How AI Is Improving Threat Protection

Successful cybersecurity attacks can be so severe that they shut down business operations, erode the public’s trust in an organization and require substantial financial resources to go toward recovering. So, it’s crucial for the security professionals who work for those companies to continually invest in updated threat protection technologies.

Artificial intelligence (AI) is one of the technologies making a particularly impressive impact on threat protection efforts. Here are four examples of why that’s true.

AI Enhances Biometric Security Efforts

Biometrics-based security typically involves using something related to a person’s body or behavior to screen for access privileges. One of the most common examples of biometrics security in action is a fingerprint reader, such as those in some high-end smartphones.

Some companies use artificial intelligence to speed the processing of biometrics platforms and make them more capable of handling more substantial quantities of information.

For example, one authentication process uses advanced deep neural network techniques to continually authenticate users based on their keyboard usage behaviors.

If the system detects anomalies, it can immediately notify a company’s security professionals, pose a typing challenge to the end user or instantly shut down a workstation. This use of AI would not be ideal for a computer terminal used by dozens of people, such as one in a publicly accessible area.

However, it’s easy to see how it would work well for a computer that gets used by just one person or one containing proprietary information. For example, the computing equipment in a CEO’s office would benefit from this kind of protection, as might a laptop operated by someone who deals with the technical specifications for a new product in development.

It’s Helping Security Professionals Benefit From a Larger Talent Pool

One of the positive things about AI is that it’s no longer a topic restricted to science-fiction novels. Since it’s part of the mainstream, it’s easier for individuals to get acquainted with AI, even without access to expensive tools. This development means that the people and organizations that intend to use AI can ask for help from a bigger group of people who are ready to provide it.

In one recent example, the U.S. Navy launched a contest that challenges private-sector individuals to come up with the best AI-based cybersecurity measures. The rewards for doing so include a $100,000 first-place prize and $50,000 for the second-place finisher. Submissions are accepted through Sept. 30 and they must consist of an endpoint security solution and accompanying white paper.

This approach lets people lend their expertise to the military without going through the extensive process of being awarded a contract—something that’s out of reach for many security enthusiasts.

AI Makes Cybersecurity Professionals More Productive

Threat detection and vulnerability management are two of the primary concerns for cybersecurity professionals. It’s crucial to address weak points at both the application and network level. Plus, in addition to mitigating current threats, internet security professionals must target the root causes of identified vulnerabilities.

Estimates say that by 2021, cybercrime will cost the global economy more than $2 trillion. This means that companies must move away from only prioritizing cybersecurity for compliance and make actual risk assessments. AI can help cybersecurity pros make the most of their time by learning the characteristics of normal network traffic and warning them of deviations that could signal problems.

Some AI platforms can recognize threats that have never affected a network before. That quality lets them play supportive roles to improve the working knowledge of the threat landscape that cybersecurity professionals possess.

One solution developed by researchers works similarly to the human autonomous nervous system. It takes a holistic look at interconnected systems, such as those used for an electrical grid. It also learns and adapts from attack attempts.

Additionally, AI technology makes cybersecurity employees less likely to spend too much time investigating false alarms. That’s because the algorithms help detect genuine issues by separating them from the noise.

It’s Able to Spot Flaws Faster Than Humans

The previous section highlighted how AI helps cybersecurity professionals work smarter by spending their time addressing the cybersecurity threats that warrant the most attention. A related example that emphasizes how AI has upended threat detection technologies centers on how fast it can find problems compared to people.

A team of researchers developed a deep learning tool that scans millions of lines of software code in seconds. It looks for the vulnerabilities that hackers typically exploit to gain entry into systems or programs. One of the people working on the project got the inspiration for the technology by thinking about how researchers at Stanford University trained neural networks to recognize the shared characteristics of cats in images.

He wanted to teach a neural network instead to detect the aspects of vulnerabilities. The research achieved that aim, and efforts are underway to make the scanning tool fix software errors rather than merely finding them. Eventually, the researchers want to offer what they’ve accomplished to corporations that would deploy the scanner on a laptop.

AI Makes Threat Detection Easier to Manage

New cyberthreats arrive so rapidly and regularly that even the most dedicated security professionals can’t stay abreast of all of them.

Fortunately, AI assists in meaningful ways. In addition to the ones mentioned here, more AI-driven threat detection technologies will become available as the companies developing them continue to react to marketplace needs and technological innovations.

Kayla Matthews

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Kayla Matthews

Kayla Matthews writes about cybersecurity, data privacy and technology for Digital Trends, Cloud Tweaks, TechnoBuffalo and The Daily Dot. To read more of Kayla’s articles, visit her blog Productivity Bytes.

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