found, the AI algorithms may examine the data more closely to determine whether the system has any security holes. AI developers are also better equipped to employ AI model management to keep up with changing threats and provide more relevant answers.
In addition to being used to stop cybercrime, AI is being employed all over the world to expedite operations and take strain off corporate cybersecurity teams. IT security professionals are worn out by the complexity and volume of cyberattacks that are on the rise. As a highly scalable technology, machine learning is frequently used to support IT security personnel’s efforts to monitor, detect, and eliminate risks.
AI is also being used to simulate network assaults so that cybersecurity teams may better understand their key weaknesses and how to react to them when they occur. AI is becoming better at illustrating how threat actors could move laterally through a network looking for vulnerabilities.
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