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20192023
most citedRisk-Awareness in Learning Neural Controllers for Temporal Logic Objectives

1 citations · 2 across the 7 of their papers we have counts for

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eess.SY20221 cited

Risk-Awareness in Learning Neural Controllers for Temporal Logic Objectives

Navid Hashemi, Xin Qin, Jyotirmoy V. Deshmukh +4

In this paper, we consider the problem of synthesizing a controller in the presence of uncertainty such that the resulting closed-loop system satisfies certain hard constraints whi…

eess.SY2019

Distributionally Robust Tuning of Anomaly Detectors in Cyber-Physical Systems with Stealthy Attacks

Venkatraman Renganathan, Navid Hashemi, Justin Ruths +1

Designing resilient control strategies for mitigating stealthy attacks is a crucial task in emerging cyber-physical systems. In the design of anomaly detectors, it is common to ass…

eess.SY2019

Filtering Approaches for Dealing with Noise in Anomaly Detection

Navid Hashemi, Eduardo Verdugo German, Jonatan Pena Ramirez +1

The leading workhorse of anomaly (and attack) detection in the literature has been residual-based detectors, where the residual is the discrepancy between the observed output provi…

eess.SY2019

Generalized chi-squared detector for LTI systems with non-Gaussian noise

Navid Hashemi, Justin Ruths

Previously, we derived exact relationships between the properties of a linear time-invariant control system and properties of an anomaly detector that quantified the impact an atta…

eess.SY2019

Co-design for Security and Performance: LMI Tools

Navid Hashemi, Justin Ruths

We present a convex optimization to reduce the impact of sensor falsification attacks in linear time invariant systems controlled by observer-based feedback. We accomplish this by…