Tools

LEADER 03501cam a2200553 i 4500

001 on1523697771;

003 OCoLC;

005 20260708021044.0;

006 m o d ;

007 cr unu||||||||;

008 250616s2025 ncua obm 000 0 eng d;

035 a| (Sirsi) o1523697771;

035 a| (OCoLC)1523697771;

049 a| EREE;

090 a| TL152.8;

100 1 a| Mavroudara, Athanasia,e| author.?| UNAUTHORIZED;

245 10 a| AI advances in autonomous vehicles and cybersecurity concerns /c| by Athanasia Mavroudara.;

264 1 a| [Greenville, N.C.] :b| [East Carolina University],c| 2025.;

300 a| 1 online resource (95 pages) :b| illustrations (some color);

336 a| textb| txt2| rdacontent;

337 a| computerb| c2| rdamedia;

338 a| online resourceb| cr2| rdacarrier;

347 a| text fileb| application/pdfc| 1.2 MB2| rda;

538 a| System requirements: Adobe Reader.;

538 a| Mode of access: World Wide Web.;

502 b| M.S.c| East Carolina Universityd| 2025.;

500 a| Presented to the Faculty of the Department of Technology Systems.;

500 a| Advisor: Sohan Gyawali;

500 a| Title from PDF t.p. (viewed June 26, 2026).;

520 3 a| Autonomous vehicles (AVs) are transforming transportation by improving road safety through advanced technologies. Technologies such as deep learning, computer vision, and reinforcement learning enable AVs to perceive their surroundings, navigate complex environments, and make critical decisions in real-time. However, their reliance on interconnected systems introduces significant cybersecurity challenges, exposing them to threats that could compromise safety and functionality. Addressing these risks requires robust solutions, including encryption, secure communication protocols, and real-time intrusion detection systems. This thesis analyzes how artificial intelligence developments in autonomous vehicles evolve while analyzing the increasing cybersecurity threats these vehicles encounter. The examination analyzed the use of AI for enhancing intrusion detection by evaluating the Car Hacking Dataset utilizing machine learning models. In addition, this thesis assessed the present autonomous vehicle security practices to determine their compatibility with the NIST Cybersecurity Framework. Research shows that AI intrusion detection systems deployed with NIST-derived security standards significantly advance the security of AV networks and strengthen their capability to defend against changing threats.;

504 a| Includes bibliographical references.;

650 0 a| Hacking.=| ^A1280113;

650 0 a| Automated vehiclesx| Security measures.=| ^A1273031;

650 0 a| Machine learning.=| ^A145211;

650 0 a| Artificial intelligence.=| ^A15394;

650 0 a| Internet of thingsx| Security measures.=| ^A1157117;

653 a| AI;

653 a| Cyberattacks;

653 a| Car hacking;

700 1 a| Sohan, Gyawali,e| degree supervisor.?| UNAUTHORIZED;

710 2 a| East Carolina University.b| Department of Technology Systems.?| UNAUTHORIZED;

856 40 z| Access via ScholarShipu| http://hdl.handle.net/10342/14047;

949 o| wjh;

994 a| C0b| ERE;

596 a| 1 4;

998 a| 6584079;

999 a| CLICK ON WEB ADDRESSw| ASISc| 1i| 6584079-1001l| JNETm| JOYNERr| Ys| Yt| JNE3ETDu| 6/16/2025x| ETDz| JERESOURCE;

999 a| CLICK ON WEB ADDRESSw| ASISc| 1i| 6584079-2001l| HSLELECm| HSLr| Ys| Yt| HEETDu| 6/16/2025x| ETDz| HERESOURCE;

AI advances in autonomous vehicles and cybersecurity concerns / by Athanasia Mavroudara.

Author/creator	Mavroudara, Athanasia author.
Other author	Sohan, Gyawali, degree supervisor.
Other author	East Carolina University. Department of Technology Systems.
Format	Theses and dissertations
Publication	[Greenville, N.C.] : [East Carolina University], 2025.
Description	1 online resource (95 pages) : illustrations (some color)
Supplemental Content	Access via ScholarShip
Subjects	Hacking. Automated vehicles--Security measures. Machine learning. Artificial intelligence. Internet of things--Security measures.

Summary	Autonomous vehicles (AVs) are transforming transportation by improving road safety through advanced technologies. Technologies such as deep learning, computer vision, and reinforcement learning enable AVs to perceive their surroundings, navigate complex environments, and make critical decisions in real-time. However, their reliance on interconnected systems introduces significant cybersecurity challenges, exposing them to threats that could compromise safety and functionality. Addressing these risks requires robust solutions, including encryption, secure communication protocols, and real-time intrusion detection systems. This thesis analyzes how artificial intelligence developments in autonomous vehicles evolve while analyzing the increasing cybersecurity threats these vehicles encounter. The examination analyzed the use of AI for enhancing intrusion detection by evaluating the Car Hacking Dataset utilizing machine learning models. In addition, this thesis assessed the present autonomous vehicle security practices to determine their compatibility with the NIST Cybersecurity Framework. Research shows that AI intrusion detection systems deployed with NIST-derived security standards significantly advance the security of AV networks and strengthen their capability to defend against changing threats.
General note	Presented to the Faculty of the Department of Technology Systems.
General note	Advisor: Sohan Gyawali
General note	Title from PDF t.p. (viewed June 26, 2026).
Dissertation note	M.S. East Carolina University 2025.
Bibliography note	Includes bibliographical references.
Technical details	System requirements: Adobe Reader.
Technical details	Mode of access: World Wide Web.

Availability

Library	Location	Call Number	Status	Item Actions
	Electronic Resources	Access Content Online	✔ Available

AI advances in autonomous vehicles and cybersecurity concerns / by Athanasia Mavroudara.

Click here for more information about this title

Availability