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One of the fastest-growing and most exciting fields in computer science is artificial intelligence (AI). It has been used successfully to reduce energy consumption, improve flight planning for aircraft, streamline manufacturing processes and increase revenue by providing more personalized services.

The idea of AI is not new. In fact, there's a long history of people thinking about creating machines that can behave intelligently. But it wasn't until the late 1950s, with the creation of IBM's Deep Blue computer, that anyone made serious progress on building an intelligent machine. 

And it took over 50 years before this technology worked well enough to beat world-class chess players at their own game. Now, these are impressive accomplishments indeed but are they destined to be applied only to games? Is it possible that we will see AI used for cybersecurity and other practical applications similar to the way humans use their intelligence?

If we can build an intelligent machine, does that mean it would behave just like a human being? No, because machines don't have human limitations such as size, weight, reach, or even common sense. In fact, there are no laws of physics that limit what kind of capabilities a machine can have.

What might happen then is that once you adjust for those physical limitations, you might find that computers have unique advantages over humans – they can do things faster and more accurately. They also never get tired, so it's possible these machines could tackle problems 24 hours a day without stopping to eat or sleep. On the other hand, they are expensive to build, need a lot of debugging and maintenance and only perform well if they are well-programmed.

The major benefit is that machines can make decisions much faster than humans can. They might also be able to learn from their mistakes, which means that an AI machine could become better at solving problems or making predictions. This is not true for humans because once we develop expertise in something, it takes years of practice before our brains' neural networks change enough so that we're prepared for similar problems.

Would this eventually lead to computers being more intelligent than us? Maybe or maybe not, but there's already evidence that humans are less capable of performing some very specific tasks. For example, finding a needle in a haystack is something humans are bad at, but it's not that hard for a computer (just search the haystack one item at a time until you find the needle).

What these machines would lack compared to us is common sense. For humans to get through their daily lives, they have developed subconscious instincts about understanding situations and predicting what will happen next based on past experiences. This problem needs to be solved before we can expect computers to behave similarly because otherwise, they won't understand the consequences of their actions.

Current Cybersecurity Threats

What does this all mean for cybersecurity? Right now, the greatest obstacle to hacking our devices or networks is that it's difficult, tedious, and time-consuming. But what if technology advances so much that we one day have artificial intelligence systems capable of defending against attacks by making more accurate predictions about hacker behavior? 

What happens when hackers can't outrun intelligent computer programs that will always be one step ahead of them? For cybersecurity professionals, these are important questions because they could affect their jobs in the future.

Today, there are many known security vulnerabilities, but most people don't exploit them for some reason. While you might consider this good news, it means hackers only need to find new ways to attack your system rather than trying to breach its defenses. Unfortunately, there are likely more unknown vulnerabilities waiting to be discovered by someone or some machine, so new defense strategies need to be developed.

Here are some examples of major cybersecurity threats today:

1. Social engineering

Social engineering is when an attacker tricks someone into revealing their password. To defend against this, you need to train your employees to be more careful about opening emails or visiting fake websites even if they appear legitimate. This problem might go away with the use of intelligent machines because it's theoretically possible for computers to recognize deceptive content (e.g., bad grammar) and alert users before they make a mistake.

2. Lateral movement

When you remove one threat like ransomware from your network, another often takes its place like backdoors, trojans, or phishing attempts. Hackers develop new ways to exploit systems, so it's important for cybersecurity professionals to stay on top of these developments and know what tools hackers are using today and what tools they're likely to use in the future. Most malware is created by computer experts who work alone or in small groups with their particular attack styles. 

However, there's a new trend emerging where machines are being used to automate hacking efforts and make it possible for more people to launch cyberattacks. If this becomes the norm, cybersecurity professionals will need different skills that focus on preventative defense strategies rather than how you respond after an intrusion happens.

3. Ransomware

With ransomware, hackers take control of your device (e.g., laptop) until you pay them money to give back access. For example, attackers could encrypt all data on your system so that without a key (stored on their servers), you can't access your files. If you try to restore the files from an earlier backup, they'll change them so that restoring data is impossible.

Right now, this type of cyberattack mainly targets individual users, but some companies have also been affected. And given how profitable it is for hackers, you can expect ransomware to be a more popular way for criminals to make money in the future. 

4. DDoS attacks

Distributed denial-of-service (DDoS) attacks are when someone or something tries to take down a computer system by overloading it with traffic until it stops working. Hackers do this by installing malware on computers to control how much bandwidth these machines use without the person who owns the computer realizing there's a problem. If enough hacked computers are involved in the attack, they can direct more traffic at one particular target than it can handle.

Why Cybercrime is Growing

At the moment, there are so many cybersecurity threats for several reasons.

1. There's too much money involved to stop

Because it makes criminals a lot of money, cybercrime has become one of the biggest problems facing organizations today. For example, an estimated $575 million was paid by companies that were affected by ransomware in 2016 (and that number is expected to grow ). With such large sums of money involved, you can expect these attacks to continue and even intensify if hackers find easier ways for computers to take control of other devices.

2. It takes too long to detect threats

It usually takes time before cybersecurity professionals discover new threats like malware or exploits (the tools hackers use to attack systems). This is because they need access to a computer that's been compromised. Hackers try everything they can for an attack to be successful until they find a vulnerability that lets them do what they want. 

This can take months, and in some cases, like ransomware (where the attacker encrypts data and holds it hostage), this process could go on for years before you know you're at risk or your backups are useless.

3. Many security tools don't work well together

Once vulnerabilities are discovered, companies need to patch them as quickly as possible, but often these patches only work with certain types of security software. Suppose you buy several different types of antivirus software which aren't compatible. In that case, it means hackers might slip past one product that would've detected their malware if it wasn't for another program on your computer.

Which industries are the most vulnerable

Every year, hackers get better at finding vulnerabilities in hardware and software, so it's hard to predict where they'll strike next. However, there are certain types of businesses that tend to face more cyberattacks than others. For example, if you work in law firms or medical practices, you might need special security solutions because the data on your computer is valuable to criminals. 

Even if you don't have any sensitive information on your machine, hackers can still use malware to encrypt every file and demand a ransom for the key. And given how widespread ransomware has become recently (with victims ranging from individual users to hospitals ), companies should assume their data is vulnerable until proven otherwise.

How AI can help support industrial cybersecurity 

Artificial intelligence isn't just being used to help build future robots. It's also helping cybersecurity professionals find potential threats more quickly. One example is IBM's Watson, which helps analyze large volumes of security data to determine which element might be dangerous.

AI can help support industrial cybersecurity in the following ways:

1. Detecting vulnerabilities

Because AI can analyze so much data from so many different sources, it's better able to find new security problems before they cause major damage. For example, a smart system could monitor all your backups and spot when one of them gets corrupted with malware, so you protect yourself from identity theft or losing important information. 

This also works for hardware since learning systems can examine the physical components and decide if there's been any tampering that might've compromised its security.

2. Preventing attacks

If a computer system believes that an attack is likely to succeed, it could adjust the firewall rules accordingly to ensure hackers never get through. And because these systems are always updating themselves, they'll know how to stop future cyberattacks when they find new vulnerabilities in hardware or when hackers come up with entirely new exploits.

3. Building more secure systems

Once AI is integrated into the design of a product, it means manufacturers have to create hardware that's resistant to attacks so they can't cause any damage. For example, an autonomous car has many different sensors which collect data about its surroundings, and if one stops working because of malware, the vehicle will refuse to start until it gets the green light from an AI system that controls all critical functions. This way, you'll always be safe while driving with your robot chauffeur.

4. Focusing on high-risk areas

Even with the most secure hardware, there are always vulnerabilities that can be found if hackers look hard enough. And this is especially true for AI since it's constantly learning how to improve its own performance. If computer systems are working together, they might spot that a device has an unexpected vulnerability and warn you right away so you don't waste money on devices that won't keep your data safe.

5. Rewriting malware so it can't spread 

A few years ago, security researchers used artificial intelligence to create special malware called AI Duqu, which didn't have any code in common with Stuxnet. But by using machine learning techniques, they were able to identify traits of the worm and come up with a way to remove the malware using software developed exclusively by their AI. And this is just one example of how machines can learn from prior attacks to stop anything similar from causing problems in the future.

6. Using data more efficiently

Just like humans, computers can better recognize objects if they have lots of examples of what something should look like. But unlike people, cyber security systems don't need to sleep or eat, so they can keep analyzing data even when you're not around, which means hackers have less time to find new ways into your system. Additionally, since these programs work faster than humans, it's easier for them to scan through billions of records and spot suspicious activity before it becomes a problem.

7. Collaborating with other systems

Strong AI is able to make decisions after finding the best possible solution from a group of responses. And this makes them better at working together to stop intruders since they don't need any downtime before implementing new rules. For example, if one system says it's safe for an autonomous car to drive, but another one reports that there's illegal software on board, the vehicle would come to a stop until one or both of these systems are proven wrong. 

Artificial Intelligence can be tough to understand initially, but you'll get used to it in no time. Even though it has tons of benefits for cyber security, you should always remember that hackers will keep trying different tricks until they find something that works against these systems. So if you're worried about the future of cybersecurity, AI might be the solution, but it won't completely replace humans behind the scenes.

Artificial intelligence is already making some big improvements in the cybersecurity industry by finding new vulnerabilities, preventing attacks before they start, and eliminating security risks before they cause any damage. So it's fair to say that AI might be — the future of cyber security.