Controlling cooperative problem solving in industrial multi-agent systems using joint intentions
Artificial Intelligence
On the design and quantification of privacy preserving data mining algorithms
PODS '01 Proceedings of the twentieth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
From logic programming towards multi-agent systems
Annals of Mathematics and Artificial Intelligence
Software Engineering for Large-Scale Multi-agent Systems SELMAS'04
Proceedings of the 26th International Conference on Software Engineering
KES'05 Proceedings of the 9th international conference on Knowledge-Based Intelligent Information and Engineering Systems - Volume Part I
Information theory and the security of binary data perturbation
INDOCRYPT'04 Proceedings of the 5th international conference on Cryptology in India
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As technology grows, so do the demands on information systems processing. Modern information systems need to handle diverse tasks that tend to be increasingly complex. Automation of processing by employing artificial intelligence techniques is an essential environment for ensuring the smooth running of information systems. In this paper, we investigate the application of multi-agent information systems for online medical surveys. In particular, our contribution is to extend our previous research results to a multi-agent technology for data perturbation as a means of camouflaging database query results. The decision on when to camouflage data is made by a system of collaborating intelligent agents. When a user query request is entered into the system, processing rules are applied to determine whether the result of the query needs to be camouflaged.