正网络中基于Katz中心性的安全分配
Katz Centrality-Based Security Allocation in Positive Networks
AI总结：
本文针对正权有向图表示的网络化控制系统的隐蔽虚假数据注入攻击，提出基于Katz中心性的安全分配方法，通过半定规划分析最坏性能损失，给出与网络规模无关的优化及启发式监测节点选择方案，经仿真验证有效。
AI中文摘要：
本文研究由正权有向图表示的网络化控制系统在隐蔽虚假数据注入攻击下的安全分配挑战。这类系统由相互连接的子系统组成，在底层有向图中称为节点，攻击者旨在通过隐蔽攻击特定节点最大化网络性能损失；而防御者监测若干节点，对攻击者的行动施加隐蔽性约束，从而最小化网络性能损失。我们分析此类隐蔽攻击下的最坏情况网络性能损失，并做出以下贡献：(i) 证明最坏情况网络性能损失可由一个易处理的半定规划（SDP）问题给出上界；(ii) 在充分条件下建立该SDP问题与底层有向图Katz中心性测度的关系，得到一个与网络规模无关的优化问题；(iii) 提出一种基于底层有向图Katz中心性测度的启发式搜索方法，用于在不求解优化问题的情况下，针对所有可容许攻击场景选择次优监测节点。这些结果为保护大规模网络化控制系统抵御隐蔽虚假数据注入攻击提供了实用见解。所得结果通过对不同规模的Erdos-Renyi随机图进行广泛仿真得到验证。
英文摘要：
This paper deals with security allocation challenges for networked control systems represented by positive-weighted digraphs under stealthy false data injection attacks. These systems consist of interconnected subsystems, referred to as nodes in the underlying digraph, where an adversary aims to maximize network performance loss by stealthily attacking specific nodes. Meanwhile, a defender monitors several nodes to impose stealthiness constraints on the adversary's actions, thereby minimizing the network performance loss. We analyze the worst-case network performance loss of these stealthy attacks and make the following contributions: we (i) show that the worst-case network performance loss is upper-bounded by a tractable semi-definite programming (SDP) problem; (ii) establish the relationship between the SDP problem and the Katz centrality measure of the underlying digraph under a sufficient condition, resulting in a network-size-independent optimization problem; and (iii) provide a heuristic search based on the Katz centrality measure of the underlying digraph for selecting sub-optimal monitor nodes against all admissible attack scenarios without solving optimization problems. These results offer practical insights for safeguarding large-scale networked control systems against stealthy false data injection attacks. The obtained results are validated via extensive simulations on Erdos-Renyi random graphs with different network sizes.
