How big data analytics combats cybercrime?
Big data analytics is used to make sense of the growing volume of data to generate profitable insights. However, did you know that it can protect against cybercrime as well? With over 4.5 billion data breaches in the first half of 2018, cybercrime has grown in both frequency and scope, breaching conventional defences and exposing the information of both institutions and individuals. However, a solution is difficult to come by because cyber crimes are constantly changing in nature. Is there a fool-proof solution that will block cybercrime? In this blog post, I am going to explain why data analytics is the future for combatting this serious threat to information.
Why is it challenging to combat cybercrime?
Before big data analytics, there were two challenges to combatting cybercrime: The growing volume of data and the range of attacks. Cybercrime does not follow one distinguishable pattern or method (at least, on the surface) because there are several attacks that occur, ranging from hacking organisation records to credit card fraud. It becomes nearly impossible to combat these incidents, which are growing more and more frequent.
The second reason is the growing volume of data. With organisations like banks, hospitals and government organisations gathering petabytes of data, it becomes even more difficult to find suitable methods for protecting the data. Without data analytics, employees have to comb through large data volumes, forcing them to look for a needle in a haystack. For these reasons, cybercrime has been impossible to combat, at least with conventional methods.
How is big data analytics a solution?
Big data analytics provides a solution because it is built to handle growing volumes of big data. Data analytics is more than capable of handling the large volumes of data organisations store. The reason behind this capacity is because of the sophisticated data algorithms that make up a data analytics framework. By using big data analytics, it is possible to process, manage and secure large volumes of data.
The second reason is that big data analytics frameworks can breakdown and discover the differences between various cybercrime attacks, like hacking and online fraud. This is because analytics can breakdown the data surrounding the attack and discover the similarities by studying patterns with pattern recognition technology, despite the differences in the attack method.
Point analysts in the right direction
One of the biggest advantages of big data analytics is its ability to detect anomalies. Whether it is in the network or on devices, analytics can detect odd behaviour, which can then be flagged for further investigation. Big data analytics can detect anomalies because it can analyse data on a massive scale to discover connections and patterns. Hence, if there is a deviation from the norm, analytics will sense it at once, and flag it for further investigation. It is an incredible asset to have because it can pinpoint and help network analysts in the right direction, allowing them to target the time and energy towards the most likely causes of an attack.
Big data analytics can predict crime before it occurs
Big data analytics can do more than just analyse data – it can also predict future attacks before they even occur. Analytics can predict the future (or some variant of it) because of its ability to study data and draw conclusions from it. This is especially the case when AI and machine learning are incorporated into an analytics platform. The ability to anticipate attacks before they happen is one of the most effective ways to combat cybercrime because it allows organisations to protect their data more effectively and develop a network that guards data.
Grasp the scope of the cybercrime
By investing in big data analytics, organisations can identify the scope and breadth of the cybercrime offense taking place. Organisations can categorise the type of cybercrime attacks and how frequently they occur, ensuring heightened levels of criminal justice. Analytics can also leverage historical data to study the type of attack, the frequency of attacks and the type of information that’s frequently targeted. With this information, organisations can plan for cybercrime attacks intelligently, pouring more resources into vulnerable areas.
Seeing the bigger picture
Cybercrime does not happen in isolation, there is a growing consensus amongst professionals, that there is an ulterior motive for stealing information from organisations. In fact, some security professionals have stated that cybercrime is an important source of funding for terrorism. Therefore, if organisations can cut down the incidence of cybercrime by half, they would able to cut funding to terrorism by half. It is one of the reasons why SAS, one of the leading providers in commercial analytics, devotes a lot of time and resources to combatting cybercrime. If organisations are to combat cybercrime meaningfully, they will need to install or optimise a big data analytics platform to protect their data – all while improving the livelihoods of the people around them.