Chief Security Strategist

Are you struggling with security? If so, you’re not alone.

Security gets harder every year. Thanks to digital business and mobility, you need to guard more attack vectors than ever before. Product updates and new software innovations often result in new vulnerabilities—and hackers are getting craftier and more adept at exploiting them.

Staying on top of the risks and recognizing active exploits—before they do damage—takes relentless focus. But too much happens too fast, and the volume of assaults is overwhelming. It’s only through deploying automation that most security teams can hope to keep up.

Artificial Intelligence: The Next Step in Security Automation

Security technology continues to get better. Three years ago, we were talking about the benefits of threat intelligence. Threat intelligence services collect and analyze information about a broad array of active threats. By connecting to intelligence data feeds, we are able to get an outside view of threats to our enterprise and use that information to take precautionary action.

Not long after the emergence of threat intelligence, machine learning dominated the conversation. Machine learning refers to the ability of software applications to predict future outcomes (within a range) based on the statistical analysis of past data. By processing volumes of data, machine learning engines identify patterns quickly and thus “learn” to recognize those patterns in the future.

Today, we are looking forward to artificial intelligence. Artificial intelligence (AI), in simple terms, refers to the science of teaching computers how to think and act on their own. In the book Artificial Intelligence: A Modern Approach (3rd Edition), the authors offer eight definitions of artificial intelligence organized into four categories that represent different approaches to AI: Thinking Humanly, Acting Humanly, Thinking Rationally, and Acting Rationally.

Artificial intelligence (AI) is the next step in the evolution of security technology. We are in the early stages. Thanks to analyst predictions and marketing literature, a lot of promises are being made and there is a lot of hype. But if AI lives up to the hype, it will revolutionize your security operations in three ways:

  1. Your network will react on its own.

    A few years ago, Gartner started talking about adaptive security, referring to a security architecture built for continuous monitoring of systems and user behavior and continuous response to threats based on advanced data analytics. In fact, according to Gartner, 40% of large organizations will build a data warehouse for the purpose of advanced security data analytics. Both machine learning and artificial intelligence will play a significant role in making security more adaptive.

    Machine learning algorithms process past data from internal logs and outside intelligence data feeds to predict future outcomes. One limitation of machine learning is determining good data from bad data. If a machine learning engine processes bad data, you can get false positives or false negatives. When that happens, SOC analysts must perform further analysis before action is taken.

    Platforms that incorporate true artificial intelligence will eliminate the risk of taking action based on bad data. With AI, the security system will do more than just learn from past experience (machine learning); it will be able to process data rationally and make human-like decisions to identify bad data—without the need of a SOC analyst.

    AI will allow your network to hunt for problems, to identify trends and threats, and to respond with the appropriate action on its own in near-real time. And it will do so without compromising your business.

  2. Your staff will look and operate differently.

    If your network is able to respond on its own, how many SOC analysts do you need dedicated to monitoring, assessing, and responding to security threats?

    With a true AI system in place, you can free up people to work on other security projects. You can spend more time addressing strategic security needs, as well as patching systems. And you can finally give vulnerability management the attention it deserves.

    In addition, AI will help eliminate the skills-gap problem. You’ll need fewer people with hard-to-find skills on your staff, because the technology will be capable of handling problems that in the past depended on a person to perform.  

  3. Your product evaluation criteria and decision matrix will change.

It seems as if artificial intelligence has taken on a life of its own. Many vendors are touting AI as part of their solutions. But as I mentioned, we are in the early stages. So it’s important to understand what each vendor’s current offerings are capable of, as well as their plans for incorporating AI in the future.

As a result, your product evaluation and decision matrix must change. Artificial intelligence now becomes a serious factor to consider. Ask questions like:

  • If your solution uses machine learning, how do you filter out the data?
  • How do you differentiate good data from bad data?
  • How does your solution incorporate artificial intelligence? What features are available today?
  • What does your development roadmap look like?
  • How are you integrating threat intelligence, machine learning, and artificial intelligence within your platform?

Artificial intelligence is exciting. The field is filled with opportunity. And it offers tremendous possibility in the realm of cyber security. For information on how you can begin to build AI into your security architecture, contact your ePlus Account Executive or email eplus-security@eplus.com.

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