Selected Projects

Addressing authentication vulnerabilities, my work focuses on user privacy and security enhancement through Multi-Factor Authentication (MFA), utilizing a combination of user-centered research to generate actionable recommendations and improve individual security practices. 

The project navigates the complex realm of privacy and security across major social media and messaging platforms, addressing prevalent user concerns. Through in-depth analysis and innovative solutions, it aims to enhance online data protection.

Phishing is a prevalent and potent cybersecurity threat. We develop tailored solutions aligned with users' mental models, which are derived from user-centric studies. These tools aim to effectively convey risks, empowering users to navigate online spaces securely.

The project delves into the privacy and security implications of IoT devices, with a particular focus on smart toys, healthcare technology integrating user studies to comprehend and address associated concerns in daily usage. 

The surge in E-waste brings not only well-known environmental issues but also overlooked security risks in discarded and refurbished devices. The project offers practical understudied directions and solutions to alleviate these threats.

Augmented Reality (AR) and Virtual Reality (VR) technologies advance and  present escalating security and privacy challenges. We focus on developing stringent authentication, data encryption, and clear privacy policies to foster user trust and reduce potential risks.

Amidst the increasing ubiquity of ePayment solutions, this project aims to rigorously evaluate a broad spectrum of mobile payment applications, assessing their security, privacy, and usability features. Our solution focuses on enhancement of user trust and experience in these prevalent digital transaction.

Dedicated to improving mental health services, our research delves into the potential of user-friendly chatbots in digital mental healthcare, with a special emphasis on addressing the specific needs of older adults. Our goal is to foster a safer and more inclusive space for those pursuing mental health support.

Leveraging deep learning and natural language processing, this project aims to streamline and clarify privacy policies by extracting, categorizing, and structuring information. We aim to create an automated platform that tackles issues of readability and ambiguity.

The Internet of Medical Things (IoMT) enhances older adults' lives with advanced health monitoring, yet raises security and privacy risks. We are developing a tailored IoMT security framework to protect the elderly's health data and maintain their privacy.