There are countless ways that an organization can fall victim to a cyber attack. Cyber criminals are not sitting on their laurels. They are coming up with new and evolved ways to attack your business.
Your business needs to analyze countless time-varying signals if it will accurately calculate its cybersecurity risk. This means that cybersecurity has reached a point where it is beyond the ability of humans to carry it out on their own anymore.
Artificial intelligence tools for cyber security are now helping information system teams improve their security posture. AI is reducing the breach risk and making it possible for enterprises to react faster and more effectively when a breach is in process.
The power of artificial intelligence and machine learning comes from their ability to quickly analyze countless events and identify multiple threats. This includes software generated threats, risky behavior that could indicate a phishing attack, or the filtration of malicious code. This capability separates AI from traditional static forms of cybersecurity, such as a VPN.
AI is software that can learn over time. Information garnered from past events helps AI-based cybersecurity software to predict and prevent current and future attacks. Machine learning makes it possible to create behavioral profiles and assign these to networks, assets, and users. AI can then identify and respond to behavior that deviates from previously established norms.
Is Artificial Intelligence Just Another Way of Saying Data Analytics?
There are a lot of buzzwords currently being used in cybersecurity. Terms like the cloud, big data, the Internet of things, machine learning and artificial intelligence are popular. The use of these terms can generate some confusion.
There are several so-called AI cybersecurity solutions that are not actually artificial intelligence. While these forms of cybersecurity software can analyze large amounts of data to try to predict outcomes, this is not artificial intelligence in its purest sense. Artificial intelligence goes a step beyond analyzing data to the point of being able to reproduce cognitive abilities and automate tasks.
Data analytics is a static process. It examines large amounts of data to draw conclusions using specialized systems. However, data analytics is not self learning nor iterative.
On the other side of the coin, artificial intelligence systems are dynamic and iterative. The more data they analyze, the smarter they get. They are actually learning from experience. The more they learn, the more autonomous they become.
Applying AI to Cybersecurity
Organizations are finding it difficult to keep up with and prioritize the number of vulnerabilities they face daily. Conventional cybersecurity techniques are reactionary. They respond once hackers have already exploited a vulnerability.
Machine learning and artificial intelligence can improve an organization’s ability to manage vulnerable databases. User and event behavior analytics when coupled with artificial intelligence can monitor and analyze the way a user behaves on servers and then identify anomalies that indicate a clandestine attack. This gives organizations a preemptive defensive weapon that can identify vulnerabilities before these are reported or patched.
With conventional tools, attack indicators or signatures are used to identify threats. With this technique, identifying previously discovered threats is easy. However, cybersecurity tools that are signature based lack the capability to identify previously undiscovered threats. As it sits, this type of cybersecurity is only beneficial 90 percent of the time.
Artificial intelligence, when used on its own, can increase the rate of detection to 95 percent. The problem with using artificial intelligence on its own is that it might produce false positives. What is the fix? A combination of AI and traditional threat detection tools. When used in tandem, AI and traditional cybersecurity can increase detection rates up to 99.9 percent. This virtually eliminates false positives.
AI also adds behavioral analysis. This is powerful because it gives your organization the ability to create profiles for each application your organization uses. This is done by evaluating data from end points.
On the other hand, traditional cybersecurity tools have shown to be very effective in fighting against cybercrime when implemented together. The pandemic is a good example of that. Many countries have had different strategies for managing drastically increasing numbers of COVID-19 related cyberattacks since March 2020.
In Australia, for example, phishing scams were one of the biggest threats during the pandemic according to the Australian Competition and Consumer Commission‘s report. The Australian Cyber Security Centre created a set of useful tips to help Australians protect themselves against any type of cyberattack.
Specifically, they recommended tools such as password managers, reputable antivirus software, and highly encrypted VPN services that work well in Australia. However, not all VPNs are created equally, and it’s very important to use one that comes with specific features to ensure it can actually be effective in preventing data breaches. According to Brisbane-based security analyst Will Ellis of Privacy Australia, Malware infections and data leaks can still occur when using a VPN, which is why it’s extremely important to look out for security features such as DNS leak protection, strong encryption algorithms and anti-virus software support.
Individuals and companies that took that advice were able to protect themselves from phishing scams, malware attacks, identity theft, breaches, and other dangerous forms of cyberattacks. As we mentioned before, AI and machine learning tools (when implemented correctly) would be able to improve the effectiveness of traditional cybersecurity tools to hacking-proof levels.
Real-Life Applications of AI in Cybersecurity
Immigration officers and custom officers have been trained to identify people who are lying about their intentions. However, this process is anything but foolproof. Humans get tired, they get distracted, and emotion and prejudice can skew their results.
However, the Department of Homeland Security is using a system called AVATAR. This system uses a combination of big data and artificial intelligence to screen the facial expressions and body gestures of people. It identifies fluctuations in a person’s facial expressions and gestures that might show suspicious behavior.
This system uses a virtual face to pose questions. It monitors fluctuations in people’s voice tones and their answers. The data collected is analyzed against other elements that show a person might be lying. If suspicious behavior is flagged, the person will need to pass through further inspection.
Darktrace is another platform that takes advantage of machine learning and artificial intelligence. This platform monitors and models the behavior of each user, device, and network. It learns normal patterns. It uses what it has learned to identify anomalies in behavior and then alerts security personnel in real time. Using artificial intelligence in this way allows security personnel to mitigate risk and carry out further investigations before damage or data breaches occur.
Is AI the Magic Bullet for Cybersecurity?
No. AI is a powerful tool that when used properly drastically improves the security profile of an organization. However, there are some limitations.
The first limitation is resources. Artificial intelligence is resource heavy. It requires massive computing power, memory, and data. Most organizations do not have the resources to take full advantage of artificial intelligence.
For AI systems to work, they need to be trained using massive amounts of unique data sets of anomalies and malware code. Getting accurate data requires phenomenal amounts of resources. Most companies cannot afford to do this.
Hackers are also using AI. AI-based malware is dangerous. It can learn, adapt, and become more advanced. It can learn from AI cybersecurity tools.
Artificial intelligence is going to continue to impact cybersecurity. Its importance will only grow as more technology becomes a part of everyday life. There is a constant back and forth about whether AI is a good thing or a negative thing. But that is a discussion for a different day.
Cybersecurity benefits from the faster analysis and adaptability of AI. Organizations will need to adapt AI-based cybersecurity in order to keep pace with the sophisticated AI-based cyber attacks hackers are using and will continue to use going forward.
