Getting from point A to point B in a car always seems to be a pretty easy proposition, at least until you’re behind the wheel and moving. On a map, look for the largest road(s) with the greatest bandwidth capacity, which in the US usually means a highway or interstate, and just take that route. If one road meeting this criteria doesn’t exist, then cobble together a series of them following this general pattern (biggest roads with the most capacity), and you’re still good, right?
This whole methodology assumes, of course, that you want to get directly from point A to point B in the quickest possible manner without any regard to other conditions or factors, such as the scenery along the way, points of interest you might want to check out, or anomalies such as accidents or unusual/unexpected traffic patterns necessitating a change in course. Once you start factoring in more than just the criteria of shortest and fastest route, you find that you can get from point A to point B in any number of ways. It all depends on what you’re really after.
The same is true of data protection. Every enterprise has sensitive data that they don’t want to expose or become public, for a variety of reasons (legal, regulatory, ethical, etc.). That data in its natural, usable state is plain text which is readable, comprehensible, and potentially actionable. Let’s call this point A for such data. Point B, then, is a secured and protected state in which the information is not fully readable except by authorized users, is at least partially if not wholly incomprehensible, and hopefully not actionable by the wrong people who get ahold of it and want to use it for nefarious purposes. For most businesses, they want to move their data from point A to point B in the quickest, most pain-free manner possible. However, what is the quickest way, and does that exclude other factors along the way such as internal usability, reversibility, and cost-effectiveness?
We’ve had an excellent eBook available for several years now that’s still very current and illustrates this concept of the many roads to data protection. If you haven’t checked it out, now might be a great time to access it. Analysts such as Gartner are also doing an enormous amount of research into the more focused area of data protection methods (data masking, encryption, tokenization, and format-preserving encryption) and how these relate to the burgeoning market for next-generation data security—which means the way that data security platforms are beginning to aggregate numerous capabilities aside from data protection (and even several different types of data protection, too) into comprehensive data security platforms. We recently made available one of Gartner’s latest reports about trends in the data security platform market. This one, too, is worth a read if you find yourself with a little downtime over the next few weeks and want to catch up on cybersecurity research.
Our enterprise data security platform certainly measures up well in its evolutionary trajectory to what Gartner sees happening in the market. As far as data protection methods are concerned, we provide multiple routes from A to point B, depending on the data being protected, how that data will be treated internally (and even externally) within the organization, and other factors influencing the organization (again, things like regulatory concerns or operational matters). Sometimes what’s needed is irreversible data masking. At other times, format-preserving tokenization is most appropriate. The fact is that we continue to provide many different routes, not just one, even while we continue to architect new ones such as a recently announced approach to format-preserving encryption. Sometimes the right question to ask when getting behind the wheel isn’t, how do I get there from here? Perhaps the more relevant question is, why do I want to get there from here? The same, of course, applies to data protection. The successful journey in either case depends on taking the most appropriate route for your purposes.
Gartner® Report: “2022 Strategic Roadmap for Data Security Platform Convergence”
“Gartner® defines Data Security Platforms (DSPs) as products and services characterized by data security offerings that target the integration of the unique protection requirements of data across data types, storage silos and ecosystems”. To learn more about DSPs read 2022 Strategic Roadmap for Data Security Platform Convergence, Gartner® report, click the button below for complimentary access to this report: