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  • Foluwa T. Rewane

The Impact of Artificial Intelligence on Cybersecurity.




The world has gone digital and it continues to do so at an exceedingly fast pace. All that digitization means everything is transforming at a high speed. A key result of this rapid digitization is artificial intelligence (AI). This technology is impacting every field, and cybersecurity is no exception to the rule. In this article, you will learn about the potential of artificial intelligence in cybersecurity solutions.



Artificial Intelligence and Cybersecurity


With cyber-attacks growing both in complexity and volume, conventional methods to identify threats and malware are failing. Cybercriminals are constantly coming up with new and smarter ways to bypass access controls and firewalls and compromise highly-secure networks. The only way to prevent these attacks is to be more prepared than the hackers.

Artificial intelligence can help under-resourced security systems to stay ahead of the threats. The use of artificial intelligence can help widen the scope of current cybersecurity solutions and also pave the way to develop new, stronger ones.


Simply put, the ever-increasing complexities of network and security threats are beyond what human beings are capable of handlings on their own. That’s why they need modern, AI-powered solutions to tackle present-day and future security risks.

By curating criminal intelligence from using millions of resources, AI can significantly improve your defence mechanisms and reduce response times in case an attack or malicious activity is detected.



Improved Security with Artificial Intelligence


Complicated hacking technologies such as polymorphism, obfuscation, etc. have made it increasingly difficult to detect malicious programs. Moreover, the lack of a domain-specific security workforce is another issue.


With artificial intelligence entering the world of cybersecurity, security analysts and experts are trying to make the best use of its potential in identifying and counteracting sophisticated criminal activity without the need for extensive human intervention. Artificial intelligence and machine learning (a sub-category of AI) have enabled security professionals to learn about advanced cyber-attack vectors.


Machine learning, in particular, can be used to analyze cyber threats better and initiate improved responses to security-related incidents.


Machine learning helps computers update algorithms based on the data they receive, while also learning from it. During the process, these computers understand the consequent improvements required.


From a cybersecurity point of view, this means that machine learning is enabling the systems to predict threats and observe any discrepancies or anomalies with an accuracy that’s beyond human capacity. 


The use of machine learning in cybersecurity is much more than just the application of algorithms.


Some of its benefits include:

⦁ Analyzing mobile endpoints for cyber threats (just like Google uses it)

⦁ Detecting malicious activity right from the start and preventing a full-fledged attack

⦁ Enabling automation of routine security tasks

⦁ Improving human analysis, ranging from malicious attack identification to endpoint safety

⦁ Eliminating zero-day vulnerabilities.



Applications of Artificial Intelligence in Cybersecurity


Here are some of the most important applications of AI in cybersecurity.

⦁ Password Security and User Authentication

Let’s face it, employees and other users are quite lazy when it comes to creating passwords and they often use the same password for multiple accounts. A wide majority of them also save the passwords as drafts in their devices. This is a considerable security risk as these passwords are often the only barrier between criminals and business accounts.


While biometric verification has been developed as a more secure alternative to passwords, it’s often not convenient and the hackers are learning to overcome it too. Developers are now incorporating AI technology to boost biometric authentication making it much more convenient and foolproof. An example is Apple’s face recognition technology which claims that there is only a one in a million chance that the device can be opened with another face.


⦁ Artificial Intelligence – Machine Learning in Vulnerability Management


Systems that are powered with AI-ML do not have to wait for vulnerability in your IT infrastructure to be exploited by cybercriminals. Instead, these AI-based systems adopt a proactive approach to look for potential vulnerabilities in your organization’s IT systems.


Furthermore, they do it by aggregating multiple factors such reputation of the hackers, discussions on the hackers’ dark web, patterns used, and so on. These systems can analyze all and more of these factors and then use the information to determine how and when a threat might make its way into your network’s high-risk areas.


⦁ Phishing Control


One of the most frequently used attacks, where hackers attempt to deliver their malicious payload, is phishing. Phishing emails are very common and account for nearly 70% of cyber-attacks. Fortunately, AI-ML comes to your rescue here as well. It can play a significant role in deterring and preventing phishing attacks.


This technology can detect and track more than 10,000 active phishing sources so that your system can react and defend itself with a much higher speed than ever before. AI-ML scans phishing threats from all around the world so there are no limits when it comes to its understanding of phishing campaigns originating from any specific geographical location. This has made it possible to distinguish between a fake website and a legitimate one in no time.


⦁ Behavioral Analytics


Another promising application of artificial intelligence in cybersecurity stems from its behavioral analytics ability. It can learn and create a pattern of the user’s behavior by assessing how they use devices or network platforms.


If at any time, the AI algorithms observe unusual activities or any anomalous behavior that falls outside of certain standard patterns, it can mark it as suspicious or even block the user. This includes activities like a sudden increase in document downloading, a drastic change in your typing speed, large online purchases, etc.


In Conclusion

With the potential of AI being increasingly explored to enhance the cybersecurity systems of a business it is important that organizations to do as much as they can with a mix of existing techniques and methods as well as AI to stay on top of their cybersecurity strategy.





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