Due to the rapid growth of the technology industry, data exchange is happening on a bigger scale between multiple systems. The latest trend in cybersecurity is to use artificial intelligence and machine learning for better defense.
AI and ML can foretell cyberattacks by analyzing the online traffic pattern. Besides, there are many reasons why engineers rely on machine learning in cybersecurity. In this article, we will focus on the pros and cons of using ML in cybersecurity.
Role of Microsoft
It all started back in 2017 when Microsoft announced that it had acquired Hexadite—a US-Israeli cybersecurity company. Other big organizations realized by then that an efficient algorithm can handle a tremendous amount of data analysis. And machine learning is the way forward.
Hexadite had a cutting-edge technology back then that lured Microsoft. The corporation later used that tech for Windows Defender’s Advanced Threat Protection feature. That’s the inception of using artificial intelligence and machine learning in cybersecurity.
Pros of using AI in cybersecurity
AI can handle an enormous volume of data
AI-based machine learning algorithm can detect threats before it happens—thanks to its ability of handling data on a very big scale. The algorithm just skims through the sea of chaotic data and exposes the malicious data.
Easier identification of unknown threats
Cybercriminals launch hundreds and thousands of malicious software every day. According to G Data Software, around 7.41 million new malware emerged every day in 2017. We can safely predict that it has increased over time. Even for a very skillful engineer, it is very tough to deal with this large volume of malicious software. The AI-based algorithm just focuses on changes in the network and identifies new malicious software.
Helps fight scams
Google uses the AI-based machine learning algorithm for preventing spam and phishing scams. Major IT companies are also using a similar algorithm to keep their business safe. AI helps users to identify suspicious emails.
Saves time for analysts
Detecting threats is a repetitive process. AI-based algorithms can detect threats automatically hence saves a lot of time for cybersecurity analysts. They can be more engaged in developing better algorithms and learn more about the new type of threats.
Cons of using AI in cybersecurity
Hackers are also AI-savvy
Cyber attackers can learn about AI-based cybersecurity solutions and also create malicious software that can dodge the AI-based algorithm. Criminals also identify how machine learning works in AI-based cyber solutions. And by using the same technology they can make malware appear ‘harmless’.
AI is very expensive
Big data and data science are a couple of contributing factors behind the rise of using artificial intelligence in cybersecurity. These AI solutions are very expensive as there are only a few cybersecurity companies that are offering the service. Many business organizations are still afraid of taking such solutions for the fear of overspending.
Creates unemployment
AI has a knack for creating unemployment as it can work automatically and can handle a large volume of data. In this connection, many business organizations may become reluctant to keep IT experts for security purposes.
Final thought
Futuristic cybersecurity solutions will be more AI-based and this solution will become more effective in cyber defense. With the improvement of technology, the advantages will outnumber the drawbacks of manifolds.
Will AI put an end to cyber threats? What do you think?
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