Titlebook: Decision and Game Theory for Security; 9th International Co Linda Bushnell,Radha Poovendran,Tamer Ba?ar Conference proceedings 2018 Springe

forbid

Suppository

https://doi.org/10.1007/978-90-313-9129-5irable—can be exploited by adversaries to contaminate training and evade classification. In this paper, we investigate the feasibility of applying a specific class of machine learning algorithms, namely, reinforcement learning (RL) algorithms, for autonomous cyber defence in software-defined network

reaching

arthrodesis

Sedimentary Structures and Beddingendation and adaptive medical treatment, among others. We provide a general attack framework based on convex optimization and show that by slightly manipulating rewards in the data, an attacker can force the bandit algorithm to pull a target arm for a target contextual vector. The target arm and tar

violate

infantile

Petrographic Classification and Glossary answer these concerns is by enabling end users to choose which aspects of their private information can be collected. Based on principles suggested by Feldman and Gonen (2018), we introduce a new online advertising market model which uses information brokers to give users such control. Unlike Feldm

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有權(quán)

Mast-Cell

安心地散步

Sedimentary Structures and Beddingplayers with no intent to intentionally harm the network. Nevertheless, the need to believe that players will behave consistently exposes the network to vulnerabilities associated with cyber-physical attacks. This paper investigates the effects of cyber-physical attacks on the outcome of distributed