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    Chapter and Conference Paper

    MAVIPER: Learning Decision Tree Policies for Interpretable Multi-agent Reinforcement Learning

    Many recent breakthroughs in multi-agent reinforcement learning (MARL) require the use of deep neural networks, which are challenging for human experts to interpret and understand. On the other hand, existing ...

    Stephanie Milani, Zhicheng Zhang in Machine Learning and Knowledge Discovery i… (2023)

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    Chapter and Conference Paper

    Game Theory on Attack Graph for Cyber Deception

    Game Theory provides a set of tools and a framework suitable to study security problems. In this paper, a class of games is developed to study cyber deception and the interactions between the network defender ...

    Ahmed H. Anwar, Charles Kamhoua in Decision and Game Theory for Security (2020)

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    Chapter and Conference Paper

    Blocking Adversarial Influence in Social Networks

    While social networks are widely used as a media for information diffusion, attackers can also strategically employ analytical tools, such as influence maximization, to maximize the spread of adversarial conte...

    Feiran Jia, Kai Zhou, Charles Kamhoua in Decision and Game Theory for Security (2020)

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    Chapter and Conference Paper

    A Game Theoretic Framework for Software Diversity for Network Security

    Diversity plays a significant role in network security, and we propose a formal model to investigate and optimize the advantages of software diversity in network security. However, diversity is also costly, an...

    Ahmed H. Anwar, Nandi O. Leslie, Charles Kamhoua in Decision and Game Theory for Security (2020)

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    Chapter and Conference Paper

    Learning and Planning in the Feature Deception Problem

    Today’s high-stakes adversarial interactions feature attackers who constantly breach the ever-improving security measures. Deception mitigates the defender’s loss by misleading the attacker to make suboptimal ...

    Zheyuan Ryan Shi, Ariel D. Procaccia in Decision and Game Theory for Security (2020)

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    Chapter and Conference Paper

    Harnessing the Power of Deception in Attack Graph-Based Security Games

    We study the use of deception in attack graph-based Stackelberg security games. In our setting, in addition to allocating defensive resources to protect important targets from attackers, the defender can strat...

    Stephanie Milani, Weiran Shen, Kevin S. Chan in Decision and Game Theory for Security (2020)

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    Chapter and Conference Paper

    Partially Observable Stochastic Games for Cyber Deception Against Network Epidemic

    A Decentralized Denial of Service is an attack done by an agent capable to control the spread of a malware. This is a combination of epidemiological and conflictual aspects between several decision makers. The...

    Olivier Tsemogne, Yezekael Hayel, Charles Kamhoua in Decision and Game Theory for Security (2020)

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    Chapter and Conference Paper

    Hardware Sandboxing: A Novel Defense Paradigm Against Hardware Trojans in Systems on Chip

    A novel approach for mitigation of hardware Trojan in Systems on Chip (SoC) is presented. With the assumption that Trojans can cause harm only when they are activated, the goal is to avoid cumbersome and somet...

    Christophe Bobda, Joshua Mead, Taylor J. L. Whitaker in Applied Reconfigurable Computing (2017)