How To Tackle Big Data From A Security Point Of View

Securing Your Big Data

A growing number of companies are using the technology to store and analyze petabytes of data including web logs, click stream data and social media content to gain better insights about their customers and their business.As a result, information classification becomes even more critical; and information ownership must be addressed to facilitate any reasonable classification. 

Deploying Big Data for Security

The deployment of Big Data for fraud detection, and in place of security incident and event management (SIEM) systems, is attractive to many organisations. 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 saviour. 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.

Big Data Technologies and Risks

If you research the term Big Data, you will invariably encounter Hadoop. Traditional data warehouses and relational databases process structured data and can store massive amounts of data, but the requirement for structure restricts the type of data that can be processed. Hadoop is designed to process large amounts of data, regardless of its structure.The core of Hadoop is the MapReduce framework, which was created at Google in response to the problem of creating web search indexes. MapReduce distributes a computation over multiple nodes, thus solving the problem of data that is too large to fit onto a single machine.

Specialist Skills

In reality, Big Data is more about the processing techniques and outputs than the size of the data set itself, so specific skills are required to use Big Data effectively. There is a general shortage of specialist skills for Big Data analysis, in particular when it comes to using some of the less mature technologies.The growing use of Hadoop and related technologies is driving demand for staff with very specific skills. People with backgrounds in multivariate statistical analysis, data mining, predictive modelling, natural language processing, content analysis, text analysis and social network analysis are all in demand. These analysts and scientists work with structured and unstructured data to deliver new insights and intelligence to the business.

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Source: http://www.computerweekly.com/feature/How-to-tackle-big-data-from-a-security-point-of-view