This is a summary of an article written for Security Week by Fortinet’s CMO and Executive Vice President of Products, John Maddison. The entire article can be accessed here.
In the cybersecurity space, there has always been an unfair advantage for cybercriminals. Adversaries only need to find one vulnerability to wreak havoc on an entire system. All it takes is a single misconfigured device, or outdated operating system. Security teams, however, must work to anticipate hundreds of types of attacks, and then block them on all devices throughout the network.
That partly explains why spending on cybersecurity continues to grow and could reach $133.8 billion by the year 2022, according to IDC. Even so, cybercrime is still costing enterprises around twice that of their total security spend.
As the stakes get higher as businesses connect more devices and applications to the internet, leaders need to rethink how they approach cybersecurity. As IT teams revise their strategies, there are three strategies they should keep in mind:
While automation speeds up response times and machine learning can identify indications of a possible threat, artificial intelligence (AI) can make human-like decisions in a split second and even anticipate future cyber events. However, using AI to protect your system means taking a giant technological leap forward. To determine if a vendor actually has the infrastructure necessary to develop an AI solution, IT leaders need to talk to vendors about their AI development strategies.
Capitalizing on new directions in cybersecurity, many vendors now claim AI-based security products. The reality is, however, that many solutions advertised as AI are merely sophisticated scripts combined with a decision tree. Developing true AI is challenging, which is why enterprises need to be skeptical when they’re talking to vendors.
An AI system needs to be fed enormous amounts of data to be effective. And in order to train an AI, there must also be an artificial neural network (ANN) present, and a deep learning model that will accelerate data analysis. Only then can the AI make use of data to learn, adapt, and evolve.
Here’s a quick checklist of what to look for:
It can take years of cycling through these steps before an AI program is ready for the field. Keep in mind that meanwhile, cybercriminals are devising new ways to breach enterprise systems. That means there’s a constant supply of new cybercrime data that will need to be continually incorporated into training. AI training models will need to be continually adjusted to new threats, along with new strategies to designed to combat those threats.
Security leaders are right to be skeptical when they talk to vendors of AI-enabled security services. The learning curve for AI might be steep, but the advantages of a good AI-based security system are well worth the effort.
This is a summary of an article written for Security Week by Fortinet’s Chief Marketing Officer and Executive Vice President of Products, John Maddison. The entire article can be accessed here.
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