CONTROLLING THE USE OF SENSITIVE INFORMATION
by Ed Colet

Data mining patterns can provide an Organization with a substantial competitive advantage. Because the information can provide a competitive edge, it is also information that is usually sensitive and/or proprietary. Herein lies a dilemma. While it is important to disseminate information as widely as possible to the right people to achieve maximum benefits, it is also important to ensure that information is not misused in such a way that it compromises competitive advantages. In this column, I summarize some new technologies designed to control the use of sensitive material.

Gartner Group analyst, Alan Weintraub, has referred to the controlled use of sensitive material as "content assurance" technologies. These technologies incorporate elements of Digital Rights Management (DRM), security controls, and content management technologies. While DRM addresses copyright protection by governing who can access information, DRM does not address how the information can be used after it's accessed. What is needed is a way to provide users with access to proprietary information, and if necessary, prevent users from saving it, printing it or forwarding it to others. Start-ups Alchemedia, Vyou and Authentica are some companies that offer products that cover the way information content is used.

In the case of Authentica, their latest product, NetRecall works by requiring users to download a plug-in that communicates with server software. The plug-in and software checks that the requested content complies with rules defined by the content provider/owner pertaining to the use of such content. Rules may allow the user one-time viewing rights, or rights that expire after a few hours. The decryption keys that are used are destroyed when the user's access expires, preventing people from forwarding encrypted content and keys to unknown parties.

The technology can also distinguish among different users accessing the same URL. For example, the same URL can provide different images or content depending on who the user is. For example, a retail price list can be shown to a consumer, but a wholesale price list shown to a business partner -- who can then be permitted to save the information to disk, while the consumer has only viewing rights to their information.

Content assurance technologies control and protect the way information is used throughout its life cycle. As such, they may be suitable for controlling the use of potentially sensitive data mining information given two recent trends regarding the use of data mining.

One trend is that data mining is moving away from being a secretive operation conducted behind closed doors as the exclusive domain of analysts. In order for an organization to achieve the maximum advantage from its data analysis, a variety of end-user decision makers need to have access to results, or to be able to conduct their own analyses. Such end users may be high-ranking executives, middle-management day-to-day decision makers, other analysts, and even people outside the organization -- partners and customers. Controlling who gets to see what and what they can do with information is now possible with content assurance technologies.

Another trend is that sharing information over the Web is becoming a predominant means of information and knowledge exchange, especially in a large and geographically distributed organization. Once information is put on the Web, there are usually concerns about who can access it, and once accessed, what users can do with it. Current technologies now address this latter aspect.

To conclude, as content assurance technologies and products mature, it should become easier to balance the apparently conflicting demands of disseminating information widely, while simultaneously controlling how such information is used.

Ed Colet is the Acting Director of Research at Virtual Gold Inc., responsible for developing analytical methods for data mining and for investigating human factors and usability issues of business intelligence systems. At present, he is in the final stage of completing a doctoral dissertation in the Cognition and Perception program at New York University's Department of Psychology. Ed has also worked for IBM Research at the T.J. Watson Research Center. At IBM, Ed was a member of the group that developed Advanced Scout, the data mining application for NBA teams. His research interests focus on statistical methods and human factors.

For more information, see www.virtualgold.com.