论文标题
流量网络容易受到虚假信息攻击的影响
Traffic networks are vulnerable to disinformation attacks
论文作者
论文摘要
由于对社会的威胁日益增加,虚假信息继续引起人们的关注。然而,迄今为止,从未研究过基于虚假信息的关键基础架构的攻击。在这里,我们考虑交通网络,并专注于操纵驾驶员制造拥塞的决定的虚假信息。我们研究对手在选择目标以最大化破坏的街道时面临的优化问题。我们证明,找到最佳解决方案在计算上是棘手的,这意味着对手别无选择,只能解决次优启发式法。我们分析了这样的启发式方法,并比较了目标分布在芝加哥市与集中在其商业区的案例。令人惊讶的是,后者会导致更深远的破坏,其影响感觉距离最接近目标2公里。我们的发现表明,关键基础架构中的漏洞不仅可能来自硬件和软件,而且还来自行为操纵。
Disinformation continues to attract attention due to its increasing threat to society. Nevertheless, a disinformation-based attack on critical infrastructure has never been studied to date. Here, we consider traffic networks and focus on fake information that manipulates drivers' decisions to create congestion. We study the optimization problem faced by the adversary when choosing which streets to target to maximize disruption. We prove that finding an optimal solution is computationally intractable, implying that the adversary has no choice but to settle for suboptimal heuristics. We analyze one such heuristic, and compare the cases when targets are spread across the city of Chicago vs. concentrated in its business district. Surprisingly, the latter results in more far-reaching disruption, with its impact felt as far as 2 kilometers from the closest target. Our findings demonstrate that vulnerabilities in critical infrastructure may arise not only from hardware and software, but also from behavioral manipulation.