Better Security Analytics? Clean Up the Data First!

Our industry is losing the cybersecurity war. Not a week goes by in which we don’t hear about a new data breach. Overwhelmed security operations center (SOC) personnel, who already were in short supply, are leaving the profession because of sheer exhaustion. The rapid rate of change brought on by DevOps and cloud computing has completely overwhelmed our traditional, rules-based perimeter defense. Sophisticated hacking syndicates and nation-states are coming at us with machines, and we’re responding with humans.

The industry’s current response to this has been to offer practitioners a dizzying array of shiny, new artificial intelligence (AI)-enabled analytics regimes, each of which claims to have better algorithms than everybody else. According to Dan Koloski, Vice President, Oracle’s Systems Management and Security products group, the problem with that approach is that even the best analytics algorithms operating against incomplete and unclean data aren’t going to yield useful results.

Read more about why Dan Koloski thinks that AI-enabled regimes will yield decisions we can’t entirely trust unless we fundamentally rethink our data tier and start presenting machines with cleaner data, on DarkReading.

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