ITChronicles reports that a new cyberattack occurs every 40 seconds. This means that hackers are almost certain to target your company. It’s not only this that hackers can be very successful in hacking your organization. Even the best cybersecurity teams will have trouble keeping track of every security threat discovered by their system. It’s often not discovered until much later when a company is hacked. IBM estimates that hacking can take an average of 287 business days to be detected.
These statistics may seem alarming, but artificial intelligence (AI) could be a solution to cyberattacks. This post will discuss five ways AI is bringing about a new era of cybersecurity. Let’s begin with the most obvious use of AI: its ability to learn.
How AI Learns
One of the greatest strengths of AI is its ability use previous information to make judgment calls. This ability is very useful when analysing security threats presented by cybersecurity platforms. A platform can often present false positives in addition to all the legitimate security threats. It’s like trying find a needle within a haystack.
False positives are cases in which the cybersecurity platform thinks an anomaly is a threat. A cybersecurity expert must examine the anomaly to determine whether it is a false positive. This can be time-consuming, but it is worth it if you find out that it wasn’t a false positive in the first instance.
AI can, however, analyze large amounts of threat detections. It can detect patterns and determine false positives. Once it has a good understanding of what makes a threat false positive, it can filter them out and only present true threats. Hackers, just like everyone else, follow trends. AI can detect similar attacks by detecting them.
This will save you hundreds of hours and increase your security. AI is more than network analysis. Let’s look at how cybersecurity can be used to authenticate users.
How AI is used in Biometrics
Biometrics are something that everyone who has used a smartphone knows. Biometrics allows users to be authorized by analysing their immutable characteristics and/or physical makeup. Examples include facial, voice and fingerprint recognition, as well as ocular recognition. The smartphone uses biometrics, such as fingerprints and faces, to identify the user. The computer learns your appearance by scanning and analysing your fingerprint or face. It can also determine who you are even if your face changes with age.
Biometrics are used for more than access authentication. It is being used in new and exciting ways by the financial industry to prevent fraud. A criminal may call a bank to pretend to be someone they are calling. They can scan the voice to verify that it is authentic using AI and biometrics. Because vocal patterns are just as unique as fingerprints, they can be used to verify that an individual is who they claim to be.
Prediction of Security System Risk
We have already discussed AI’s role in biometric validation and threat detection. Security system assessment is another critical role that AI plays. Imagine that you are the AWS security expert responsible for managing a cloud environment. This will mean that you will be responsible for the EC2 instances, Virtual Private Clouds (VPC), the Elastic Load Balancingrs, as well as everything else.
It is enough to say that the configuration required to connect everything to the cloud is overwhelming. Developers often overlook critical security components. All of this being said, a security expert cannot examine each configuration individually.
Amazon Inspector can be used instead to search AWS resources and identify risks. Amazon Inspector is a service that uses AI to mitigate threats. Azure and Google Cloud