Handling the Security Breaches of Big Data!

Big Data is an immensely popular talking point, but from a security perspective, there are two distinct issues, in particular, are discussed a lot: securing the enterprise and its customers’ information in a Big Data context; and using fail-proof and safe Big Data techniques to analyze, and predict, secure incidents. One of the incredible things that big data do is that it blows away the last vestiges of platform security issues and endpoint-centric security paradigms. Many organizations training the workforce on Big Data are often aiming to protect their information resource from any security breach.

Big data means terabytes, petabytes, and Exabyte of data which means huge clusters of data in almost all sorts of formats and file extensions. Those data are getting transferred into many new and different software packages -- many of which treat security as a secondary or tertiary requirement. Big data also means the business wants up-to-the-hour (or more frequent) results, so forget about that iron-fisted control IT had over traditional data warehouse/business intelligence models. Any IT department that tries to hold to the security paradigms of 10, or even five, years ago will go the way of the slide-rule salesman. If you can't adapt, you aren't needed.

Security today is more difficult to navigate, it's more expensive, and there will be breaches no matter what we do. From a policy and budget perspective, the introduction of big data into an organization may be a tipping point for full adoption of modern security practices. It's time to get started.

Many businesses in existence already use Big Data technology for marketing and research, yet may not have the fundamentals right – particularly from a security perspective. As with all new technologies, security seems to be an afterthought at best.  Big Data security breaches will be big too when we take into account potential for more critical serious reputational damage and legal repercussions than at present.

A growing number of companies are using the technology to store and analyze petabytes of data including weblogs, click stream data, and social media content to gain better insights about their customers and their business.

Security Incident and Event Management Systems (SIEM)

The deployment of Big Data for fraud detection, and in place of a security incident and event management (SIEM) systems, is attractive to many organizations. The overheads of managing the output of traditional SIEM and logging systems are proving too much for most IT departments and Big Data is seen as a potential savior. There are commercial replacements available for existing log management systems, or the technology can be deployed to provide a single data store for security event management and enrichment.