Does Artificial Intelligence Aid Cybersecurity?


Artificial intelligence (AI) still has a long way to go to reach a sci-fi-level of advancement. For businesses in the digital age, however, it’s proving to be highly effective in its current state. Artificial intelligence and machine learning, its subset, have reduced costs, streamlined operations, fueled innovations, fast-tracked growth, and managed risks for many businesses. 

Still, AI isn’t yet capable of making apps operate with unlimited autonomy—apps that can constantly create different algorithms that learn and adjust to evolving IT situations. Alan Turing predicted in 1945 that AI will someday play ‘very good chess.’ A computer program did play chess good enough to beat a reigning world chess champion—Garry Kasparov, in 1997. It took more than 50 years, sure—but the potential for an autonomous AI is undoubtedly there.

At present, AI with machine learning is well-suited for cybersecurity. AI paired with cybersecurity seems like a match made in heaven. But then again, AI paired with almost anything tech-related is a great combination. Viewed this way, AI is to tech what butter is to bread. 

Silent Guardian And Watchful Protector

With artificial intelligence and cybersecurity combined, network security gets around-the-clock protection, 365 days a year. This combination can respond quickly and effectively to any security threats: a highly-efficient cybersecurity specialist always on the look-out for any suspicious behavior.   

Team of Professional IT Developers Have a Meeting, Speaker Talks about New Blockchain Based Software Development Shown on TV. Concept: Deep Learning, Artificial Intelligence, Data Mining, Neural Network

The worldwide cost of data breaches at present is around USD$3.86 million. Numbers like that remind everyone of the importance of sophisticated cybersecurity. That’s why companies that provide this kind of service, like, will always be sought after. 

After all, nobody likes to become a victim of cyberattacks. Not only because data breaches could cost money, but people could also lose trust in your brand, especially if you’re an IT company.   

AI and its subset machine learning (ML) specializes in pattern recognition. Moreover, AI pushes businesses to abide by security best practices, with its ability to detect threats and respond quickly. Both are hallmarks of a cybersecurity’s precision and automation. Indeed, there are a lot of ways that AI can help cybersecurity.

Ability To Handle Huge Amount Of Data

AI security can automate the creation of algorithms in detecting threats, a capability that gives it a tremendous advantage when it comes to processing huge amounts of data. Included in the processed data are various IT network elements like visited sites, emails, and files shared. Likewise, a hacker activities’ patterns, as well as third-party software, don’t go unnoticed from AI’s watchful eye.   

Of course, a manual scan isn’t comparable to an AI security’s in-depth scanning system, especially when it involves a vast amount of data. A person can take months to scan a piece of data, whereas AI isn’t only quick, but also extremely thorough. It can detect anomalies and present solutions within minutes.

Ensuring An Error-Free Cybersecurity

Unlike humans, an AI doesn’t get tired or get distracted, even when doing repetitive tasks, thus ensuring the accuracy of results. Also, compared to a person’s efforts, an AI’s error rates are considerably low. Limiting a network security’s errors is one of artificial intelligence’s major contributions to cybersecurity.

Your security team might get overwhelmed with the sheer amount of data that requires risk assessment. An AI, however, won’t get fazed; it can quickly go through massive amounts of data quickly and accurately. This gives your team more time to focus on other jobs. 

No Threat Too Small To Ignore

Like Stephen Curry, cybercriminals are always putting pressure on your defense, a consistent threat that keeps your defenders on their toes. What’s more, hackers find new ways to infiltrate network security. Their threats can go unnoticed, due to their ability to camouflage themselves. AI, however, can recognize unusual patterns and behavior, enabling your security to detect even a slight deviation from the norm, and flagging them as threats. Your security can identify and stop these threats, preventing them from doing any mischief. 

Challenging Advanced Hacking Techniques

There are cyber criminals that employ advanced and sophisticated techniques to penetrate security and steal your data. These techniques, like polymorphism, obfuscation, and others, are extremely malicious and difficult to identify. These threats can be very alarming, especially when faced with a shortage of cybersecurity experts. 

Hackers can obtain personal information using their knowledge of social engineering. However, artificial intelligence provides a countermeasure to this kind of attack, called the social honeypot. A honeypot is an AI tool created to snare hackers, using decoys set up by security experts. It can then trace the origin, as well as the techniques, used by the cybercriminals.  


Artificial intelligence is a valuable addition to cybersecurity, with its ability to handle massive amounts of data quickly and accurately. Cybercriminals are getting sophisticated with their attacks, that’s why pairing security with artificial intelligence and machine learning could give companies the ability to face challenges to their network security.         

March 31, 2021


Hakin9 TEAM
Hakin9 is a monthly magazine dedicated to hacking and cybersecurity. In every edition, we try to focus on different approaches to show various techniques - defensive and offensive. This knowledge will help you understand how most popular attacks are performed and how to protect your data from them. Our tutorials, case studies and online courses will prepare you for the upcoming, potential threats in the cyber security world. We collaborate with many individuals and universities and public institutions, but also with companies such as Xento Systems, CATO Networks, EY, CIPHER Intelligence LAB, redBorder, TSG, and others.
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