This is a guest post by Tiffany Rowe
In the past, computer security could do little to guard against infection; instead, early security software merely reacted swiftly to threats detected on the machine. Thanks to data, that changed. Today, security tools are effective at predicting threats and guarding against them, so users are hardly inconvenienced by malicious attacks. It is only because diligent data-gatherers accumulated information on malware and attack patterns that cybersecurity software could improve so dramatically – and it will be thanks to data that security continues to improve.
How Big Data Improves Cybersecurity
A recent study on cyber threats found that the biggest gaps in businesses’ cybersecurity strategies concern the ability to detect malware, corruption and attacks before they devastate the organization. By applying Big Data to security, businesses can close those gaps and protect themselves against emerging cyberthreats.
With every attack, regardless of whether it was successful or unsuccessful, cybersecurity professionals and organizations can collect data on the event. This data includes information such as existing defenses before the attack, vectors of the attack, symptoms of the attack, targets, thefts and more. Every day, overwhelming amounts of data are created and collected for the purposes of understanding the current threat environment and strengthening security – and it’s working.
A recent study found that over the past few years, there has been a decline in the success of security breaches. One reason might be the overall increase in security awareness; businesses know they need only a basic layer of protection to ward off the vast majority of attacks. However, available security solutions have also improved in recent years thanks to the accessibility of data. By understanding what is happening in the wild, security organizations can develop software solutions that better protect against common types of attack, and they can build tools that learn and act autonomously to keep their clients safe.
Trend Micro’s TippingPoint intrusion prevention system is an excellent example of how data can dramatically improve cybersecurity solutions for businesses. TippingPoint closely monitors network traffic in real time to detect potential threats. Using data from previous network attacks, the software can recognize the signs of a breach and take action to block malicious traffic without human intervention. This cybersecurity solution relies heavily on machine learning technology, as nearly all cybersecurity software of the future will also do.
Artificial intelligence is the most anticipated tech in the cybersecurity landscape. Using machine learning, security providers will be able to develop software that learns and adapts without updates and patches, ensuring that individual organizations are fully protected against the specific threats that jeopardize their data and devices. By accumulating Big Data, analyzing it and applying it, we are slowly but surely approaching a time when AI will dominate cybersecurity.
Big Data Is Also a Significant Threat
Data is precisely what most cybercriminals are after, so by collecting data, businesses are making themselves bigger and juicier targets for cybercrime. Often, business data includes payment information, personal identification information, login credentials and similar valuable numbers and codes. Criminals can use this data for personal gain in a variety of ways – but in the future, cyberattackers could use valuable data in more devastating ways.
Just as trustworthy security organizations like Trend Micro are using Big Data to develop stronger protections for business, so are malicious cyber criminals using Big Data to build more effective methods of attack. In fact, malicious attackers are even developing their own machine learning and AI tools to increase the success of their attacks, making it even more imperative that security professionals develop equivalent protections. In fact, it shouldn’t be doubted that cybercriminals are already devising methods of attack that organizations have never encountered before, which makes AI tools critical for safety and security.
Big Data is undeniably important to the advancement of civilization. Not only does data help organizations better identify their audiences’ needs and wants, but it keeps businesses and consumers safer from existing threats. Unfortunately, data is not just a force for good; bad actors can also employ data to expand the scope and power of their attacks. Thus, it is critical that businesses equip themselves with the strongest and most up-to-date security systems available, especially those that employ machine learning and similar futuristic features to fight threats.