In the last couple of years, the buzz around Big Data analytics has solidified into enterprise reality, with a growing number of organizations leveraging Big Data technology for better and more actionable business insights and streamlining their operations and optimizing their campaigns and initiatives as a result. The potential of Big Data is seemingly limitless. And there's a rapidly developing key area where mining Big Data can lead to big rewards: information security. Here are three ways that Big Data can improve security.
1. More detailed baselines lead to faster, better incident detection.
One of the critical challenges that security administrators face is finding a way to detect attempted breaches and other security incidents. Traditional and legacy security solutions can detect known threats, and DLP can catch obvious data exfiltration attempts, but the new generation of cybercriminals and malicious insiders often operate in ways too subtle for such solutions to detect, particularly when attacks come from multiple vectors or take place over extended periods of time. Mining Big Data can help catch more sophisticated attacks by establishing a baseline of normal usage patterns in order to more easily identify deviations, enabling a quicker response.
2. More granular monitoring leads to more accurate alerts.
The power of Big Data lies in its ability to harvest vast and detailed amounts of data from huge numbers of devices and users—far more data than traditional monitoring solutions can provide. Mining Big Data and using the right analytics software can therefore enable user and device monitoring on a much more granular level than was possible before. Enterprise security administrators can look at large-scale or organization-wide patterns or, if necessary, drill down into individual devices or user accounts in order to identify anomalous behavior or policy violations and block bad devices or accounts as needed.
3. More data to analyze leads to more effective use of threat intelligence.
A number of security firms now offer up-to-the-minute threat intelligence databases that aggregate detailed, in-depth, real-world data from hacks and attacks as they are detected. These threat intelligence databases can be a priceless resource for enterprise security administrators—but only if those administrators have a way to take advantage of them. Mining Big Data for access and activity data and patterns and comparing those patterns to the information in threat intelligence databases allows administrators to discover even the attacks that are too new to have been addressed by traditional security solutions.
Mining Big Data for security offers a tremendous advantage to the enterprise. With Big Data analytics, organizations can detect and respond to security incidents with much greater speed than they could before. Even unknown or zero-day exploits can be caught before systems are compromised, and malicious insiders can be stopped before they steal valuable corporate information. But while Big Data technologies make this possible, it's up to the individual enterprise and the resellers it trusts to figure out how best to implement analytics solutions. Security is the selling point, but how you launch from that point depends on your knowledge of the market and your customers' concerns.