Dr. Sunitha Safavat - Research & Publications

Dr. Sunitha Safavat

Ph.D Research Scientist at Howard University

Web: www.sunitha-safavat.com

Dissertation Topic: "Secure Communication and Content Caching for Internet of Vehicles"

Research Guide: Dr. Danda B. Rawat

“Arise, awake, and don’t stop till you reach your goal” - Swami Vivekananda

I’m a Ph.D. Graduate at the prestigious R1 "Howard University". My research revolves around developing and enhancing security tools for wireless communication in the fascinating realms of the Internet of Things (IoT), Vehicular Networks, and Cyber-Physical Systems. By harnessing cutting-edge technologies such as Artificial Intelligence/Machine Learning, Blockchain, and Cryptographic Protocols, I strive to create innovative solutions for the complex challenges that arise in the realm of IoT, Vehicular Networks, and Cyber-Physical Systems applications.

Under the guidance of Dr. Danda B. Rawat, an esteemed professor at HU, currently, I am actively conducting research work in Cybersecurity at the distinguished Department of Defense Center of Excellence in Artificial Intelligence and Machine Learning (CoE-AIML) at Howard University.

The concept of the Internet of Things (IoT) has completely transformed the way we perceive connectivity. With the IoT, apart from personal computers, it also enabled the possibility for embedding internet connectivity and relevant functions in various types of devices. The world has witnessed rapid growth in the connectivity of vehicles, smart homes, sensor cameras and other security devices to the internet. At the same time, the concerns regarding security and privacy in IoT have also gained prominent attention as the world recognizes the true potential of IoT. My field of research broadly lies at the intersection of Artificial Intelligence, mobile edge computing, software-defined systems, and Cybersecurity, where I seek to develop new analytical tools for understanding and enhancing the performance of Wireless communication in Internet of Vehicles (IoV) Networks, as well as I develop security approaches for IoV applications. During my Ph.D (December 2018 – Present), I discovered that, Internet of Vehicles (IoV) is a typical application of Internet of things in the field of transportation, which aims at achieving an integrated intelligent transportation system to enhance traffics, to avoid accidents, to ensure road safety, and to improve driving experiences.

Due to its characteristics of dynamic topological structures, huge network scale, non-uniform distribution of nodes, and mobile limitation, IoV systems face various types of attacks, such as authentication and identification attacks, availability attacks, confidentiality attacks, routing attacks, data authenticity attacks and etc., which result in several challenging requirements in security and privacy. To address security and privacy issues, I developed an Elliptic Curve Cryptography (ECC) based Ant Colony Optimization Ad hoc On-demand Distance Vector (ACO-AODV) routing protocol which avoids suspicious vehicles during message dissemination in IoV and improves efficiency in the wireless communication systems. I also discovered that Unmanned Aerial Vehicles (UAVs) in Flying Ad-Hoc Networks (FANET) are increasing rapidly and being employed for many civilian and military applications. UAVs carry sensitive data and hence, it is crucial to authenticate UAVs’ identities before they begin to communicate with each other. However, the traditional authentication methods encompass a low secure ability. To address this issue, I proposed a “modified Elliptic Curve Cryptography (ECC) based lightweight identity authentication method” which makes sure no malicious UAVs present in the FANET and improves wireless communications overhead. During my Master’s, I studied about recent advances in mobile edge computing and content caching. This was an insightful model to study how the demand for digital media services is increasing as the number of wireless subscriptions are growing exponentially. In order to meet this growing need, mobile wireless networks have been advanced at a tremendous pace over recent days. However, the centralized architecture of existing mobile networks, with limited capacity and range of bandwidth of the radio access network and low bandwidth back-haul network, cannot handle the exponentially increasing mobile traffic.

I have done extensive research on this issue and presented a survey on recent advances in mobile edge computing and content caching, including caching insertion and expulsion policies, the behavior of the caching system, and caching optimization based on wireless networks. Some of the important open challenges in mobile edge computing with content caching are identified and discussed. Also compared edge, fog and cloud computing in terms of delay which help researchers to get a thorough understanding of recent advances in mobile edge computing and content caching in mobile wireless networks. In the future, my work will focus on (1) Emerging sustainable and intelligent transportation systems, including connected and automated vehicles (CAVs), transportation electrification, mobility-as-a service (MaaS), and active transportation. (2) Application of machine learning techniques to modeling, secure and control of transportation systems. (3) Develop best security approaches for manned and unmanned vehicles and systems which we use in emergency and military applications.

Research & Industry Publications:

Safavat, Sunitha, and Danda B. Rawat. "On the elliptic curve cryptography for privacy-aware secure ACO-AODV routing in intent-based internet of vehicles for smart cities." IEEE Transactions on Intelligent Transportation Systems 22.8 (2020): 5050-5059.
Safavat, Sunitha, and Danda B. Rawat. "OptiML: An enhanced ML approach towards design of SDN based UAV networks." ICC 2022-IEEE International Conference on Communications. IEEE, 2022.
Safavat, Sunitha, and Danda B. Rawat. "Improved multiresolution neural network for mobility-aware security and content caching for internet of vehicles." IEEE Internet of Things Journal 10.20 (2023): 17813-17823.
Safavat, Sunitha, and Danda B. Rawat. "Asynchronous federated learning for intrusion detection in vehicular cyber-physical systems." IEEE INFOCOM 2023-IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS). IEEE, 2023.
Safavat, Sunitha, and Danda B. Rawat. "Securing unmanned aerial vehicular networks using modified elliptic curve cryptography." MILCOM 2021-2021 IEEE Military Communications Conference (MILCOM). IEEE, 2021.
Safavat, Sunitha, and Danda B. Rawat. "Energy-efficient resource scheduling using x-cnn and cd-sbo for sdn based mec enabled iov." 2023 IEEE 20th Consumer Communications & Networking Conference (CCNC). IEEE, 2023.
Safavat, Sunitha, and Danda B. Rawat. "Digital Twin Based Asynchronous Federated Learning Enabled IDS for False Data Injection Attacks in Vehicular CPS." 2024 8th International Conference on Computer, Software and Modeling (ICCSM). IEEE, 2024.
Safavat, Sunitha, and Danda B. Rawat. "Joint Exponential Window-Kalman Filter and Weight Normalized ReLU-Memristor Activation Function-LSTM-based Proactive Content Caching framework in IoV using Asynchronous Federated Learning." ICC 2024-IEEE International Conference on Communications. IEEE, 2024.
Safavat, Sunitha, Naveen Naik Sapavath, and Danda B. Rawat. "Recent advances in mobile edge computing and content caching." Digital Communications and Networks 6.2 (2020): 189-194.
Vinay Gugueoth, Sunitha Safavat, Sachin Shetty, "Security of Internet of Things (IoT) using federated learning and deep learning — Recent advancements, issues and prospects" ICT Express, 2023, ISSN 2405-9595.
Vinay Gugueoth, Sunitha Safavat, Sachin Shetty, "A Review of IoT Security and Privacy Using Decentralized Blockchain Techniques" Computer Science Review, 2023, COSREV-D-23-00048R1.
Sapavath, Naveen Naik, Sunitha Safavonlinelibrary.wiley.com/doi/abs/10.1002/ett.3713 at, and Danda B. Rawat. "On the machine learning–based smart beamforming for wireless virtualization with large‐scale MIMO system." Transactions on Emerging Telecommunications Technologies 30.9 (2019): e3713.

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