Secure Route Planning Using Dynamic Games with Stopping States

Secure Route Planning Using Dynamic Games with Stopping States
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使用具有停止状态的动态博弈来保护路线规划

DOI:
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发表时间:
2020
期刊:
IEEE/RJS International Conference on Intelligent RObots and Systems
影响因子:
--
通讯作者:
S. Bopardikar
S. Bopardikar
中科院分区:
--
文献类型:
--
作者:
Sandeep Banik;S. Bopardikar

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本文研究了一个路线图上的运动规划问题,其中车辆的目标是从起点行驶到目的地,攻击者可以在路线图的任何一个边缘上对车辆发动网络攻击。车辆(防御者)有能力打开/关闭一个对策,可以检测和永久禁用攻击,如果它同时发生。我们首先将穿越边缘的问题建模为具有停止状态的零和动态博弈,称为攻击者和防御者之间的边缘博弈。我们刻画了纳什均衡的边缘游戏,并提供了封闭形式的表达的情况下,每个球员的两个行动。我们进一步提供了一个分析和近似表达的边缘游戏的价值和特征条件下,它的增长与边缘的长度呈次线性。我们研究了纳什均衡对(i)使用对策的成本,(ii)运动成本和(iii)禁用攻击的好处的敏感性。边对策的解决方案是用来制定和解决安全的路线规划问题。我们设计了一个有效的启发式转换问题的最短路径问题,使用的边缘成本作为相应的边缘游戏的解决方案。我们通过几个有见地的模拟来说明我们的发现。
This paper studies a motion planning problem over a roadmap in which a vehicle aims to travel from a start to a destination in presence of an attacker who can launch a cyber-attack on the vehicle over any one edge of the roadmap. The vehicle (defender) has the capability to switch on/off a countermeasure that can detect and permanently disable the attack if it occurs concurrently. We first model the problem of traversing an edge as a zero-sum dynamic game with a stopping state, termed as an edge-game played between an attacker and defender. We characterize Nash equilibria of the edge-game and provide closed form expressions for the case of two actions per player. We further provide an analytic and approximate expression on the value of an edge-game and characterize conditions under which it grows sub-linearly with the length of the edge. We study the sensitivity of Nash equilibrium to the (i) cost of using the countermeasure, (ii) cost of motion and (iii) benefit of disabling the attack. The solution of the edge-game is used to formulate and solve the secure route planning problem. We design an efficient heuristic by converting the problem to a shortest path problem using the edge cost as the solution of corresponding edge-games. We illustrate our findings through several insightful simulations.
扭曲网络物理系统中对手的观点
DOI: --
发表时间: 2018
期刊: IEEE Control and Decision Conference (CDC
影响因子: --
作者:
Agarwal, G.;Karmoose, M.;Fragouli, C.;Diggavi, S.;Tabuada, P.
通讯作者: Tabuada, P.