How Can Big Data Improve Cyber Security?

How Can Big Data Improve Cyber Security?

How Can Big Data Improve Cyber Security?

Big data is an umbrella term that covers all the digital information created and captured by companies, governments, schools, hospitals, and other organizations. It can be a powerful tool for cybersecurity because it offers a detailed understanding of how people behave online.

This allows data scientists to identify patterns in behavior that can help them combat cyber-attacks before they have any impact on critical services or infrastructure. This article will look at some examples of how big data is being used to improve cybersecurity today.

Listen to our audio to learn how big data can help improve cyber security:

Big Data: How Does It Prevent Cyber Threats?

Big Data: How Does It Prevent Cyber Threats?

Fraud Detection

One of the biggest challenges when it comes to cybersecurity is fraud.

Every day, millions of people use online services such as banks and social networks that store their personal information to identify them whenever they log in.

If an attacker could access this login process and hijack a person’s account, they would be free to cause a lot of damage. Their actions would not be traced back to them, and it might take days or weeks for the person whose identity was stolen to realize that their information had been compromised.

The good news is that most fraud detection systems use data collected from customers to identify abnormal behavior patterns as they happen.

For example, when somebody logs in from their home with their work computer, big data can help flag this activity if it suddenly occurs somewhere else.

Hackers use many tools to camouflage where they’re coming from and the general location of the target they’re trying to invade. However, cybersecurity experts can still block most of these hijacking attempts thanks to big data.

Anomaly Detection

Cybersecurity is constantly evolving; new techniques are being developed by hackers, while new tools are also being invented to detect these new techniques.

Understanding the behavior of any system is vital for this process, and it’s also one of the main methods used in extensive data analysis.

Some of this data analysis is done through machine learning and anomaly detection methods. This allows cybersecurity experts to understand how any secure network or system works and to identify abnormal behavior that shouldn’t be happening.

The black market gives hackers access to a wide array of tools and tactics, making it difficult for cybersecurity experts to anticipate what attacks will be used against them.

However, big data provides an in-depth understanding of all the different types of activity taking place within a company or organization.

This helps experts understand the threat landscape and prevent malicious behavior before it impacts critical business processes.

Mobile Security

Big data is also being used to improve mobile security for tablets and smartphones.

These devices are powerful computing tools used by millions of people all around the world, but they can be attractive targets for cybercriminals because of the large amounts of sensitive data that their users store on them.

Companies use big data to develop a comprehensive understanding of how customer behavior changes as they move from desktop to mobile. This allows them to protect this sensitive data using the same state-of-the-art protection on their business networks.

The information can be analyzed in real-time and automatically, which makes it much easier to secure these devices against cyberattacks as soon as they are created.

Situational Intelligence

Big data is also being used to provide situational intelligence for cybersecurity experts.

This involves understanding the entire environment and every activity taking place within it, which means looking at all sorts of different factors, such as whether a device is operating normally or if abnormal behavior is occurring. This makes it possible to secure mobile devices much more quickly and provide the administrators of a network with data that helps prevent data breaches.

Check out our post to learn about the Biggest Data Breaches in History.

Big data can also be used in conjunction with machine learning tools to automatically learn how normal behavior looks and then identify when something different is happening. This results in fewer false alarms, which means less time wasted examining alerts that don’t lead anywhere.

In most cases, big data is being used with a human security analyst to provide the best possible results. While this can take longer than automated techniques, it’s still a much quicker way of identifying basic patterns and improving cybersecurity overall. Big data helps identify breaches before they impact critical business processes and reduces the amount of time that cybersecurity experts have to spend dealing with false alarms.

Big Data for Cyber Security Case Studies

Big Data for Cyber Security Case Studies

People have been using big data to improve cybersecurity for a long time, and several cases show just how practical this approach can be.


Netflix is one of the world’s largest providers of streaming movies, and its use of big data to improve cybersecurity has been well documented. The company uses cutting-edge tools like learning algorithms to determine the best movie recommendations for users while at the same time blocking other programs from accessing their services without permission.

By analyzing large sets of customer interaction data, Netflix has figured out exactly what customers want to see, which means it can stream the right movies at the right time. Cybersecurity experts use this information to determine if someone is trying to access Netflix illegally or if something else is causing problems with their services. Big data helps produce an accurate picture of how their network looks and what type of behavior is occurring within it.


Another example of how big data can improve cybersecurity is found in the cloud services offered by AccuWeather. This company is also one of the world’s largest providers of weather forecasting, with thousands of subscribers all over the globe.

By analyzing usage patterns, they can gather information about each user and determine if someone is trying to access their services without permission. If something is detected, they can use machine learning to assess the situation and decide whether it is a false alarm or an attack that needs to be handled accordingly.

This information helps cybersecurity experts keep data breaches to a minimum while also helping improve the customer experience at the same time.


Etsy, an online marketplace that allows anyone to sell handmade goods or vintage items, is another example of how big data can improve cybersecurity. The site uses cloud services from Google to analyze activity patterns throughout its entire business network. This information helps them identify potential electronic attacks, malware infections, and policy violations so they can take action before they lead to a problem.

For instance, Etsy knows that when users click on certain links within their mobile app, they’re likely trying to access Etsy from an unauthorized device or location. The site can terminate the user’s session and revoke their account privileges if this happens.

Google analyzes terabytes of data every day to help Etsy improve cybersecurity. By automatically learning how regular activity looks, they can determine what behavior is suspicious and then take steps to deal with the issue right away.

This information helps cybersecurity experts assess potential threats before an attack occurs and keeps users from having their accounts compromised by another person.


Splunk is a revolutionary application that provides companies with automation capabilities to search and index their log files. It provides businesses with the insights they need from the data that they’ve amassed.

The main reason why Splunk was created was to resolve the challenge of big data being difficult to comprehend, especially when information is presented in a non-structured format. The platform is designed to collate data, analyze the details, and store it for later use.

It can be used for security analytics and security information and event management (SIEM) by using pre-built workflows, dashboards, and frameworks. Such functions allow companies to more easily understand their data so that they can make more well-informed decisions.


By using big data to identify activity patterns throughout a business network, security experts can improve cybersecurity and reduce the amount of time they spend dealing with false alarms. These tools also help determine the best course of action when something does go wrong.

In some cases, it’s safer to have a qualified cybersecurity expert on staff because it’s not always easy to tell the difference between regular traffic and something that could be a problem. This issue is compounded by the fact that it can be difficult for human staff members to keep up with everything they have to do each day without proper technology in place.

Big data helps security experts process more data in less time to make the best decisions possible, but they still need to know when human intervention is necessary. By combining the power of big data with the expertise of cybersecurity professionals, companies can create a more secure environment for their users and better protect their valuable digital assets.

As technology continues to advance and data continues to grow exponentially, it is essential for businesses and organizations to stay ahead of the curve by leveraging big data analytics to enhance their cybersecurity strategies. By doing so, they can not only safeguard their networks and sensitive information but also create a more secure digital landscape for everyone.