How Big Data Analytics Boosts Cyber Security

As more and more parts of our lives become connected to the internet, and more of our daily transactions take place online, cybersecurity is becoming an increasingly important topic. Just as modern technology changes more quickly than ever before, so do cyber criminals create newer and faster ways to target and rip off organizations. New malware is difficult to detect using previous strategies, which means we need new cybersecurity strategies to ensure commercial security.

One such new strategy is to use big data analytics. Big data analytics is an automated process by which a computer system examines large and varied sets of data to find patterns and trends. It is currently used to help companies track customer preferences and therefore better target their products and advertisements to specific users. However, with some reprogramming, those same big data analytics could be used to detect, respond to, and ultimately prevent cybercrime.

Here are some ways that big data analytics could help in the fight against cyber criminals.

1. Identifying Anomalies in Device and Employee Behavior

It is nigh-on impossible for a human user to manually analyze the millions of alerts that internet customers generate each month and pick out the valid ones from the threats. A problem cybersecurity experts have faced in the past is having more false alarms than accurate identification of malware. By monitoring networks and analyzing the myriad behaviors of people who use those networks, automated big data analytical systems could learn to distinguish normal online behavior from abnormal ones, just as they currently distinguish users’ preferences for different brands. The more transactions it monitors, the better the system will become at recognizing anomalies in client behavior and discerning real people’s transactions from malware. This will result in fewer false alarms due to human error, allowing cybersecurity experts to focus on actual threats.

2. Responding Quickly to Malware Attacks

When a cybersecurity threat occurs, it is important for a system to be able to not only detect the threat but also trigger important actions to stop the malware from causing a lot of damage. Big data analytics could be programmed to not just passively detect malware and other anomalies, but to actively respond to signals of malware and other anomalies. Such responses could include automatically cutting off the devices that are causing those anomalies or sending notifications to cybersecurity experts about the detected potential threat. The big data analytics could provide human users with a detailed report on the incident, including the clues it found and identified as anomalies. It is possible that the system could even identify the specific employee or another user who was attempting to steal the data, saving cybersecurity organizations a lot of time and effort in hunting cybercriminals down.

3. Assessing Networks for Future Vulnerabilities

Of course, it is not enough to only detect and respond to threats. As technologies change, it is important to be able to identify potential future threats. The most useful big data analytical system, as it conducts its network monitoring, could also analyze its data to identify databases that are either particularly appealing to hackers because of their large amount of information related to customer identity or particularly vulnerable to hackers because of their lack of cybersecurity measures. In this way, big data analytics could track down and help remove sources of potential cybersecurity risks.

As more money, power, and information becomes connected to the internet, and more criminals decide that it is time to attack and abuse those internet-based data systems, it is more vital than ever before that cybersecurity keep ahead of malware threats and other kinds of cybercrime, in the name of preserving commercial security and protecting the people of this increasingly interconnected, digital, internet-using world. Big data analytics, though currently mainly the tool of advertisers, could be a part of the solution to cybercrime.

With some reprogramming, big data analytics could help cybersecurity experts and organizations prevent malware attacks by identifying anomalies in transactions, respond to malware attacks by shutting down impacted systems and notifying human users who need to know about the attacks and assess rapidly-changing networks and systems for future cybersecurity vulnerabilities.