Dynamic inference control

Abstract

An inference problem exists in a multilevel database if knowledge of some objects in the database allows information with a higher security level to be inferred. Many such inferences may be prevented prior to any query processing by raising the security level of some of the objects, however this inevitably impedes information access, as a user with low authorization who queries just one of the objects with raised security must seek clearance even when not in danger of making the inference. More flexible access control is possible when inferences are prevented during query processing, however this practice can result in slow query response times. We demonstrate that access control can be made sufficiently dynamic to ensure easy access to the information users are entitled to, while retaining fast query processing. Our inference control schemes provide collusion resistance and have a query processing time that depends only on the length of the inference channels (not on the length of user query histories). In addition, our schemes provide a property we call crowd control that goes beyond collusion resistance to ensure that if a large number of users have queried all but one of the objects in an inference channel, then no one will be able to query the remaining object regardless of the level of collusion resistance provided by the scheme.

Collusion Resistant Inference Control for Cadastral Databases

“…The closest approach to ours is the one presented by Staddon [20]. In her paper, Staddon presented a dynamic inference control scheme that does not depend on user query history.…”

Database Security: What Students Need to Know

“…Developing technological solutions to detecting database inference is complex. Much of the work done in this area involves revoking access to specific database objects based on a user's past querying history (Staddon, 2003). The problem with inference detection, especially when done at query processing time, is that it results in a significant delay between the time the query is executed and the results are presented.…”

Private inference control

“…Tools and techniques for ensuring inference control without user privacy can be found in [43,32,47].…”

“…It is straightforward to modify our protocols to protect against collusion -we simply permit each user to access less of each channel. The same technique is used in [47] to ensure collusion-resistant inference control without privacy, however it is easily adopted in our setting as it only depends on server knowledge of the number of queries a user has made not the content of the queries. Adjusting the definition is similarly straightforward, one would instead consider malicious users, U * 1 , .…”