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This blog post is the sixth of an ongoing cybersecurity training series sponsored by OPSWAT Academy which reviews the technologies and processes required to design, implement, and manage a critical infrastructure protection program.

We commonly hear about the billions of dollars that companies are investing in big data and the implications it has on the every day consumer. Web searches, locations visited, ads clicked, photos taken – if there is a way for big corporations to find patterns in their target customers and cut above their competition, they will do so.

Setting aside the socio-political debate of consumer privacy, the technology used to find these consumer patterns is quite remarkable. These techniques can be used in objectively positive practices to protect people, companies, and their assets.

Large amounts of data on its own can appear as random events. Isolated data points of traffic jams, weather events, or market trends are meaningless if we can’t find ways to correlate the information and provide a bigger picture.

Think of a pointillism painting. If you are standing too close to the canvas, all you can see is a series of multicolored dots. Even if you were to move around the entire surface of the artwork, it wouldn’t appear as any recognizable image. It isn’t until you step back and see the painting as a whole will you see the true piece that all those dots represent. Big data technologies work in this way. They are tools that let us step back and recognize what kind of picture all these points of data are painting.

By finding big data patterns in malware attacks, we can stay one step ahead of bad actors.

In our last two blogs, we covered the philosophy behind Static and Dynamic analysis when it comes to analyzing malware. In the end, we can consider the results of these technologies as data points for our big data analysis. With proper analysis, data is transformed into information. This information can then be used to decide a course of action to change or take advantage of the emerging patterns.

At OPSWAT, our practice of analyzing malware information comes in the form of Threat Intelligence.

OPSWAT's Threat Intelligence platform analyzes data entries from in-the-wild devices across the globe. We have developed a cloud-oriented database that provides data points for binary reputation, vulnerable applications, malware analysis reports, Portable Executable or PE info, static and dynamic analysis, IP/URL reputation and, most importantly, the correlations between them. With OPSWAT’s Threat Intelligence engine, you can now upload your on-premises MetaDefender Core‘s quarantined files to MetaDefender Cloud for further analysis.

Using MetaDefender Cloud, you are getting the most accurate and up-to-date results possible. You can also see both static and dynamic malware analysis results. You will learn the differences between these two forms of malware analysis during the OPSWAT’s Sandbox Technology module.

In OPSWAT's commitment to improving the anti-malware industry, we have leveraged the benefits of community-oriented malware sharing through our own hosted Malware Sample Sharing program. Here we aggregate reports to our AV engine partners on potential False Positives and False Negatives that we have crowdsourced, or that have been reported by our customer base, all to improve data points and paint the most accurate image possible.

Intelligently analyzing patterns of malicious content is fundamental to preventing outbreaks or stopping them in their tracks.

Want to know more? OPSWAT Academy offers several cybersecurity training courses that will dive deeper into Threat Intelligence and other security technologies OPSWAT offers. Head over to, and sign up for free today!

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