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August - 2015 issue

Big Data Analytics: Key Component of Security Breach Mitigation

By CR Team

No longer are firewalls and isolated DMZs good enough, and nor is antivirus or any of the other traditional means of protection. After all, despite these standard measures and the unsophisticated monitoring that has largely passed scrutiny in the past, security breaches have occurred. Hackers infiltrated these systems for months, and sensitive data was stolen. Not only is detection a challenge, so is prevention.

Big data is inherently vulnerable to these breaches, making the matter of preventing them all the more urgent but doing so has become particularly challenging due to the increasingly complex IT environment. As a result, organizations are in greater need of a robust data privacy solution to prevent breaches and enforce data security. Having a good big data solution in place can help forestall and prevent data breaches before they happen, respond quickly to reduce risks and costs, minimize the impact of changes on the network and help protect sensitive data before it leaks out of the company. Using quality analytics products enables end users and other employees to be able to work without risking security.

Real-time big data analytics is a key component of an advanced threat diminution strategy. Capturing the data at network speed is one thing, but spotting the threats and responding is the challenge. Big Data analytics succeeds in this arena precisely because of the strength of what it does: analyzing unstructured data and pulling out information that you may not have even known to look for. For the first time in information security's history, skeptically analyzing security threats is within our reach.

Big data may also be able to help with data classification as companies can help prioritize threats and make sure the most sensitive information is getting the best possible protection from the organization.