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How AI and machine learning in cybersecurity bolster your defenses

Cybersecurity is front-page news, and its impacts are considerable. For instance, NBC News recently called ransomware “a major national security issue.” The same story explained that the cybersecurity industry is stretched thin, with a shortage of workers to help stem the damage. The FBI 2020 Internet Crime Report shows how big the problem is, with the bureau’s Internet Crime Complaint Center receiving a record 791,790 complaints last year, with reported losses exceeding $4.1 billion. And today’s headlines make it clear that it’s only getting worse.

While these statistics are frightening, there are plenty of proactive steps you can take to protect your business data—and, by extension, your business itself—so you don’t become another cybercrime victim. Today, two advances in technology are making a substantial impact on cybersecurity—machine learning (ML) and artificial intelligence (AI). But these technologies only add value if they are part of a comprehensive approach to cybersecurity. With that in mind, here are some essential first steps you should take to improve your defenses.

Assess and improve your security posture

You can’t understand how to best strengthen your defenses without a thorough assessment of your security posture. A cybersecurity workshop offers you expert help in identifying your weaknesses and evaluating solutions to fill those gaps. The workshop outcome should cover everything from tech configurations to resource optimization and security policies to compliance requirements. It’s an investment well worth considering as you prepare your organization for the security challenges ahead. It’s also your chance to get a deeper understanding of the value of ML and AI.

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Regardless of whether you choose the workshop approach or use other resources, ML and AI are likely to come into play once you start to implement new security solutions. While people often confuse the two terms, each delivers a very different benefit.

ML: Learning-driven security

Tom Mitchell, who wrote the book on machine learning back in 1997, defines it as “the study of computer algorithms that improve automatically through experience.” Considered by most to be a form of AI, ML gives systems the ability to automatically learn and improve from experience without being explicitly programmed to do so. In cybersecurity, ML is used to monitor your networks, machines, and other resources, looking for and learning from patterns that help it make better decisions over time.

Machine learning’s key benefit in cybersecurity is its ability to recognize when an event falls outside of established pattern parameters. With consistent monitoring, when an event does fall outside of those parameters, ML triggers an alert so that the system or personnel responsible can assess and address the issue. Essentially, ML is a reactive component of your security solution that checks off a critical box for improving your security posture.

AI: Intelligence-driven security

Britannica defines AI as the ability of a computer or computer-controlled robot to perform tasks commonly associated with intelligent beings. Put simply, AI simulates human intelligence in machines by programming them to think and act like humans. In cybersecurity, AI communicates with and crunches massive amounts of data from your network, devices, and other resources, recognizing and assessing behaviors and events. AI then correlates the events, reacting to behaviors in real time, making decisions, and communicating with other devices to proactively stop a threat before it can do substantial damage, if any.

The key benefit of AI in cybersecurity is reaction time. Put a human into the same situation, and the clock will keep ticking while they first try to understand both the source and severity of the problem. Add more time while decisions as to how to react are pondered. With AI, reaction time is measured in milliseconds. That checks another box for improving your security posture.

AI: Broader security coverage

While ML and AI both have their place in your security strategy, AI stands out because it delivers a more heterogeneous solution, helping you avoid vendor lock-in. With the ability to communicate with many machines from various vendors, AI can help you incorporate the latest security trends, cover a much broader range of threats, and react much more quickly in the event of an attack. AI can even recognize zero-day attacks that might get past outdated security solutions and systems. That’s important because staying ahead of the bad guys isn’t easy.

The good news is that both ML and AI are affordable today and should be considered as you evaluate security solutions.

Simplify security

There is no silver bullet to protect you from every security threat. ML and AI are only part of the story—a story that is getting more complex by the day. Expert help can make all the difference in the world, guiding you through those complexities and putting you in the best possible position to combat threats and minimize downtime.

Thank you for trusting us to help with your cybersecurity needs. Contact us any time—we’re always happy to help.

Jon

Meet the Author
Jon Bolden is Quest's Chief Information Security Officer
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