東華大學圖書館 |

Language: English

Help

回圖書館首頁

手機版館藏查詢

Back

Switch To: Labeled | MARC Mode | ISBD

Linked to FindBook

Google Book

Amazon

博客來

Context-Aware Detection and Resolution of Data Anomalies for Semi-Autonomous Cyber-Physical Systems.

Record Type:	Electronic resources : Monograph/item
Title/Author:	Context-Aware Detection and Resolution of Data Anomalies for Semi-Autonomous Cyber-Physical Systems./
Author:	Chen, Chun-Yu.
Description:	1 online resource (260 pages)
Notes:	Source: Dissertations Abstracts International, Volume: 84-04, Section: A.
Contained By:	Dissertations Abstracts International84-04A.
Subject:	Computer science. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=29712152click for full text (PQDT)
ISBN:	9798845451033

Context-Aware Detection and Resolution of Data Anomalies for Semi-Autonomous Cyber-Physical Systems.
Chen, Chun-Yu.

Context-Aware Detection and Resolution of Data Anomalies for Semi-Autonomous Cyber-Physical Systems. - 1 online resource (260 pages)

Source: Dissertations Abstracts International, Volume: 84-04, Section: A.

Thesis (Ph.D.)--University of Michigan, 2022.

Includes bibliographical references

A cyber-physical system (CPS) with both autonomous and manual control capabilities, or a semi-autonomous (SA) system, is one of the most commonly seen types of system in our daily lives, such as cars, airplanes and ships. While having the benefits of autonomous control to enhance safety/comfort of transportation and the flexibility of manual control to handle safety-critical situations, SA systems inevitably inherit the vulnerabilities embedded in both control types. That is, an SA system will also suffer from component failures or design/software bugs (e.g., crashes of Boeing 737 MAX) and potential attacks (e.g., sensor spoofing) as a general CPS does. Moreover, since mechanical components are gradually being replaced by their electronic counterparts in SA systems, this trend also introduces new reliability and security risks - increasing adoption of multiple heterogeneous communication interfaces widens attack surfaces that an adversary can exploit. Considering the potential security and safety concerns caused by system faults/flaws, human error, and malicious attacks, we develop a suite of mechanisms/systems for detection and resolution of system anomalies by cross-validating the sensor data and the context information to enhance the security and safety of SA systems from three key perspectives that can directly influence the operation of SA systems - system operation, received information, and control decisions. In this thesis, we propose both domain-general design for SA systems and its domain-specific realization using SA vehicles as a concrete case study. From the system operation perspective, we propose CADD, a context-aware anomaly detection system, to capture abnormal system behavior under various operation contexts while considering practical scenarios where some (context) information cannot be observed by the SA system. We then present DiVa, a diagnostic system that pinpoints/identifies the anomalous source(s) after an anomaly is detected. It exploits the cyber-physical correlation or causality between the internal data of the SA system to narrow down the origin of anomaly while assuming no data can be entirely trusted. From the received information perspective, we propose EDRoad, an easy-to-use system for verification of the data received from external sources to ensure no compromised data will be used to provide services to the SA systems. Finally, from the control decision perspective, we introduce CADCA, a system for detecting and resolving control actions that may potentially lead to unstable system states or safety-critical situations.

Electronic reproduction.
Ann Arbor, Mich. :
ProQuest,
2023

Mode of access: World Wide Web

ISBN: 9798845451033Subjects--Topical Terms:

523869
Computer science.
Subjects--Index Terms:

Semi-Autonomous systemsIndex Terms--Genre/Form:

542853
Electronic books.

Context-Aware Detection and Resolution of Data Anomalies for Semi-Autonomous Cyber-Physical Systems.
LDR:04034nmm a2200409K 4500 001 2356501
005 20230612110839.5
006 m o d
007 cr mn ---uuuuu
008 241011s2022 xx obm 000 0 eng d
020 $a 9798845451033
035 $a (MiAaPQ)AAI29712152
035 $a (MiAaPQ)umichrackham004291
035 $a AAI29712152
040 $a MiAaPQ $b eng $c MiAaPQ $d NTU
100 1 $a Chen, Chun-Yu. $3 3696976
245 1 0 $a Context-Aware Detection and Resolution of Data Anomalies for Semi-Autonomous Cyber-Physical Systems.
264 0 $c 2022
300 $a 1 online resource (260 pages)
336 $a text $b txt $2 rdacontent
337 $a computer $b c $2 rdamedia
338 $a online resource $b cr $2 rdacarrier
500 $a Source: Dissertations Abstracts International, Volume: 84-04, Section: A.
500 $a Advisor: Shin, Kang G.
502 $a Thesis (Ph.D.)--University of Michigan, 2022.
504 $a Includes bibliographical references
520 $a A cyber-physical system (CPS) with both autonomous and manual control capabilities, or a semi-autonomous (SA) system, is one of the most commonly seen types of system in our daily lives, such as cars, airplanes and ships. While having the benefits of autonomous control to enhance safety/comfort of transportation and the flexibility of manual control to handle safety-critical situations, SA systems inevitably inherit the vulnerabilities embedded in both control types. That is, an SA system will also suffer from component failures or design/software bugs (e.g., crashes of Boeing 737 MAX) and potential attacks (e.g., sensor spoofing) as a general CPS does. Moreover, since mechanical components are gradually being replaced by their electronic counterparts in SA systems, this trend also introduces new reliability and security risks - increasing adoption of multiple heterogeneous communication interfaces widens attack surfaces that an adversary can exploit. Considering the potential security and safety concerns caused by system faults/flaws, human error, and malicious attacks, we develop a suite of mechanisms/systems for detection and resolution of system anomalies by cross-validating the sensor data and the context information to enhance the security and safety of SA systems from three key perspectives that can directly influence the operation of SA systems - system operation, received information, and control decisions. In this thesis, we propose both domain-general design for SA systems and its domain-specific realization using SA vehicles as a concrete case study. From the system operation perspective, we propose CADD, a context-aware anomaly detection system, to capture abnormal system behavior under various operation contexts while considering practical scenarios where some (context) information cannot be observed by the SA system. We then present DiVa, a diagnostic system that pinpoints/identifies the anomalous source(s) after an anomaly is detected. It exploits the cyber-physical correlation or causality between the internal data of the SA system to narrow down the origin of anomaly while assuming no data can be entirely trusted. From the received information perspective, we propose EDRoad, an easy-to-use system for verification of the data received from external sources to ensure no compromised data will be used to provide services to the SA systems. Finally, from the control decision perspective, we introduce CADCA, a system for detecting and resolving control actions that may potentially lead to unstable system states or safety-critical situations.
533 $a Electronic reproduction. $b Ann Arbor, Mich. : $c ProQuest, $d 2023
538 $a Mode of access: World Wide Web
650 4 $a Computer science. $3 523869
650 4 $a Computer engineering. $3 621879
650 4 $a Multimedia communications. $3 590562
653 $a Semi-Autonomous systems
653 $a Cyber-Physical Systems
653 $a Anomaly detection
653 $a Security
653 $a Safety
655 7 $a Electronic books. $2 lcsh $3 542853
690 $a 0984
690 $a 0464
690 $a 0558
710 2 $a ProQuest Information and Learning Co. $3 783688
710 2 $a University of Michigan. $b Computer Science & Engineering. $3 3285590
773 0 $t Dissertations Abstracts International $g 84-04A.
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=29712152 $z click for full text (PQDT)