Big Data generally refers to a collection and analysis of any large collection of data, both traditional and digital, as well as structured and unstructured, that lead to certain insights. In network security, Big Data can be used to both provide insight into network operations as well as enhance security by analyzing attacks and potential risks.

Used since the 1990s, the term Big Data has been defined by Gartner in 2012 as high-volume, high velocity, and/or high-variety information assets that demand cost-effective, innovative forms of information processing that enable enhanced insight, decision making, and process automation.”

This has been also known as the 3Vs definition, which has been later expanded with both Variability, which adds data inconsistency and Veracity, which adds the quality of data, to the list of Big Data characteristics, both of which affect results.
In network security, Big Data allows network administrators to process a large amount of data and analyze network security attacks and potential risks as well as detect abnormal network activity.

According to Cisco’s VNI Global IP Traffic Forecast report from 2016, by the year 2020, there will be 4.1 billion global internet users, 26.3 billion networked devices and connections, while global IP traffic will reach 2 Zettabytes. The same report suggests that advancements in the Internet of Things (IoT) will drive IP traffic and applications such as video surveillance, smart meters, digital health monitors and a host of other M2M services will reach 12.2 billion in 2020, representing nearly half of total connected devices.

For Big Data, the increase in users, networked devices, connections, and traffic, simply gives more data for analysis and should eventually offer better results.
With both the increase in amount and complexity of cyber attacks on networks, tools like Hadoop software framework and MapReduce can allow network administrators to handle and process Big Data in order to enhance network security.

Of course, Big Data analytics, machine learning, artificial intelligence (AI) and other methods need to be combined with the new generation of hardware like routers and switches which gather the date, as well as human intelligence that can understand the results of Big Data analysis and implement it into network security.

Future of Big Data and Big Data analytics in network security

While it won’t replace the traditional network security methods like firewalls, Intrusion Prevention Systems (IPS), Intrusion Detection Systems (IDS), anti-DDoS software or any other method, Big Data analytics can certainly help in network security.

Most agree that its usage is critical in modern times where data amount is rising exponentially. Big Data and its analysis can help enterprises to detect and remove threats as well as prevent attacks on their networks.

 

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