Artificial intelligence (AI), without a doubt, has already revolutionized the way people work, live, and think in many different fields. This isn’t a surprise anymore, especially since last year’s ChatGPT launch, which caused some massive talks on the internet about its benefits as well as security concerns. 

One thing’s clear, though: the rise in the use of AI is creating more opportunities for cybercriminals to fuel their cyberattacks.

So in this article, we’ll explore the benefits and disadvantages of AI in cybersecurity, and dive into the ultimate question of whether it’ll take over the important computer field in the future.

Artificial Intelligence and Cybersecurity

With cyberattacks getting more advanced, businesses are turning to AI and its automated solutions to minimize the increasing risks of data breaches, identity theft, and other devious crimes. 

And with good reason. AI has become a mainstream trend, accessible to millions of people. What’s dangerous about the technology today is that even less skilled individuals can leverage AI-models to generate code, complete exams, or even expedite malicious acts. Hackers, for example, are using AI to generate text messages and legit-looking phishing emails, which have higher open rates than traditionally crafted phishing emails. This is especially true for those who aren’t native English speakers. Specialists argue that the only way to fight cybercriminals who are benefiting from AI is to use the same weapon, which is artificial intelligence.

But despite this “double agent” role in cybersecurity, AI has major potential to strengthen cybersecurity by automating threat detection, analyzing vast amounts of data, and even predicting future cyberattacks. Currently, it is being widely used for:

  • antivirus/antimalware solutions
  • data loss prevention services
  • fraud prevention tools
  • intrusion detection systems
  • ID verification and compliance management tools

Benefits of AI in Cybersecurity

While AI can’t work completely on its own, it’s the type of invention that is designed to do things right. It does so by focusing on finding the solution to the issue rather than just following sets of rules or instructions. It imitates how people solve problems. 

These examples show how AI can be helpful in cybersecurity:

  •       Threat detection: AI-powered tools can be used to automatically identify and respond to cybersecurity risks in real time. These solutions use machine learning algorithms to detect patterns and anomalies in network traffic. This in turn can lead to quick responses to threats by blocking access to criminals.
  •       Data handling: With the increasing volume of data, AI can help in gathering, analyzing, and interpreting data quickly. Naturally, that’s why AI tools can reduce human error and enhance the accuracy of data analysis. This can help organizations identify emerging threats and vulnerabilities who then can take proactive measures to prevent cyberattacks.
  •       Predictive analytics: AI can analyze huge volumes of data and predict future cyber threats, and then prevent these attacks. For instance, AI can be used to analyze social media data and predict which vulnerabilities will likely be targeted in the future. This is similar to how it’s used in predicting problems in manufacturing so they can be dealt with before becoming a major issue. 
  •       Improved authentication: AI can enhance authentication methods by analyzing user behavior and identifying suspicious patterns that tell about unauthorized access. For example, AI can detect if a person is attempting to use a stolen password or if their behavior is abnormal.
  •       Greater scalability: AI automates repetitive and time-consuming tasks. This reduces response times to security incidents and lowers the expenses of proactive measures that are used to create robust cybersecurity systems. Companies can then allocate their resources to other critical business areas. 

Overall, these benefits show that AI is able to significantly enhance the efficiency and effectiveness of various cybersecurity processes, helping organizations stay ahead of evolving threats, and better protect their valuable assets.

Disadvantages of AI in Cybersecurity

When businesses think about incorporating AI tools into their operations, they should bear in mind several limitations. Although AI has primarily transformed the cybersecurity landscape positively, trusting this technology can be costly, making it potentially impractical for small businesses. Additionally, AI demands specific integration use cases that businesses must embrace to ensure it’s properly functioning.

Here are a few examples of the drawbacks of AI in cybersecurity:

  •       Various vulnerabilities: AI can be vulnerable to adversarial attacks, which means that malicious actors can intentionally manipulate AI algorithms to avoid detection. This threat can compromise the precision and effectiveness of any AI-powered cybersecurity solutions.
  •       Outdated information: AI-powered services sometimes rely on historical data to recognize patterns and detect potential threats, which leads to a high rate of false positives. Moreover, since AI systems require vast amounts of data to train and operate effectively, organizations can face challenges in collecting and managing such data.
  •       Lack of expertise: AI still remains a complex solution when it comes to cybersecurity. This makes it a hassle for non-experts to use it effectively and avoid improper configuration. Such issues could potentially result in security gaps and vulnerabilities for organizations.
  •       Potential risks of misuse: While AI is a huge help for ethical reasons, bad actors can also use this technology to carry out cyberattacks. These bad actors may employ AI to infiltrate sensitive information or attack infrastructure, increasing the potential risks for businesses that lack robust security measures.
  •       Bias decision-making: AI systems can lack objectivity when operating with biased data sets. That’s how a faulty decision based on biased inputs can potentially result in false positives, blocking legitimate users from accessing company systems and even causing the loss of customers.

However, businesses can avoid bumping into these challenges by implementing proper practices for using AI technology for cybersecurity. Establishing clear goals, using accurate data to train AI systems, and utilizing multiple AI algorithms are just some of the ways AI will help cybersecurity respond to threats successfully.

Will AI Take Over Cybersecurity?

While AI has shown impressive results and major potential in detecting and preventing cyberattacks, it’s unlikely that this technology will take over cybersecurity completely. Compared to people, AI lacks intuition, empathy, and creativity. Currently, AI systems are limited in programming, so they can’t improvise as humans can. AI functions based on the data it’s trained on. If the data is incomplete, the AI model may not be effective. 

Moreover, AI systems require screening and ongoing monitoring to remain effective. Bad actors always develop new tactics, which is one reason why AI systems need to be updated to be able to identify risks effectively. Obviously, that requires humans to monitor and update the AI model’s performance. Otherwise, hackers can exploit AI’s vulnerabilities.

Bottom line

There aren’t many arguments left on whether AI isn’t useful. It’s clear that AI can enhance cybersecurity by detecting threats or handling data. Despite its booming success over the past few years, AI also has drawbacks, especially when it comes to its potential misuse. While AI can prevent cyberattacks, it cannot replace humans, at least not yet.

Contact an expert at Cybernet if you’re interested in learning more about AI and cybersecurity.

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