Insurers Mining Consumer Data

I saw this article in the Arizona Republic Monday about how the insurance companies are able to save money by gathering health care records electronically, make more accurate analyses of patients (also saving money) and be able to adjust premiums (i.e., make more money) based upon your poor health or various other things. You know, like ‘pre-existing’ conditions, or whatever concept they choose to make up. Does anyone think that they will be offered an option? The choice of not providing these electronically? Not a chance. This will be the insurer’s policy, and you can choose to not have insurance, or turn over your records. Does this violate HIPPA? To me it does, but since you are given the illusion of choice, their legal team will surely protect them with your ‘agreement’ to turn over these electronic documents. And why not, with all the money they saved through data analysis, they have plenty of money for their legal expenses. Does anyone think that the patient will be allowed to see this data, verify accuracy, or have it deleted after the analysis? Not a chance. Your medical data will most likely have a “half life” longer than your life span. That stuff is not going anywhere, unless it is leaked of course. But then you will be provided a nice letter in the mail about how your data may or may not have been stolen and how you can have free credit monitoring services if you sign this paper saying you won’t sue. It’s like watching a car wreck in slow motion. Or a Dilbert comic strip. Let me take another angle on the data accuracy side of this proposition. When I first graduated college, I walked down the street to open a checking account with one of the big household names in banking. For the next 12 months I received a statement each month, and not one of those banking statements was 100% correct. Every single statement had an error or an omission! My trials and angst with a certain cell phone provider are also well documented. Once again, charges for things I did not order, rates that were not part of the plan, leaked personal data, and many, many other things during the first year. I had one credit card for a period of 12 years, and like clockwork, a late fee was charged every 6-9 months despite postmarks and deposit dates which conclusively showed I was on time. I finally got tired of having to call in to dispute it, and just plain fed up with what I assumed was a dastardly business practice to generate additional revenue from people too lazy to look at their bills or pick up the phone and complain. I had a utility company charge me $900, for a single month, on a vacant home I had moved out of three months prior. One out of two grocery store receipts I receive is incorrect in that one or more prices are wrong or one of the items scans as something that it is not. Other companies who saved my credit card information, without my permission, tried to bill me for things I did not want nor purchase. Electronic records typically have errors, they are not always caught, and there may or may not be a method to address the problem. The studies I have seen on measuring the accuracy of data contained within these types of databases is appalling. If memory serves, over 20% of the data contained in these databases is inaccurate due to entry or transcription errors, is incorrect logic errors in transformational algorithms, or has become inaccurate with the passage of time. That later item means each subsequent year, the accuracy degrades further. There is no evidence that Ingenix will have any higher accuracy rates, or will not be subject to the same issues as other providers, such as Choicepoint. They say computers don’t lie, but they are flush with bogus data. Now think about how inaccurate information is going to affect you, the medical advice you receive, and the cost of paying for treatment! There is a strong possibility you could be turned down for insurance, or pay twice as much for insurance, simply because of data errors. And most likely, the calculation itself will not be disclosed, for “Pharmacy Risk Score” or any other actuarial calculation. If this system does not have a built-in method for periodically certifying accuracy and removing old information, it is a failure from the start. I know this is a recurring theme for me, but if companies are going to use my personal information for their financial gain, I want to have some control over that information. Insurance companies will derive value from electronic data sharing because it makes their jobs easier, but the consumer will not see any value from this. Share:

Read Post

Black Hat: The Risks Of Trusting Content

I’m sitting in the Extreme Client-side exploitation talk here at Black Hat and it’s highlighting a major website design risk that takes on even more significance in mashups and other web 2.0-style content. Nate McFeters (of ZDNet fame), Rob Carter, and John Heasman are slicing through the same origin policy and other browser protections in some interesting ways. At the top of the list is the GIFAR– a combination of an image file and a Java applet. Since image files include their header information (the part that helps your system know how to render it) and JAR (java applets) include their header information at the bottom. This means that when the file is loaded, it will look like an image (because it is), but as it’s rendered at the end it will run as an applet. Thus you think you’re looking at a pretty picture, since you are, but you’re also running an application. So how does this work for an attack? If I build a GIFAR and upload it to a site that hosts photos, like Picassa, when that GIFAR loads and the application part starts running it can execute actions in the context of Picassa. That applet then gains access to any of your credentials or other behaviors that run on that site. Heck, forget photo sites, how about anything that let’s you upload your picture as part of your profile? Then you can post in a forum and anyone reading it will run that applet (I made that one up, it wasn’t part of the presentation, but I think it should work). This doesn’t just affect GIF files- all sorts of images and other content can be manipulated in this way. This highlights a cardinal risk of accepting user content- it’s like a box of chocolates; you never know what you’re gonna get. You are now serving content to your users that could abuse them, making you not only responsible, but which could directly break your security model. Things may execute in the context of your site, enabling cross site request forgery or other trust boundary violations. How do manage this? According to Nate you can always choose to build in your own domain boundaries- serve content from one domain, and keep the sensitive user account information in another. Objects can still be embedded, but they won’t run in a context that allows them to access other site credentials. Definitely a tough design issue. I also think that, in the long term, some of the browser session virtualization and ADMP concepts we’ve previously discussed here are a god mitigation. Share:

Read Post

Totally Transparent Research is the embodiment of how we work at Securosis. It’s our core operating philosophy, our research policy, and a specific process. We initially developed it to help maintain objectivity while producing licensed research, but its benefits extend to all aspects of our business.

Going beyond Open Source Research, and a far cry from the traditional syndicated research model, we think it’s the best way to produce independent, objective, quality research.

Here’s how it works:

  • Content is developed ‘live’ on the blog. Primary research is generally released in pieces, as a series of posts, so we can digest and integrate feedback, making the end results much stronger than traditional “ivory tower” research.
  • Comments are enabled for posts. All comments are kept except for spam, personal insults of a clearly inflammatory nature, and completely off-topic content that distracts from the discussion. We welcome comments critical of the work, even if somewhat insulting to the authors. Really.
  • Anyone can comment, and no registration is required. Vendors or consultants with a relevant product or offering must properly identify themselves. While their comments won’t be deleted, the writer/moderator will “call out”, identify, and possibly ridicule vendors who fail to do so.
  • Vendors considering licensing the content are welcome to provide feedback, but it must be posted in the comments - just like everyone else. There is no back channel influence on the research findings or posts.
    Analysts must reply to comments and defend the research position, or agree to modify the content.
  • At the end of the post series, the analyst compiles the posts into a paper, presentation, or other delivery vehicle. Public comments/input factors into the research, where appropriate.
  • If the research is distributed as a paper, significant commenters/contributors are acknowledged in the opening of the report. If they did not post their real names, handles used for comments are listed. Commenters do not retain any rights to the report, but their contributions will be recognized.
  • All primary research will be released under a Creative Commons license. The current license is Non-Commercial, Attribution. The analyst, at their discretion, may add a Derivative Works or Share Alike condition.
  • Securosis primary research does not discuss specific vendors or specific products/offerings, unless used to provide context, contrast or to make a point (which is very very rare).
    Although quotes from published primary research (and published primary research only) may be used in press releases, said quotes may never mention a specific vendor, even if the vendor is mentioned in the source report. Securosis must approve any quote to appear in any vendor marketing collateral.
  • Final primary research will be posted on the blog with open comments.
  • Research will be updated periodically to reflect market realities, based on the discretion of the primary analyst. Updated research will be dated and given a version number.
    For research that cannot be developed using this model, such as complex principles or models that are unsuited for a series of blog posts, the content will be chunked up and posted at or before release of the paper to solicit public feedback, and provide an open venue for comments and criticisms.
  • In rare cases Securosis may write papers outside of the primary research agenda, but only if the end result can be non-biased and valuable to the user community to supplement industry-wide efforts or advances. A “Radically Transparent Research” process will be followed in developing these papers, where absolutely all materials are public at all stages of development, including communications (email, call notes).
    Only the free primary research released on our site can be licensed. We will not accept licensing fees on research we charge users to access.
  • All licensed research will be clearly labeled with the licensees. No licensed research will be released without indicating the sources of licensing fees. Again, there will be no back channel influence. We’re open and transparent about our revenue sources.

In essence, we develop all of our research out in the open, and not only seek public comments, but keep those comments indefinitely as a record of the research creation process. If you believe we are biased or not doing our homework, you can call us out on it and it will be there in the record. Our philosophy involves cracking open the research process, and using our readers to eliminate bias and enhance the quality of the work.

On the back end, here’s how we handle this approach with licensees:

  • Licensees may propose paper topics. The topic may be accepted if it is consistent with the Securosis research agenda and goals, but only if it can be covered without bias and will be valuable to the end user community.
  • Analysts produce research according to their own research agendas, and may offer licensing under the same objectivity requirements.
  • The potential licensee will be provided an outline of our research positions and the potential research product so they can determine if it is likely to meet their objectives.
  • Once the licensee agrees, development of the primary research content begins, following the Totally Transparent Research process as outlined above. At this point, there is no money exchanged.
  • Upon completion of the paper, the licensee will receive a release candidate to determine whether the final result still meets their needs.
  • If the content does not meet their needs, the licensee is not required to pay, and the research will be released without licensing or with alternate licensees.
  • Licensees may host and reuse the content for the length of the license (typically one year). This includes placing the content behind a registration process, posting on white paper networks, or translation into other languages. The research will always be hosted at Securosis for free without registration.

Here is the language we currently place in our research project agreements:

Content will be created independently of LICENSEE with no obligations for payment. Once content is complete, LICENSEE will have a 3 day review period to determine if the content meets corporate objectives. If the content is unsuitable, LICENSEE will not be obligated for any payment and Securosis is free to distribute the whitepaper without branding or with alternate licensees, and will not complete any associated webcasts for the declining LICENSEE. Content licensing, webcasts and payment are contingent on the content being acceptable to LICENSEE. This maintains objectivity while limiting the risk to LICENSEE. Securosis maintains all rights to the content and to include Securosis branding in addition to any licensee branding.

Even this process itself is open to criticism. If you have questions or comments, you can email us or comment on the blog.