Sporadic data integrity for secure state estimation
Sporadic data integrity for secure state estimation
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DOI：
10.1109/cdc.2017.8263660
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发表时间：
2017-12
期刊：
影响因子：
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通讯作者：
Ilija Jovanov;Miroslav Pajic
中科院分区：
文献类型：
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作者：
Ilija Jovanov;Miroslav Pajic
我们在标准状态估计器上考虑基于网络的攻击问题，例如中间人攻击。为了确保在存在攻击时的优雅控制退化，现有的结果对未受损传感器的数量施加了非常严格的完整性要求。我们研究了零星数据完整性强制，如消息认证，对隐形攻击下控制性能的影响。我们证明了即使有零星的数据完整性保证，攻击者也不能在保持隐身的情况下引入无界状态估计误差。我们提出了一个设计时框架来推导安全完整性执行策略，并说明了它的使用；我们证明，即使只有20%的经过身份验证的消息，我们也可以确保在攻击下出现令人满意的状态估计错误。
We consider the problem of network-based attacks, such as Man-in-the-Middle attacks, on standard state estimators. To ensure graceful control degradation in the presence of attacks, existing results impose very strict integrity requirements on the number of noncompromised sensors. We study the effects of sporadic data integrity enforcement, such as message authentication, on control performance under stealthy attacks. We show that even with sporadic data integrity guarantees, the attacker cannot introduce an unbounded state estimation error while remaining stealthy. We present a design-time framework to derive safe integrity enforcement policies, and illustrate its use; we show that with even 20% of authenticated messages we can ensure satisfiable state estimation errors under attacks.