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PhD Dissertation Defense: Qian Wang
Friday, July 19, 2019
9:00 a.m.
AVW 1146
For More Information:
Maria Hoo
301 405 3681
mch@umd.edu

ANNOUNCEMENT: PhD Dissertation Defense

Name: Qian Wang

Advisory Committee:
Professor Gang Qu, Chair/Advisor
Professor Yasser Shoukry
Professor Charalampos Papamanthou
Professor Manoj Franklin
Professor Yang Tao, Dean's Representative

Date/Time: Friday, July 19, 2019 at 9:00 am - 11:00 am 

Location: AVW 1146

Title: Hardware Assisted Solutions for Automobile Security


Abstract:

In the past decade, more and more advanced functions and features have been added to the modern vehicles which make them not only safer and more reliable but also connected, smarter, and more intelligent. To support these updated functions, a large amount of software and hardware electronic equipment is integrated into the car system. Besides, vehicular ad-hoc networks (VANETs) are applied as the foundation of the next generation of intelligent transportation system to improve the efficiency of transportation.  Although these add-on functions around vehicles offer great help in driving assistance, they inevitably introduce some new vulnerabilities that threaten the safety for the on-board drivers and passengers as well as the pedestrians. Many recent attacks have been demonstrated either on the in-vehicle bus or through the wireless communications of vehicle to vehicle. In this thesis, we design and develop hardware oriented solutions on the arousing security issues around the vehicles. More specifically, we focus on adding the security features of the Controller Area Network (CAN) bus to protect it from insider or outsider attacks and as well we also try to ensure the trust and privacy of VANETs through a block-chain based reputation management system.

 

First, we propose a new type of intrusion detection system (IDS) to improve the insecure CAN bus protocol. With this method, we monitor the entropy changes of the identifier bit of the CAN messages. Next, we also develop a delay-based IDS to protect the CAN network by identifying the location of the compromised Electronic Control Unit (ECU) for the in-vehicle network. The proposed scheme is demonstrated to protect the integrity of the messages on CAN bus leading to a further improve the security and safety of autonomous vehicles. Also, we focus on the key management for automotive networks (i.e., CAN) as a critical element, governing the adoption of security in the next generation of vehicles. A recent promising approach for dynamic key agreement between groups of nodes, Plug-and-Secure for the CAN, has been demonstrated to be information theoretically secure based on the physical properties of the CAN bus. We illustrate side-channel attacks, leading to nearly-complete leakage of the secret key bits, by an adversary that is capable of probing the CAN bus. Besides, we take use the rich dataset from the CAN bus and build a cross-validation system to detect the GPS spoofing attacks on the vehicles.  Our proposed method could reconstruct the GPS signal when the GPS signal is unavailable in some circumstances, which could be a backup plan to cope with the failure of GPS for the navigation system. Finally, we propose a blockchain-based anonymous reputation system (BARS) to establish a privacy-preserving trust model for VANETs. The certificate and revocation transparency is implemented efficiently with the proofs of presence and absence based on the extended blockchain technology. Experiments are conducted to evaluate BARS in terms of security and performance and the results show that BARS is able to establish distributed trust management meanwhile protecting the privacy of vehicles.


This Event is For: Graduate • Faculty

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