IoT research in the Department of Electrical and Computer Engineering at the University of Texas at San Antonio

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Vehicle Security

Developed AI-based detectors to protect vehicles from cyber attacks. The detectors were trained and tested by driving behavior, driver’s impulsiveness, vehicle’s network, and psychical systems behavior. This early detection and high accuracy detector can enhance roadway safety, which will save human lives from vehicle cyber attacks.

Malware & intrusion detection

Developed AI-based intrusion detection systems to identify malware (i.e., ransomware attacks) in their early deployment stages to prevent the enterprise systems from being compromised. My team is currently developing AI-based early detection and protection techniques to enhance both enterprise (IT network) and operational technology (OT) network systems of critical infrastructure from cyber threats.


Psyber-security

Used psychology principles such as human impulsiveness to develop cybersecurity solutions for cyber physical-human systems. These psychology principles and human subject studies have also been applied and conducted to enhance engineering education. Currently, my team is extending this study to find out the relationship between impulsiveness and insider threats/human errors.

Cybersecurity & data analytics for healthcare

Collaborated with UT Health school of nursing to improve the safety, effectiveness, and efficiency of ICU clinical alarm systems. Initiating a new collaboration to develop AI solutions to detect children’s disabilities (i.e., Autism). The secured IoT ecosystems and communication networks will be designed and deployed to monitor patient’s behavior and detect abnormal behavior in near real time. Treatment will also be provided to patients through this IoT ecosystem.



Blockchain

Developed blockchain-based security solutions to protect the availability and integrity of Internet of Medical Things (IoT) and healthcare information systems (EHR) data. These blockchain-based solutions are currently applying and evaluated for protecting the supply chain from cyber threats.



Hardware security

Recently started a new research direction of hardware security. This research will collaborate with national laboratory researchers for the newly funded CONCISE project. This project will acquire a SCADA (hardware and software) testbed for research and education purposes. My team will focus on researching to develop AI-based solutions to enhance hardware malware detection and protect SCADA systems from side-channel attacks.