We live in a digital era, and online security is more important than ever, especially for businesses and enterprises. Namely, the number of cyber security attacks on companies continuously increases, and new types of attacks are emerging on the regular.
In addition to being damaging, cyber-attacks are also costly—according to the latest numbers, the cost of cybercrime to the world economy is estimated to be more than £10 trillion. The good news, however, is that businesses and IT specialists can rely on AI to efficiently identify and prevent threats, thus protecting consumers and company data and saving billions of dollars in the process.
What An AI-Driven Network Site Looks Like
In recent years, the number of devices, operating systems, and applications used by businesses increased significantly, making an efficient and secure network infrastructure one of the most important aspects of a modern business and its everyday operations. However, as users become more distributed and as business networks grow, the attack surface cybercriminals can potentially exploit increases correspondingly.
Because of that, a traditional reactive way of manually troubleshooting network problems and collecting event logs isn’t sufficient to keep up with the ever-growing networks. Systems like LAN, WAN, and WLAN require an enormous amount of data to operate, and despite that, they do not provide a sufficient level of protection.
The good news is that a lot of work in a security operation center is either routine or repetitive. Therefore, rather than spending resources on time-consuming and tedious problems that continuously plague networks, IT teams can leverage the help of AI and automate a good chunk of their work and focus on high-value tasks instead.
The biggest use for AI in networking is that it can discover anomalous behavior and compare it with available data in real time to quickly locate and isolate problems before customers or IT technicians even recognize the problem.
In order to make the most of AI, artificial intelligence relies on machine learning, which is the use of algorithms to process data, learn from it, and make a prediction or come up with a solution without explicit instructions by a human.
In addition, the latest advancements in storage capabilities and computation have already helped machine learning evolve into more complex models, such as deep learning that uses neural networks for even greater insight and automation, making AI that much better.
Long story short, an AI-driven network is a network that relies on AI solutions to optimize user experiences and simplify operations across the entire network, including wireless access, SD-WAN domains, and all wired access. To do that, an AI-driven network uses various data science techniques, artificial intelligence, and machine learning, combining data from multiple sources to protect user and company data and prevent malicious cyber-attacks.
3 Main Advantages of AI-Driven Network Security
Artificial intelligence has massive potential in cybersecurity, and there is a number of possibilities AI can help businesses with. It can generate alerts for threats, combat existing malware, identify new ones, protect sensitive data for businesses and enterprises, and much more.
In general, artificial intelligence can do much of what an IT technician can. After all, the goal of AI is to mimic and simulate human intelligence. Of course, the computing power of AI is far above that of an average human, and it takes nanoseconds to do tasks that would take people significantly more time.
With that said, there are plenty of advantages of AI-driven network security, and we’ve picked the three main ones.
AI Can Process Massive Amounts of Data
The bigger the business or the network, the more communication and information goes through said network. Furthermore, the exchange of data can be both internal and external, making it virtually impossible for cybersecurity technicians to verify all the traffic that goes through the network.
Instead, it makes much more sense to use AI that can process a ton of data and do it significantly faster than IT personnel could do manually.
AI Continues to Learn
As we mentioned earlier, AI relies on machine learning to make decisions without requiring explicit instructions. For AI to learn, it requires data, and the more information you feed the AI, the more resources it has to prevent new threats.
Not only that, but by learning from past events, AI can use the data and deep learning techniques to recognize patterns and even improve security in the future.
Vulnerability Management and Improved Security
Businesses and entities often have to deal with thousands, if not millions, of cyber attacks on a daily basis. Apart from the sheer number of attacks, businesses will often deal with different types of simultaneous attacks, such as denial-of-service attacks, ransomware, and phishing attacks, for example.
By learning from previous attacks and data, AI can identify and correctly prioritize each threat. In addition, AI is impervious to fatigue and lack of focus, both of which often lead to human error, making it significantly better at prolonged and tedious tasks.
Businesses That Implement AI Network Security
Even though the term artificial intelligence may sound like something from a sci-fi movie, numerous companies have already been using AI on a day-to-day basis.
In fact, did you know that Google’s Gmail has used various machine-learning techniques to filter spam emails since its launch nearly two decades ago?
Naturally, Google isn’t the only company that uses AI and ML, and nowadays, there are dozens of use cases and industries where AI has proven more than useful.
The use of AI in the financial sector is on the rise, and corporate banks use artificial intelligence to assist them with various tasks. For example, AI can analyze customer spending habits and help banks with risk assessments in order to determine whether someone is eligible for a loan.
At the same time, AI can help with fraud detection and prevention and can even assist bankers in finding potential customers based on several parameters.
In addition, AI can help businesses in the finance sector with automation, reduce the need for repetitive work, help prevent human error, and reduce false positives. Furthermore, AI can also scale to tackle both short-term and long-term projects and much more, making it an ideal addition to the finance industry.
User security and steadfast transactions are one of the most important factors in online gambling, which is why reliable blockchain casinos put a big emphasis on protecting user data and making sure transactions that occur on the platform are encrypted and well-protected.
Additionally, online casinos use AI to improve customer experience and create personalized offers based on players’ preferences. In addition, by analyzing patterns and player data, AI can help online casinos prevent cheating or help detect any suspicious transactions on the platform to help deal with illicit activities, such as money laundering.
Lastly, by user activity, AI can identify gambling patterns that are considered problematic—for example, if a user is suddenly spending significantly more than usual or chasing after their losses.
By doing so, casino representatives can potentially contact the player or even temporarily suspend their account, mitigating the damage and helping with problem gambling.
One of the most common uses of AI in healthcare is to help automate administrative tasks, saving precious time and money. The AI can also use technologies like voice-tot-text transcriptions and help doctors and nurses order tests, prescribe medications, and write chart notes.
Furthermore, by using natural language processing, AI can support physicians and inform them about patient treatment plans. Not only that, but there is also plenty of potential for AI to help with clinical judgment and diagnosis, despite the feature still being in its infancy.
In addition to everyday tasks, AI can also help surgeons with AI-assisted robotic surgery. For example, the Da Vinci AI, one of the most advanced surgical robots, can help doctors perform complex procedures with even greater control than they would have with a traditional approach.
On the other hand, a miniature robot, Heartlander, can make small incisions on the patient’s chest and perform mapping and therapy over the surface of the patient’s heart. Finally, AI can even analyze images significantly faster than normal and assist surgeons by providing them with data in near-real-time.
The Bottom Line
Artificial intelligence improves the way security experts analyze and study cybercrime. It also enhances existing technologies that companies use to prevent cybercriminals and keep data safe, making it crucial in securing traffic for businesses and enterprises.
When it comes to network security in particular, the AI’s capability to process large amounts of data in nanoseconds is crucial in helping IT experts combat hundreds of thousands of cyberattacks businesses experience on the regular. Not only that, but AI allows security experts to automate various operations and focus on more daunting tasks.
Because of its numerous advantages, AI is used everywhere, from finance, healthcare, and online entertainment to industries like real estate, food tech, manufacturing, travel, and many others.
In addition, industry experts are continuously looking for new ways to improve artificial intelligence and machine learning, further cementing AI’s place as one of the most important aspects for businesses and entities across many industries.