This paper investigates infinite horizon repeated security games with one defender and multiple attacker types.The incomplete information brings uncertainty of attackers’behaviour for the defender.Under the uncertain...This paper investigates infinite horizon repeated security games with one defender and multiple attacker types.The incomplete information brings uncertainty of attackers’behaviour for the defender.Under the uncertainty of attackers’behaviours,we take the worst-case analysis to minimise the defender’s regret w.r.t.each attacker type.We wish to keep the regret especially small w.r.t.one attacker type,at the cost of modest additional overhead compared to others.The tradeoff among the objectives requires us to build a Multi-Objective Repeated SecurityGame(MORSG)model.To parameterise the regret Pareto frontier,we combine the different weight vectors with different objectives and build a linear programming approach.By running the Q-iteration procedure on linear programming for each weight vector,the optimal regret Pareto frontier can be computed.We also propose an approximate approach to approximate it.The approximation analysis proves the effectiveness of the approximation approach.展开更多
基金The paper is supported by theNationalNatural Science Foundation of China[grant nos 61572095,61877007].
文摘This paper investigates infinite horizon repeated security games with one defender and multiple attacker types.The incomplete information brings uncertainty of attackers’behaviour for the defender.Under the uncertainty of attackers’behaviours,we take the worst-case analysis to minimise the defender’s regret w.r.t.each attacker type.We wish to keep the regret especially small w.r.t.one attacker type,at the cost of modest additional overhead compared to others.The tradeoff among the objectives requires us to build a Multi-Objective Repeated SecurityGame(MORSG)model.To parameterise the regret Pareto frontier,we combine the different weight vectors with different objectives and build a linear programming approach.By running the Q-iteration procedure on linear programming for each weight vector,the optimal regret Pareto frontier can be computed.We also propose an approximate approach to approximate it.The approximation analysis proves the effectiveness of the approximation approach.
