The Recent Past: Pandemic and AI

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Late 2010s: Businesses Fight Back
Things started to change for the better in the late 2010s. By then, typical organizations realized that basic, reactive cybersecurity defenses weren’t enough. Companies realized they also needed to invest in preventative measures.

The widespread adoption of multi-factor authentication (MFA) solutions has made it much more difficult for attackers to impersonate other users using stolen credentials. Companies have also invested in more advanced cybersecurity solutions and techniques, such as threat intelligence and hunting.

Of course, these solutions did not eliminate cybercrime. But they were effective in reducing the overall level of risk.

Over the past few years, we have faced two new serious challenges that have made cybersecurity even more difficult.

One of them was the Covid pandemic. As many benin mobile database workers began working from home, corporate networks expanded to include home networks. Businesses had to implement more sophisticated cybersecurity measures, such as zero-trust network security policies.

Meanwhile, the AI ​​boom of the last few years has given attackers new tools. They can now use AI to solve problems such as target selection and malware creation, increasing the efficiency and scale of hacking operations.

In this regard, we are currently witnessing another inflection point in cybersecurity strategies. Enterprises have realized that in order to keep up with attackers, they need to improve their efficiency and skills. To do this, they are investing in AI-enabled cybersecurity tools that provide advanced behavioral analysis, automated response, and other capabilities.

Lessons from the History of Cybersecurity, or Why We Need to Go Back to Basics
There are many useful lessons to be learned from the history of cybersecurity that I have just outlined. However, I will focus on the one that I believe is most important for developing modern cybersecurity strategies.