Rizwana Akter – Center for Connected Multimodal Mobility https://cecas.clemson.edu/C2M2 Clemson University Innovation Center Fri, 20 May 2022 04:10:48 +0000 en-US hourly 1 https://wordpress.org/?v=6.5.2 https://cecas.clemson.edu/C2M2/wp-content/uploads/2017/05/cropped-logo-32x32.png Rizwana Akter – Center for Connected Multimodal Mobility https://cecas.clemson.edu/C2M2 32 32 C2M2 CPS Frontiers Series – Dr. Zadid Khan https://cecas.clemson.edu/C2M2/c2m2-cps-frontiers-series-dr-zadid-khan/ Fri, 20 May 2022 03:57:48 +0000 https://cecas.clemson.edu/C2M2/?p=8390 Read moreC2M2 CPS Frontiers Series – Dr. Zadid Khan]]>

C2M2 would like to thank Dr. Zadid Khan, Walmart for taking part in our C2M2 CPS Frontiers Series. Dr. Khan spoke on April 21, 2022.

Seminar Title

Cybersecurity of Connected Automated Vehicles in Transportation Cyber-physical Systems with Artificial Intelligence.

Seminar Abstract

The transportation system in the US is transforming into intelligent cyber-physical systems (CPS) with the advancement and merging of sensing, computer, and communication technologies. One of the core components of the transportation CPS (TCPS) is connected and automated vehicles (CAVs). Improving the cybersecurity of in-vehicle networks and automated vehicle applications are critical areas that need further attention. In this talk, Dr. Zadid Khan demonstrates novel methods and models to improve the cybersecurity of CAVs using artificial intelligence under different cyberattack scenarios. This talk is composed of two primary topics. In the first topic, an anomaly detection model is developed for a vehicle’s in-vehicle controller area network (CAN). The model is evaluated using CAN datasets from two real vehicles. Test results show improvement in detection accuracy over baseline models with the model. The second topic focuses on the cybersecurity of automated vehicles. Under this topic, a hybrid defense method is developed that protects an autonomous vehicle’s deep learning models against adversarial attacks. These deep learning models are used for traffic sign classification. This method uses a combination of random filtering, ensembling, and local feature mapping methods to improve the resilience of the traffic sign classifier used by autonomous vehicles. Analysis shows that this defense method improves baseline defense strategies in making an autonomous vehicle sign classifier resilient against different types of adversarial attacks.

Speaker Bio

Dr. Zadid Khan is a Senior Data Analyst in the supply chain (transportation) department at Walmart, Inc. He received his Ph.D. and M.Sc. in Civil Engineering (transportation major) from Clemson University and B.Sc. degree in Electrical Engineering from the Bangladesh University of Engineering and Technology (BUET). His primary research focus is cybersecurity and reliability of transportation cyber-physical systems (TCPS) and connected automated vehicles (CAVs). Within the TCPS and CAV domains, his research interests are data science, machine/ deep learning, computer networking, data analytics, cloud computing, and optimization. During his Ph.D. and M.Sc., Dr. Zadid Khan worked under the supervision of Dr. Mashrur “Ronnie” Chowdhury on multiple C2M2 supported research projects.  

]]> C2M2 CPS Frontiers Series – Manveen Kaur https://cecas.clemson.edu/C2M2/c2m2-cps-frontiers-series-manveen-kaur/ Fri, 20 May 2022 03:37:55 +0000 https://cecas.clemson.edu/C2M2/?p=8384 Read moreC2M2 CPS Frontiers Series – Manveen Kaur]]>

C2M2 would like to thank Manveen Kaur, Clemson University for taking part in our C2M2 CPS Frontiers Series. Manveen Kaur spoke on April 28, 2022.

Seminar Title

The Design and Validation of an ICN-Enabled Hybrid Unmanned Aerial System.

Seminar Abstract

This talk will present a measurement study that evaluates a novel Information-Centric Networking (ICN)- enabled Hybrid Unmanned Aerial Vehicle (UAV) System called IH-UAS. IH-UAS leverages ICN and an innovative system model integrating broker-based publish-subscribe message dissemination with a decentralized architecture to form an ad hoc (infrastructure-less) UAS to carry out military missions. The goal of this study is to design a system that pushes decision-making to the UAV swarm on the battlefield such that mission tasks are completed more reliably and in less time than traditional centralized UAV-based missions. We use theoretical and measurement-based analysis to validate the system. Through experiments conducted using a simplified variant of a Coordinated Search and Tracking (CSAT) application in IH-UAS, we demonstrate that IH-UAS performs better than the same application operating in a traditional centralized solution. We also discuss how the broker placement and the number of brokers are critical to application performance.

Speaker Bio

Manveen Kaur is a Ph.D. student in the School of Computing at Clemson University. Her research focuses broadly on wireless networks and systems, specifically designing, implementing and evaluating systems design and communication methods for emergent Internet of Things (IoT) systems. The two primary systems used in her research are Connected Vehicular Networks and Unmanned Aerial Vehicle (UAV) swarms. She is currently working on a solution that provides efficient system connectivity and data dissemination services for resource-constrained IoT systems running data compute-intensive applications with strict performance requirements. Manveen obtained her M.S. degree in Electrical and Computer Engineering from The Ohio State University. She worked in the media-streaming industry as a Systems Engineer before joining Clemson University.  

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