Advantages Of Ai And Ml For Cloud Security

By Author: James
Total Articles: 13
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As per a 2018 study by the Ponemon Institute, it takes one year and nearly USD3.94 million to control the average data breach. In spite of an increasing number of cloud adoption, a huge number of IT professionals still highlight the cloud as the main area of weakness within their business.

To fight this and lessen the chances of experiencing a breach, some firms are resorting to artificial intelligence and machine learning to strengthen their cloud security. Software with artificial intelligence integration has problem solving abilities and can think like humans. Machine learning, on the other hand, is a subset of artificial intelligence that utilizes algorithms to learn from data. The more data patterns it analyses, the more it processes and adjust by itself based on those patterns, and the more valued its insights become.

Even though it is not a solution, the approach shifts practices from prevention to realtime threat detection, enabling companies and cloud service providers to remain ahead of the curve vis-à-vis cyber attackers.

Some of the advantages of AI and ML for cloud security are:

Big ...
... data processing

Cybersecurity systems generates huge amount of data – numerous times more than any human team could ever examine and analyse the raw data. Machine learning technologies utilize all of this data to identify threat events. The more data is processed, the more patterns it identifies and learns after which it then utilizes to detect changes in the normal pattern flow. These changes could be cyber threats.

For instance, machine learning takes note of what’s regarded as the norm, such as the time and location from which employees log into their systems, the sites they access normally, and other user activities and traffic patterns. Anomalies from the norms, such as logging in different time and locations get flagged. This in turn means that probable threats can be alarmed and taken care of in a faster manner.

Event Detection and Blocking

As soon as artificial intelligence and machine learning technologies process the data created by the systems and detect abnormalities, they can either alert a human or respond by shutting a specific user out, among other options. By taking these steps, events are often identified and blocked within hours.

Delegation to the automation

When artificial intelligence and machine learning technologies manage routine tasks and initial level of security analysis, security teams are free to concentrate on more complex or critical threats.