In this work, we develop an approach to anomaly detection and prevention problem using Signal Temporal Logic (STL). This approach consists of two steps: detection of the causes of the anomalities as STL formulas and prevention of the satisfaction of the formula via controller synthesis. This work focuses on the first step and proposes a formula template such that any controllable cause can be represented in this template. An efficient algorithm to synthesize formulas in this template is presented. Finally, the results are shown on an example
We propose a novel passive learning approach, TeLEx, to infer signal temporal logic formulas that ch...
In this paper, we investigate the controller design problem for linear disturbed systems under signa...
This paper presents an inference algorithm that can discover temporal logic properties of a system f...
In this work, we propose a novel method to find temporal properties that lead to the unexpected beha...
In online monitoring, it is crucial to detect a deviation from normal behavior as soon as it occurs....
Due to its expressivity and efficient algorithms, Signal Temporal Logic (STL) is widely used in runt...
In online monitoring of critical systems, it is important to detect an abnormal behavior as early as...
Online monitoring is essential to enhance the reliability for various systems including cyber-physic...
The increased complexity of modern systems necessitates automated anomaly detection methods to detec...
Signal Temporal Logic (STL) is used to reason about the behavior of continuous signals. Due to its e...
Signal temporal logic (STL) is a formal language for expressing temporal and real-time properties of...
In this paper, a backpropagation based algorithm is presented to learn parameters of past time Signa...
We propose a novel passive learning approach, TeLex, to infer signal temporal logic (STL) formulas t...
Parameters are often used to tune mathematical models and capture nondeterminism and uncertainty in ...
We propose a novel passive learning approach, TeLEx, to infer signal temporal logic formulas that ch...
We propose a novel passive learning approach, TeLEx, to infer signal temporal logic formulas that ch...
In this paper, we investigate the controller design problem for linear disturbed systems under signa...
This paper presents an inference algorithm that can discover temporal logic properties of a system f...
In this work, we propose a novel method to find temporal properties that lead to the unexpected beha...
In online monitoring, it is crucial to detect a deviation from normal behavior as soon as it occurs....
Due to its expressivity and efficient algorithms, Signal Temporal Logic (STL) is widely used in runt...
In online monitoring of critical systems, it is important to detect an abnormal behavior as early as...
Online monitoring is essential to enhance the reliability for various systems including cyber-physic...
The increased complexity of modern systems necessitates automated anomaly detection methods to detec...
Signal Temporal Logic (STL) is used to reason about the behavior of continuous signals. Due to its e...
Signal temporal logic (STL) is a formal language for expressing temporal and real-time properties of...
In this paper, a backpropagation based algorithm is presented to learn parameters of past time Signa...
We propose a novel passive learning approach, TeLex, to infer signal temporal logic (STL) formulas t...
Parameters are often used to tune mathematical models and capture nondeterminism and uncertainty in ...
We propose a novel passive learning approach, TeLEx, to infer signal temporal logic formulas that ch...
We propose a novel passive learning approach, TeLEx, to infer signal temporal logic formulas that ch...
In this paper, we investigate the controller design problem for linear disturbed systems under signa...
This paper presents an inference algorithm that can discover temporal logic properties of a system f...