Belief change operations under confidentiality requirements in multiagent systems

Multiagent systems are populated with autonomous computing entities called agents which pro-actively pursue their goals. The design of such systems is an active field within artificial intelligence research with one objective being flexible and adaptive agents in dynamic and inaccessible environments. An agent's decision-making and finally its success in achieving its goals crucially depends on the agent's information about its environment and the sharing of information with other agents in the multiagent system. For this and other reasons, an agent's information is a valuable asset and thus the agent is often interested in the confidentiality of parts of this information. From research in computer security it is well-known that confidentiality is not only achieved by the agent's control of access to its data, but by its control of the flow of information when processing the data during the interaction with other agents. This thesis investigates how to specify and enforce the confidentiality interests of an agent D while it reacts to iterated query, revision and update requests from another agent A for the purpose of information sharing. First, we will enable the agent D to specify in a dedicated confidentiality policy that parts of its previous or current belief about its environment should be hidden from the other requesting agent A. To formalize the requirement of hiding belief, we will in particular postulate agent A's capabilities for reasoning about D's belief and about D's processing of information to form its belief. Then, we will relate the requirements imposed by a confidentiality policy to others in the research of information flow control and inference control in computer security. Second, we will enable the agent D to enforce its confidentiality aims as expressed by its policy by refusing requests from A at a potential violation of its policy. A crucial part of the enforcement is D's simulation of A's postulated reasoning about D's belief and the change of this belief. In this thesis, we consider two particular operators of belief change: an update operator for a simple logic-oriented database model and a revision operator for D's assertions about its environment that yield the agent's belief after its nonmonotonic reasoning. To prove the effectiveness of D's means of enforcement, we study necessary properties of D's simulation of A and then based on these properties show that D's enforcement is effective according to the formal requirements of its policy

Providing Information by Resource- Constrained Data Analysis

The Collaborative Research Center SFB 876 (Providing Information by Resource-Constrained Data Analysis) brings together the research fields of data analysis (Data Mining, Knowledge Discovery in Data Bases, Machine Learning, Statistics) and embedded systems and enhances their methods such that information from distributed, dynamic masses of data becomes available anytime and anywhere. The research center approaches these problems with new algorithms respecting the resource constraints in the different scenarios. This Technical Report presents the work of the members of the integrated graduate school

Constructing Inference-Proof Belief Mediators

Part 4: Authentication and Information IntegrationInternational audienceAn information owner might interact with cooperation partners regarding its belief, which is derived from a collection of heterogeneous data sources and can be changed according to perceptions of the partners’ actions. While interacting, the information owner willingly shares some information with a cooperation partner but also might want to keep selected pieces of information confidential. This requirement should even be satisfied if the partner as an intelligent and only semi-honest attacker attempts to infer hidden information from accessible data, also employing background knowledge. For this problem of inference control, we outline and discuss a solution by means of a sophisticated mediator agent. Based on forming an integrated belief from the underlying data sources, the design adapts and combines known approaches to language-based information flow control and controlled interaction execution for logic-based information systems

Preserving Confidentiality in Multiagent Systems - An Internship Project within the DAAD RISE Program

RISE (Research Internships in Science and Engineering) is a summer internship program for undergraduate students from the United States, Canada and the UK organized by the DAAD (Deutscher Akademischer Austausch Dienst). Within the project A5 in the Collaborative Research Center SFB 876, we have planned and conducted an internship project in the RISE program that should support our research. Daniel Dilger was the intern and has been supervised by the PhD students Patrick Krümpelmann and Cornelia Tadros. The aim was to model an application scenario for our prototype implementation of a confidentiality preserving multiagent system and to run experiments with that prototype