AI and predictive analytics certainly make it harder for attackers to penetrate networks, Martini said, but time has taught us that hackers are constantly learning new techniques, are resourceful, sophisticated, and selective in their targets, and will continue to find ways to breach systems. While AI and predictive analytics will be a good tool for preventing the most common types of attacks, highly targeted attacks using unconventional or tailored methods will continue to pose challenges for enterprise IT security teams.
are not intended to replace cybersecurity personnel or human actions. Their main purpose is to complement the efforts of specialists, freeing them from manual operations so that they can focus on more complex issues, patching processes, and critical security issues.
Solving this problem also requires data. AI, ML, and italy mobile database analytics are only as effective as the information they operate on, and unless companies collect high-quality information about services, users, network traffic, and other aspects, they will inevitably encounter false alarms and incorrect conclusions that will degrade the quality of their security systems.
“AI and predictive analytics will be most effective in cloud cybersecurity because they deal with larger data sets,” Martini said. “The more historical and current data that feeds AI programs, the better they will perform. While AI and predictive analytics will be valuable for traditional security solutions, their highest level of effectiveness will always be achieved in the cloud.”
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