Big Data Requires New Thinking in Security
The Big Data boom isn't all about analytics; it's also about smart data management and protecting data assets.
As consolidation and cloud options become increasingly prevalent within the higher education setting, or institutions find themselves moving large amounts of data from one department or campus to another at or near real time, it is likely the IT department will find the requisite security also is in need of an upgrade.
As the Big Data Working Group at the Cloud Security Alliance pointed out in a November report: "Security and privacy issues are magnified by velocity, volume and variety of Big Data, such as large-scale cloud infrastructures, diversity of data sources and formats, streaming nature of data acquisition and high volume inter-cloud migration. … Traditional security mechanisms … are inadequate," the report continues.
It's estimated that 2.5 quintillion bytes of data are created every day. IBM estimates that 90 percent of the data that now exists was created in the past two years. Traditional security measures simply aren't enough to keep such massive amounts of data safe.
As part of its report, the alliance spells out the top challenges that enterprise networks now face when it comes to security in the realm of Big Data, several of which are important to higher education, including best practices for nonrelational data stores; secure data storage and transaction logs; secure computation in distributed programming frameworks; endpoint input validation and filtering; real-time security and compliance monitoring; scalable and composable privacy-preserving data mining and analytics; crypto‑ graphically enforced access control; granular access control; audits and secure data provenance.
The list is meant to "clarify specific aspects of the attack surface of the entire Big Data processing infrastructure that should be analyzed for [such] threats."
What's Next?
Even as its own risks grow, Big Data itself is being used increasingly to assess security threats and vulnerabilities. Scott Crawford, research director of Enterprise Management Associates, predicts a market will soon emerge for security algorithms that can spot anomalies.
In the meantime, some products already on the market, such as security information and event management tools, are providing new ways of analyzing security through the Big Data lens.
Gartner Fellow Neil MacDonald says threat detection tools such as RSA NetWitness and HP ArcSight ESM now serve as weapons against advanced persistent threats that can't be stopped by traditional defenses such as firewalls or antivirus systems.
Such convergence technologies require a new breed of technician who is trained to parse the various elements of integrated infrastructures, storage management, cloud computing and more. (Read Are the Days of the IT Specialist Numbered? for more on the new role of IT workers.) Data analysis certainly belongs on that list.
And while institutions today face increasing demands on networks as well as the ever-present need for greater storage, they must strive above all to implement solutions that can adapt rapidly to combat attacks on those systems.
That requires a new generation of IT professionals, trained in data science, security and agility — and always thinking one step ahead of the threats.
