Can AI Make Data Security Simpler (and Smarter)?

Cybersecurity teams often face tough choices, and there’s typically much at stake. For example, do you rely on already overworked team members to manually sift through threat alerts but run the risk of someone missing an important connection or trend? Or, consider this situation: You deploy an automated solution to generate attack alerts, only to get bogged down in a torrent of warnings. Many may be false positives that, again, waste the team’s time.

No matter the choice, many organizations’ security measures have a lot of gaping holes. If your business is undergoing its digital transformation, those gaps may be holding you back. And you’re not alone: Data security is often listed as the single biggest challenge to driving digital change.

Fight Fire with Fire to Improve Data Security

Security threats are evolving and growing increasingly sophisticated. Artificial intelligence (AI) and botnets are behind some of the slickest attacks. The best way to stay a step ahead? Arm your systems and infrastructures with the same smarts and efficiency.

Why? On a security level, AI’s value lies in its speed, repetition, and accuracy. Machine learning ensures algorithms get smarter over time, learning from wins and misses. Additionally, it can help by assessing risk and uncovering warnings faster than humans can. (And given the IT security talent shortage, that extra help can’t hurt.) Coupled with security tools, AI can perform the repetitive, tedious tasks, minute by minute. This reduces security teams’ “low-brain, high-repetition” tasks, like reviewing system alerts, and frees up some of their time. Lean teams can tackle more strategic projects, like proactive “threat-hunting” exercises that detect gaps in security.

AI on the Offense: Data Protection that Tells You What’s Wrong

AI can support a proactive posture for data security. This puts you on the offense, not just the defense. With AI behind data storage, you don’t have to sit and wait for attackers to get a foot in the virtual door—you can get clues about what they’re up to.

Security and AI applications together make the secret sauce for better offensive data security with:

• Big-data analytics: These tasks tend to fall in the category of “needle in a haystack” applications. Think scanning millions of data points for outliers and anomalies, like large file transfers or suspicious uploads.
• Predictive analytics: AI can predict or forecast the likelihood of future events based on analysis of past trends and events. For example, AI may be able to predict which assets attackers are most likely to strike.
• Behavioral analytics: AI’s unbiased approach can spot behavioral patterns such as repeated login attempts. What’s the probability that a certain user’s behavior is malicious? AI can analyze it quickly and with great accuracy. Once those outliers are located, a human can step in and do the critical thinking.

In our survey of IT decision makers across the United States, we heard loud and clear that predictive support goes a long way toward simplifying technology management tasks. In the survey, 48% of respondents cited “ability to train staff on new technology” as an obstacle to digital transformation while 39% cited “complexity of data management” as an obstacle.

These are issues that AI can help address. AI tools can reduce the need to train security teams on complicated and tedious monitoring tasks. Abstracting away complexity is another boon—especially for stressed security teams.

AI on the Defense: Security that Can Keep Pace

But don’t underestimate your defense—something many organizations already admit hasn’t kept pace with the complexity of their IT environments. Here’s where AI adds another layer of support.

AI-enabled workflows can help security teams identify threats sooner and recover faster, which can reduce costs incurred. AI is the driving force behind email filters that can flag suspicious messages that may contain…