國立虎尾科技大學 |

Security Enhancement of Vehicle Software Systems.

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Security Enhancement of Vehicle Software Systems./
作者:	Moukahal, Lama J. .
出版者:	Ann Arbor : ProQuest Dissertations & Theses, : 2021,
面頁冊數:	219 p.
附註:	Source: Dissertations Abstracts International, Volume: 83-10, Section: B.
Contained By:	Dissertations Abstracts International83-10B.
標題:	Transportation. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=29005963
ISBN:	9798209916796

Security Enhancement of Vehicle Software Systems.
Moukahal, Lama J. .

Security Enhancement of Vehicle Software Systems. - Ann Arbor : ProQuest Dissertations & Theses, 2021 - 219 p.

Source: Dissertations Abstracts International, Volume: 83-10, Section: B.

Thesis (Ph.D.)--Queen's University (Canada), 2021.

This item must not be sold to any third party vendors.

In an era of connectivity and automation, the vehicle industry is adopting various technologies to transfer driver-centric vehicles to intelligent mechanical devices driven by software components. However, software integration and network connectivity inherit numerous security issues. This thesis offers methods and tools that collaboratively enhance vehicle software security, making vehicles more resilient to cyber incidents. The uniqueness of Connected Autonomous Vehicles (CAVs) invites challenges for Vehicle Software Engineering (VSE) that render traditional software development models and practical solutions less effective for automotive software development. This research presents a Secure Vehicle Software Engineering (SVSE) lifecycle that ensures security-by-design, devoting security considerations throughout all phases of the vehicle software development process. We also introduce novel security enhancement techniques to be employed during the SVSE lifecycle. We propose security vulnerability metrics tailored to identify complexity within vehicle software systems that open the door for malicious behavior. These metrics are utilized with grey-box fuzzing to offer a vulnerability-oriented fuzz testing (VulFuzz) framework explicitly designed to address vehicle security testing challenges. Using the vulnerability scores, VulFuzz systematically directs and prioritizes the fuzz testing toward the most vulnerable components. Depending on the component under test, fuzz testing may not be sufficient to assure a reliable system. Fuzz testing blindness prevents it from exploring the deep paths of the system, which is critical to evaluate for safety-critical components. As a result, we present a hybrid fuzz testing framework (VulFuzz++) that unites the efficiency of fuzzing and the precision of concolic execution to provide the automotive industry a reliable security testing tool. VulFuzz++ utilizes a tailored, targeted concolic engine that limits the symbolic exploration to only specific functions. While security testing can identify many vulnerabilities and enhance security, vehicles’ resilience against attacks might change during their operational lifespan. We introduce a security decay assessment framework that monitors vehicles’ security risks and recognizes security failure. We have implemented and evaluated the security enhancement techniques on OpenPilot, an automotive Autopilot system. The results show the effectiveness of the proposed techniques in strengthening vehicles’ resilience by identifying vulnerabilities at an early stage.

ISBN: 9798209916796Subjects--Topical Terms:

558117
Transportation.

Security Enhancement of Vehicle Software Systems.
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