Dynamic Information Disclosure for Deception

Muhammed O. Sayin, Tamer Basar

Research output: Chapter in Book/Report/Conference proceedingConference contribution


We analyze in this paper how a deceptive information provider can shape the shared information in order to control a decision maker's decisions. Data-driven engineering applications, e.g., machine learning and artificial intelligence, build on information. However, this implies that information (and correspondingly information providers) can have influential impact on the decisions made. Notably, the information providers can be deceptive such that they can benefit, while the decision makers suffer, from the strategically shaped information. We formulate (and provide an algorithm to compute) the optimal deceptive shaping policies in the multi-stage disclosure of, general, multi-dimensional Gauss-Markov information. To be able to deceive the decision maker, the information provider should anticipate the decision maker's reaction while facing a trade-off between deceiving at the current stage and the ability to deceive in the future stages. We show that optimal shaping policies are linear within the general class of Borel-measurable policies even though the information provider and the decision maker could be seeking to minimize quite different quadratic cost functions.

Original languageEnglish (US)
Title of host publication2018 IEEE Conference on Decision and Control, CDC 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
Number of pages8
ISBN (Electronic)9781538613955
StatePublished - Jul 2 2018
Event57th IEEE Conference on Decision and Control, CDC 2018 - Miami, United States
Duration: Dec 17 2018Dec 19 2018

Publication series

NameProceedings of the IEEE Conference on Decision and Control
ISSN (Print)0743-1546
ISSN (Electronic)2576-2370


Conference57th IEEE Conference on Decision and Control, CDC 2018
Country/TerritoryUnited States

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Modeling and Simulation
  • Control and Optimization


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