Browsing by Author "Sundaram, Shreyas"

Now showing 1 - 2 of 2
  • Thumbnail Image
    Item
    Morshed: Guiding Behavioral Decision-Makers towards Better Security Investment in Interdependent Systems
    (Association for Computing Machinery, 2021) Abdallah, Mustafa; Woods, Daniel; Naghizadeh, Parinaz; Khalil, Issa; Cason, Timothy; Sundaram, Shreyas; Bagchi, Saurabh; Engineering Technology, Purdue School of Engineering and Technology
    We model the behavioral biases of human decision-making in securing interdependent systems and show that such behavioral decision-making leads to a suboptimal pattern of resource allocation compared to non-behavioral (rational) decision-making. We provide empirical evidence for the existence of such behavioral bias model through a controlled subject study with 145 participants. We then propose three learning techniques for enhancing decision-making in multi-round setups. We illustrate the benefits of our decision-making model through multiple interdependent real-world systems and quantify the level of gain compared to the case in which the defenders are behavioral. We also show the benefit of our learning techniques against different attack models. We identify the effects of different system parameters (e.g., the defenders' security budget availability and distribution, the degree of interdependency among defenders, and collaborative defense strategies) on the degree of suboptimality of security outcomes due to behavioral decision-making.
  • Thumbnail Image
    Item
    The Effect of Behavioral Probability Weighting in a Simultaneous Multi-Target Attacker-Defender Game
    (IEE, 2021) Abdallah, Mustafa; Cason, Timothy; Bagchi, Saurabh; Sundaram, Shreyas; Electrical and Computer Engineering, Purdue School of Engineering and Technology
    We consider a security game in a setting consisting of two players (an attacker and a defender), each with a given budget to allocate towards attack and defense, respectively, of a set of nodes. Each node has a certain value to the attacker and the defender, along with a probability of being successfully compromised, which is a function of the investments in that node by both players. For such games, we characterize the optimal investment strategies by the players at the (unique) Nash Equilibrium. We then investigate the impacts of behavioral probability weighting on the investment strategies; such probability weighting, where humans overweight low probabilities and underweight high probabilities, has been identified by behavioral economists to be a common feature of human decision-making. We show via numerical experiments that behavioral decision-making by the defender causes the Nash Equilibrium investments in each node to change (where the defender overinvests in the high-value nodes and underinvests in the low-value nodes).