In terms of cybersecurity, Big Data is both an opportunity and a threat for businesses. Analytical technologies offer new possibilities in terms of data protection and the prevention of possible cyber attacks.
However, cybercriminals can even benefit} of those opportunities to access huge amounts of sensitive data exploiting the most advanced technologies.
Big data raises 3 main challenges for corporations within the field of computer security. These 3 challenges are the subsequent. Protection of sensitive and private information, information and possession rights, and also the want for qualified personnel, like information scientists, to investigate knowledge.
Cybersecurity definition
Before looking at security needs, we need to define what cybersecurity is. This neologism designates a heteroclite set of actions, tools of texts of laws, methods of management of the risks of formations. It aims to protect individuals, organizations, member states and their tangible and intangible computer assets from states, criminal organizations, attackers, other governments, etc.
This IT challenge is not just about maintaining the integrity of computer systems. It is also about protecting people and governments.
What is cybersecurity in Big Data?
Protecting sensitive information may seem rather simple. However, faced with the volume of data to be processed and analyzed to prevent cyber attacks, most companies face a major challenge.
According to the news, a medium-sized network of 20,000 devices including laptops, smartphones, and servers delivers more than 50 terabytes of data over a 24-hour period.
In fact, to detect cyber attacks, more than 5 gigabytes of data must be analyzed every second.
Analytics technologies for cybersecurity
Traditionally, the technologies and tools used to stop cyber attacks are a lot more reactive than proactive. They additionally gave rise to several false alarms. This reduces the potency of companies. it’s a distraction from real threats. additionally, these standard tools don’t have the bandwidth needed to support massive volumes of information
On the contrary, analytics tools in big data provide cybersecurity professionals the power to investigate different kinds of information from varied sources and react in real time. These tools not solely gather info, however additionally connect this information, and establish correlations and connections. This makes it doable to extend potency and counteract cyber attacks more simply.
While companies can understand how to use modern technologies to protect data, big data is an obvious opportunity. The two main benefits of Big Data today are the optimization of sales and marketing strategies through access to customer data, and the detection of fraud or the replacement of cyber security management systems.
Historical data to prevent future cyber attacks
The ability to use these pieces of information permits you to use not solely current knowledge however additionally historical data. Exploiting this knowledge, it has the potential to make statistics and baselines to spot normality. Later, it’s doable to instantly verify once the info deviates from this standards. Some indicators might not be perceived once given in real time, however, these indicators are also even a lot of helpful within the future.
This historical data also makes it possible to create predictive models, statistical models, and offer new opportunities in machine learning. Thus, it is possible to predict future events.
It is not the data that makes it possible to develop an IT security strategy, but what the company is capable of doing. The ability to automatically respond to detected threats within data, and to trust data accuracy are two keys to developing a Big Data cyber security solution.
Big Data and Machine Learning: A big opportunity to cybersecurity?
Big Data and Machine Learning can be a perfect combo for cybersecurity. Big Data has already proved its value. It increases by 2.25 the probability that companies recognize an accident in the hours that follow, according to the Ponemon Institute.
Machine Learning, on the other hand, can help organizations manage the vast amount of data faster and easier. Indeed, Machine Learning solutions can scan data quickly. Then, it generates a fresco of historical patterns of negative and positive behaviors. The companies can use this technology to detect vulnerabilities, identify gaps. Then they correlate information from multiple sources. By combining these two tools, companies can thwart attacks and reduce the risk of loopholes.
In addition, the characteristics of Machine Learning and Big Data can be combined. This can predict future attacks by mapping threats. According to experts, the assimilated data can be sufficient to identify a pattern of faults.
However, there is still no platform to accurately predict when a security breach may occur. Companies must use Machine Learning and Big Data processes to detect attacks early. The goal is to prevent damage.
By using the tools of Machine Learning and Big Data, companies can develop a solid cybersecurity strategy. In the face of increasingly sophisticated threats, these two technologies make it possible to detect problems as soon as they occur. The potential damage is greatly reduced.
If you want to know more about how cybersecurity can team up with Big Data and help your business, give us a call.
