How AI Solutions Are the Future of Data Security

AI is improving the security industry in many ways: Here’s why it’s so important!

AI programs can shift massive amounts of data, look for particular issues or warning signs, and even teach themselves more about data attacks. It makes sense that the information security industry would be interested in using AI to help prevent breaches and solve problems: The result is a new wave of AI-fueled solutions that are changing the way the industry works. Here are the top reasons to get excited about it.

Pinpointing Data Issues

When a breach, hack or similar data issue occurs, the first question is, “Where did this attack come from, how did it get inside, and what did it access?” That question can take a surprisingly long time to answer, especially if the attack was a surprise. An AI program can be far more efficient than a person at studying a hack and finding out where it came from so that a solution can be proposed.

Considering Outliers

One of the most important tasks that security AI can accomplish is looking for outliers. Typically, this consists of comparing past data to current data and noting the discrepancies that really stand out. For example, let’s say that a credit card has had an average monthly balance of $500 since the account was first opened. But suddenly that average jumps to $1000 during one week. An AI watching for outliers will immediately see this and raise warning flags because that’s a good sign that the card may have been stolen – and the change may never have been noticed if the software wasn’t comparing data and looking for odd situations.

Expand this line of thinking to all financial accounts and transactions, and it’s easy to see how AIs can excel at catching identify theft and financial fraud just by spotting things that aren’t normal. Of course, humans are also an important part of this process: Red flags are typically sent to a specialist who can examine the situation further to see if it’s really a problem, or if there is an alternative explanation.

Monitoring Traffic

In addition to studying obvious outliers, AI can also be programmed to analyze web traffic: This can be more illuminating that you might think. Unexpected traffic to a particular web page or login screen can indicate that hackers have gotten ahold of login data or are trying to break through security. Traffic can also indicate some other problems associated with hacking, such as DDOS attacks. While businesses frequently study traffic from a marketing perspective, few try to link changes in traffic with potential security breaches or attacks. The AI can step in and note that this could be a problem.

All About Speed

As you may have pointed out in the examples that we gave, a human could search through data and note any changes that may indicate data security issues. But it would take a long time, especially for larger companies that deal with a lot of data every day. One of the main advantages of AI in the security is speed. A well-crafted AI program can “look” at many different streams of data at once, and immediately note any issues, where it might take a person days to try to do the same – at which point the damage has already been done. When dealing with security breaches, time is of the essence, and even minutes can prove crucial in damage control. AIs allow for the fastest response time and the most effective action.

Machine Learning

Let’s assume that an AI is created to watch for security flaws – but it doesn’t really know what to look for (let’s say that the industry is young and there aren’t many best practices yet, or a lot of new data is added that the AI was programmed for). What happens then? Here is where another advantage of AI comes in handy: Machine learning. Machine learning is a complex subject, but it basically refers to AI programs changing themselves to become more efficient. This is particularly useful for new security AI. They work alongside human security experts, which feed them data about which outliers and issues indicate a security breach. The AI keeps track of this information and uses it when looking for future data issues. The result is a program that continues to learn the signs of a data problem and gets better at it as time goes on.

Testing

AI, unfortunately, is also excellent at hacking, especially hacks that rely on brute force by throwing a lot of different attempts at many various parts of security to see if any cracks show. The good news here is that white hat hackers can use AI for the same purpose – to find any unexpected vulnerabilities in software. More and more often we see security audits use AI to strictly test security through a series of large-scale hacking attempts, to see how well security measures can deal with it. This information can be treasured when improving security.

Cost Control

While initial investments in AI solutions may have a high associated cost, long-term expenses tend to be lower than hiring the equivalent in manpower. In other words, AI can take the place of security and IT employees with reducing costs. While this poses hiring challenges for the industry, it also allows companies to save a significant amount of money by switching to AI solutions.

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