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Toward High Robustness and Resiliency using Fault/Attack Detection

Title
Toward High Robustness and Resiliency using Fault/Attack Detection
Translated Title
오류 및 공격 검출을 통한 강인성 과 고 신뢰성 획득
Authors
Jo, Min Su
DGIST Authors
Jo, Min Su; Son, Sang Hyuk; Lee, Seong Hun
Advisor(s)
Son, Sang Hyuk
Co-Advisor(s)
Lee, Seong Hun
Issue Date
2017
Available Date
2017-01-18
Degree Date
2017. 2
Type
Thesis
Keywords
RobustnessSensor fusionSensor attackAttack detectionHardware redundant methodAnalytical redundant method오류 및 공격 검출강인성고 신뢰성
Abstract
Modern Cyber-physical Systems (CPS) in the automobile industry are equipped with various sensors to provide the safety and the convenience such as the obstacle detection and the adaptive cruise control. However, those systems could be vulnerable to sensor attacks (e.g., GPS spoofing) and the malicious sensory data causes the system to be in the danger. Therefore, the robustness and resilience against the abnormal conditions is essential to improve the safety of the system. To achieve the robustness and resiliency, multiple sensors measuring the same physical (i.e., redundancy) can be used. Sensory data obtained from the multiple sensors is fused using various sensor fusion models to detect and identify the malicious sensor data. In this thesis, sensor fault/attack detection methods are elaborated, which can be classified into two types: Hardware redundant method and analytical redundant method. The hardware redundant method is based on the sensor data obtained from multiple sensors. It has the advantage that doesn’t require the process of modeling. However, using multiple sensors causes the high cost and the limitation of the space to be implemented. In contrast, the analytical redundant method is based on the model of the system. It doesn’t require the several sensors. However, modeling a system is complicated and if the modeling has the error, it could result in the false alarm during the fault evaluation. In this thesis, we first focus on the hardware redundant method using several sensors measuring the same physical value. Then, we also handle the analytical redundant method by modeling the unmanned ground vehicle. ⓒ 2017 DGIST
Table Of Contents
I.Introduction 1-- II.Adaptive Transient Fault Model for Sensor Attack Detection 2-- 2.1 Problem Formulation and Preliminaries 4-- 2.1.1 Abstract Sensor Model 4-- 2.1.2 Attack Detection with the Transient Fault Model 5-- 2.1.3 Motivation and Example 7-- 2.2 Adaptive Transient Fault Model 9-- 2.2.1 Detection Scheme with Adaptive Transient Model 10-- 2.2.2 Automating the Transient Fault modeling Process 10-- 2.3 Case Study 12-- 2.3.1 Jackal Robot System Description 12-- 2.3.2 Lookup Table 13-- 2.3.3 Evaluation on Motivating Example 14-- 2.3.4Further Evaluation 17-- 2.4 Conclusion 19-- IV.Performance Analysis of Sensor Fusion Models for Pedal System in Brake-by-Wire System 20-- 3.1 EMB System and Sensor Fusion Model 21-- 3.1.1 Electromechanical Brake (EMB) Systems 22-- 3.1.2 Sensor Fusion Techniques 23-- 3.2 Sensor Fusion Model 23-- 3.2.1 Naïve Averaging Method 24-- 3.2.2 Moving Averaging Method 24-- 3.2.3 Marzullo’s algorithm 25-- 3.2.4 Median Filter 26-- 3.2.5 Iterative Filter 26-- 3.3 Case Study 27-- 3.3.1 System Description 27-- 3.3.2 Curve Fitting Problem 29-- 3.3.3 Performance Evaluation: Sensor fusion 32-- 3.3.4 Hybrid method using Median and Marzullo algorithm 36-- 3.3.5 Motor control using CANoe 36-- 3.3.6 Performance Evaluation: Clamping force 37-- 3.4 Conclusion 39-- III.Hybrid Diagnosis System in the Presence of the Transient Faults 40-- 4.1 Problem Formulation and Proposed Method 42-- 4.1.1 Motivation and Problem Statements 42-- 4.1.2 Proposed System with A-TFM 43-- 4.1.3 Kalman-based Approach for Fault Diagnosis 44-- 4.1.4 Approach of Adaptive Transient Fault Model (A-TFM) 45-- 4.2 Case Study 47-- 4.2.1 Jackal Modeling 47-- 4.2.2 A-TFM for Proposed System 49-- 4.2.3 Comparison and Evalution 50-- 4.3 Conclusion 54-- V. Conclusion and Future Work 54-- References 55
URI
http://dgist.dcollection.net/jsp/common/DcLoOrgPer.jsp?sItemId=000002322990
http://hdl.handle.net/20.500.11750/1522
DOI
10.22677/thesis.2322990
Degree
Master
Department
Information and Communication Engineering
University
DGIST
Files:
Collection:
Information and Communication EngineeringThesesMaster


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