Artificial intelligence: a vital tool for cybersecurity

Artificial intelligence: a vital tool for cybersecurity


According to the latest Accenture report, 82 percent of companies increased their cybersecurity budget in 2021. In addition, Hillstone Networks pointed out in a statement, cybersecurity solutions based on Artificial Intelligence ( AI) will become more and more common.

BBVA points out that by identifying patterns, an AI can provide the necessary information to anticipate the attack. Which allows you to make the most suitable decisions in real time. For its part, IBM said AI helps under-resourced security operations analysts stay ahead of threats.

As highlighted in the statement, AI technology has increased in the cybersecurity industry. For example, Principal Component Analysis can automatically identify application programming interface (API) usage quirks and thus uncover vulnerabilities.

Other methods to apply AI are the use of recurrent neural networks. These are used to identify binary program vulnerabilities and graph grouping for bot detection supported by domain generating algorithms (DGA). As well as the multilayer perceptron (MLP) to locate abnormal network traffic, among others.

Through AI, security workflows can be greatly improved. In this way, security teams can focus on more vital issues for the business, which require human intelligence. In that sense, the statement highlighted that more providers will engage in in-depth research of artificial intelligence improvements in cybersecurity.

In addition, the use of deep neural networks will start to increase in order to automatically extract features from the raw host-side and network-side data. This will allow to mitigate the subjection of security experts to extract the characteristics of those data that can be automated.

However, considering that the methodology of black box attacks is still under development, there is no reliable method to judge the performance of AI models. This is why small sample learning is important to the network security industry.

In another sense, threat detection technology based on the graphical neural network (GNN) model is important. As highlighted in the release, GNNs can learn from structured data in graph form. It can also dynamically detect attacks even if they deliberately modify packet volume and arrival times to distract from traditional detection methods.

But, BBVA points out that while it can bring benefits to companies, hackers themselves make use of AI. With which they know the behavior patterns of the victims and even hack passwords of various platforms.