Understanding and Selecting Data Masking: Use Cases

As we approach the end of this series, it has become clear that I should really have started with use cases. Not only because they are the primary driver of interest in masking products, but also because many advanced features and deployment models really only make sense in terms of particular use cases. The critical importance of clustered servers, and the necessity for post-masking validation for some applications, are really only clear in light of particular usage scenarios. I will sort this out in the final paper, putting use cases first, which will help with the more complex later discussions. But here they are. Use Cases Test Data Management: This is, by far, the most important reason customers gave for masking. When polled, most customers say their #1 use for masking technologies is to produce test data. They want to make sure employees don’t do something stupid with corporate data, like making private data sets public, or moving production data to insecure test environments. That is technically true as far as it goes, but fails to capture the essence of what customers look for in masking products. In actuality, masking data for testing and sharing is almost a trivial subset of the full customer requirement; tactical production of test data is just a feature. The real goal is administration of the entire data security lifecycle – including locating, moving, managing, and masking data. The mature version of today’s simpler use case is a set of enterprise data management capabilities which control the flow of data to and from hundreds of different databases. This capability answers many of the most basic security questions we hear customers ask, such as “Where is my sensitive data?” “Who is using it?” and “How can we effectively reduce the risks to that information?” Companies understand that good data makes employees’ jobs easier. And employees are really crafty at procuring data to help with their day jobs, even if it’s against the rules. If salespeople can get the entire customer database to help meet their quotas, or quality assurance personnel think they need production data to test web applications, they usually find ways to get it. The same goes for decentralized organizations where regional offices need to be self-sufficient, or companies need to share data with partners. The mental shift we see in enterprise environments is to stop fight these internal user requirements, but find a way to satisfy this demand safely. In some cases this means automated production of test data on a regular schedule, or self-service interfaces to produce masked content on demand. These platforms are effectively implementing a data security strategy for fast and efficient production of test data. Compliance: Compliance is the second major reason cited by customers for why they buy masking products. Unlike most of today’s emerging security technologies, it’s not just the Payment Card Industry’s Data Security Standard (PCI-DSS) driving sales – many different regulatory controls, across various industry verticals, are driving broad interest in masking. Early customers came specifically from finance, but adoption is well distributed across different segments, including particularly retail, telecomm, health care, energy, education, and government. The diversity of customer requirements makes it difficult to pinpoint any one regulatory concern that stands out from the rest. During discussions we hear about all the usual suspects – including PCI, NERC, GLBA, FERPA, HIPAA, and in some cases multiple requirements at the same time. These days we hear about masking being deployed as a more generic control – customers cite protection of Personally Identifiable Information (PII), health records, and general customer records, among other concerns; but we no longer see every customer focused on one specific regulation or requirement. Now masking is perceived as addressing a general need to avoid unwanted data access, or to reduce exposure as part of an overall compliance posture. For compliance masking is used to protect data with minimal modification to systems or processes which use the (now masked) data. Masking provides consistent coverage across files and databases with very little adjustment. Many customers layered masking and encryption in combination; using encryption to secure data at rest and masking to secure data in use. Customers find masking better at maintaining relationships within databases; they also appreciate that it can be applied dynamically and causes fewer application side effects. In some cases encryption is deployed as part of the infrastructure, while others employ encryption as part of the data masking process – particularly to satisfy regulations that prescribe encryption. But the key difference is that masking offers full control over the data lifecycle from discovery to archival, whereas encryption is used in a more focused manner, often at multiple different points, to address specific risks. Masking platform manage the compliance controls, including which columns of data are to be protected, how they are protected, and where the data resides. Production Database Protection: The first two use cases drive the vast majority of market demand for masking. While replacement of sensitive data – specifically through ETL style deployments – is by far the dominant model, it is not the only way to protect data in a database. At some firms protection of the production database is the primary goal for masking, with test data secondary. Masking can do both, which makes it attractive in these scenarios. Production data generally cannot be fully removed, so this model redirects requests to masked data where possible. This use case centers around protecting information with finer control over user access and dynamic determination whether or not to provide access – something roles and credentials are not designed to support. Dynamic masking effectively redirects suspect queries to a masked view of the real data, along with reverse proxy servers, in a handful of cases. These customers appreciate the dual benefits of dynamically detecting misuse while also monitoring database usage; they find it useful to have a log of which view of information has been presented to which users, and when. It is worth mentioning a few use cases I

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Friday Summary: June 15, 2012

Ah, summer. That time of year where our brains naturally start checking out, even if it’s inconvenient. You have probably noticed a bit of a slowdown on the blog as we succumb to the sweet call of adventure. And by ‘adventure’ I mean the delicate balance of being way freaking behind while trying to squeeze in family vacations and a few conferences. Since my kids are too young for school I can’t really use them as the excuse for taking time off. No, in my case it is the temperatures over 100F that started a month or so ago and won’t subside until sometime close to Halloween. Phoenix is not fun in the summer if you get my drift. Today, for example, when I do my short run after my hour on the bike trainer, the temp will be somewhere around 104F. So I was super excited to spend last week in my home town of Boulder, Colorado. I grew up in New Jersey, but moved to Boulder when I was 18, spent the next 16 years there, and consider Boulder the place I really grew up. Some places just fit a person, and Boulder appealed to me on more levels that I can explain. The culture, physical environment, and social scene all aligned with that perfect cosmic center of the Universe all the new-age freaks claim is somewhere behind Pasta Jay’s. This was the first time I had been back for any length of time in about 5 years, and it was was my first time back since becoming a parent. It was sort of funny – when I lived there I didn’t think there was much for kids to do until they were old enough to climb, hike, ski, and ride. I was all worried my kids would be bored out of their gourds. Sure, I know where all 20+ bars near the Pearl St. Mall are located, but I had to email friends to find a single playground. But man, they are all over the place! And the best part? A lot are located really close to all those bars… which were coincidentally a reasonable bike ride from the house we rented. Yep, total coincidence. I mean, it isn’t like we’d plan that sort of thing. On the downside, instead of escaping from 100+ in Phoenix to Boulder’s typical 60-80F this time of year, we landed in a heat wave. As in 90F+. The technical term for that is “extreme suckage”. They always say you can’t go home, and to some extent that’s true. The life I had in Boulder is long dead. Friends have moved on, the ones who stayed got old (like me), the bars of our youth are now – if they exist at all – the bars of someone else’s youth, and if I tried to spend my leisure time doing everything I did back then I would soon be hunting for a good divorce lawyer in between those mountain rescues. In some ways it is good that I left Boulder, even if I miss it every day. I was instantly pulled out of my single/childless life and forced to drop things – like 5 martial arts classes a week, on top of dozens of mountain rescues, and ski patrol every other weekend, and all the other ways I passed my time. They were instantly severed instead of being drawn out in a long, painful process of separation and personal realizations that life changed and I need to back off. For me, life changed instantly instead of slowly. I know this because it is 100+ fracking degrees at 9am where I live, which is an excellent reminder. I have seen how most of my other friends with kids struggled to balance their lives through this transition, and ripping off the Band-Aid isn’t a bad way to do it. On the other hand, Boulder is still Boulder. Some of the buildings change, but I felt just as at home there last week as I did 6 years ago when I left. The 15 minute rain still comes in every day between 4 and 4:30, the convenience store in Jamestown is still a perfect place to stop for some coffee while riding a (rented) road bike in the hills, and the annoying-ass Rainbow Family kids – who you know have loaded parents – still camp out on the Pearl St. Mall begging for cash. You can go home. It’s just that someone else lives there now – even if you never left. With that, daycare just called and I need to go pick up a little kid with a fever and end my work day. On to the Summary: Webcasts, Podcasts, Outside Writing, and Conferences We have been on vacation – nothing to see here. Favorite Securosis Posts Adrian Lane: Market Share Nonsense. Mike Rothman: Malware Analysis Quant [Final Paper]. Check out the final paper for the epic Malware Analysis Quant research. And then play a drinking game for every step in the process you don’t do. Make sure you don’t drive after that. Rich: What Adrian said. I need to write a follow-up on some of the BS vendors have tried to pull on me over the years. Like paying cash under the table for references. I tried my best, but I know at least once I was fooled… and it probably happened more than that. Other Securosis Posts Evolving Endpoint Malware Detection: Providing Context. New Paper: Defending Data on iOS. Incite 6/13/2012: Tweeting Idiocy. Understanding and Selecting Data Masking: Management and Advanced Features. Upcoming: Tokenization Webcast This Week. Evolving Endpoint Malware Detection: Behavioral Indicators. Favorite Outside Posts Adrian Lane: Mistakes Were Made: Incident Response. An informative rant on incident response and preparedness. Mike Rothman: Pre to postmortem: the inside story of the death of Palm and webOS. As a student of business, I love stories that dig into how anything can go from the top to the bottom within a few short years.

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