Andrea Abrardo, Mauro Barni, Kassem Kallas, Benedetta Tondi

Information Fusion in Distributed Sensor Networks with Byzantines (eBook, PDF)

• Format: PDF

Produktbeschreibung

This book reviews the most powerful attack strategies and potential defense mechanisms, always approaching the interplay between the Fusion Center and the Byzantines from a game-theoretic perspective. For each of the settings considered, the equilibria of the game and the corresponding payoffs are derived, shedding new light on the achievable performance level and the impact that the presence of the Byzantines has on the accuracy of decisions made by the Fusion Center.

Accordingly, the book offers a simple yet effective introduction to the emerging field of adversarial information fusion, providing a wealth of intuitive take-home lessons for practitioners interested in applying the most basic notions to the design of practical systems, while at the same time introducing researchers and other readers to the mathematical details behind the theory.

Produktdetails

• Verlag: Springer Singapore
• Erscheinungstermin: 14. Juli 2020
• Englisch
• ISBN-13: 9789813290013
• Artikelnr.: 59828139

Inhaltsangabe

Introduction.- Preliminaries.- Security attacks and defenses in distributed sensor networks.- A Heuristic defense: A soft isolation algorithm for adversarial decision fusion.- Optimum decision fusion in the presence of Byzantines.- Nearly optimum decision fusion via message passing.- Decision fusion of hidden-Markov observations with synchronized attacks.- Decision fusion with unbalanced priors.- Decision fusion game with incomplete knowledge in a Bayesian setup.- Conclusions.

---

Introduction.- Preliminaries.- Security attacks and defenses in distributed sensor networks.- A Heuristic defense: A soft isolation algorithm for adversarial decision fusion.- Optimum decision fusion in the presence of Byzantines.- Nearly optimum decision fusion via message passing.- Decision fusion of hidden-Markov observations with synchronized attacks.- Decision fusion with unbalanced priors.- Decision fusion game with incomplete knowledge in a Bayesian setup.- Conclusions.