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AI Cybersecurity Outmaneuvering Attacks in New Ways

HwHowAI cybersecurity outmaneuvering attacks in new ways


Artificial Intelligence (AI) chatbots are getting all of the attention these days. However, one of the fastest-growing uses of the software program is AI cybersecurity. That is because it saves companies, governments, and individuals money by detecting and countering cyber attacks in real-time. 

Worldwide, the AI cybersecurity market is valued at $22.2 billion this year, according to MarketsandMarkets Research. However, it is expected to reach $60.6 billion by 2028. That is a compound annual growth rate of 21.9 percent.

Rising Cybercrime Attacks

Every hour 97 individuals or organizations fall victim to a cybercrime, according to SurfShark. Accordingly, on the day you read this, 2,328 successful cyber attacks will be launched resulting in the loss of millions of dollars.

Those losses are expected to increase by 15 percent per year, according to Cybersecurity Ventures. As a result, annual losses are projected to reach $10.5 trillion by 2028.

“If it were measured as a country, then cybercrime would be the world’s third-largest economy after the U.S. and China,” writes Steve Morgan, founder of Cybersecurity Ventures.

Rising AI Cybersecurity Response

The cops on the beat to thwart this rising cybercrime wave are AI and its sidekick machine learning (ML).

“AI is big data,” explains Mansour Khatib, CEO of GBT Technologies, Inc., Santa Monica, CA. “AI manages massive amounts of data to detect something that’s suspicious. It can stop an attack and, based on the data it has gathered, it can know the attack’s next move.”

AI is constantly gathering information on cyber attacks worldwide. From the knowledge gained by AI, ML can understand global and industry threats to counter an attack.

AI Cybersecurity Flexibility

In theory, humans could do the same thing AI Cybersecurity does. However, it takes much longer for people to realize a system is under attack. Many successful attacks on systems unmanned by AI have gone undetected for days.

Traditional cybersecurity is limited. Once a piece of malware is found, it is blacklisted and examined for information. This method may stop attacks from that specific malware but, it can not detect a new unique attack.

In addition to its superior speed and capacity, AI is more flexible than traditional cybersecurity methods. 

Using ML, an AI cybersecurity system learns patterns, determines relationships between patterns, and identifies new attacks and attackers based on similarities to previous ones. In short, AI can adjust on the fly.

IoT and AI Cybersecurity’s Future

Increasingly the world is becoming connected through physical objects that transmit and receive information through the internet. Accordingly, that is referred to as the Internet of Things. Examples include your cell phone, your car, your thermostat, and even your refrigerator. 

“There are refrigerators on the market today that can tell you when you are low or out of something so you can reorder it,” says Khatib.

Because the refrigerator communicates through Wi-Fi, it can send messages to your smartphone or home assistant, such as Google Assist or Alexa. 

As more things become connected to the internet, cyber crooks have more avenues to steal your personal and financial information.

“You might have a smart light bulb,” says Khatik. “This light bulb sends you information through your router. Someone could gain access to your router by accessing the light bulb. From there, they could get into your computer and get all kinds of information.”

AI cybersecurity could stop such attacks. But, is it affordable?

“Absolutely,” says Khatib. “In today’s world, it is becoming cheaper to protect your home and personal devices. You can buy a cheap computer today that has fingerprint recognition.”

From April 2021 to April 2022, CujoAl studied 1.7 billion connected devices in North America and found that about half are not capable of running antivirus software. However, AI cybersecurity can be added to a router to protect all devices on a network. 


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