Rohit Pai

I am a thesis-track MS in Computer Science student at the University of California San Diego, advised by Professor Mihir Bellare.

My research focuses on the end-to-end empirical evaluation of Committing Authenticated Encryption transforms. I design rigorous experiments in C using the OpenSSL EVP interface and systematically compare a new generic transform against existing ones across multiple AEAD schemes.The broader goal of my thesis is to understand which environments different transforms are empirically best suited for.

Building on this, I am particularly interested in designing cryptographic primitives and systems that are modular, composable, and easy to adopt. By doing so, developers can achieve strong security guarantees without constantly tracking new attacks or re-engineering existing systems, simplifying cryptographic adoption at scale while ensuring high performance and reliability.

Previously, I was a Senior Analyst in the Cryptography Engineering and Solutions team at Deutsche Bank in India. I developed and deployed secure hybrid post-quantum communication channels across legacy systems, supporting over 5 million network operations. I also carefully evaluated PQC algorithms for secure adoption and led efforts to patch critical vulnerabilities in legacy applications.

Earlier, I completed my BTech in Computer Engineering from Sardar Patel Institute of Technology in 2022, ranking 3rd in the department. In my capstone project, I developed a robust deep-learning-based malware detection system under the guidance of Dr. Preetida V-Jani.

In my spare time, I enjoy watching basketball (Go Lakers!), travelling, and exploring new food and cuisines with friends and family.

news

Sep 23, 2024	Delighted to begin my MS in Computer Science at UC San Diego, specializing in Cryptography 🔐!
Oct 01, 2023	Promoted to Senior Analyst at Deutsche Bank
Jul 18, 2022	Thrilled to join Deutsche Bank as an Analyst in the Cryptography Engineering team!
Jan 03, 2022	Excited to join SafexPay as a Product Management Intern, contributing to the dynamic Risk Management and International Projects teams!
Dec 31, 2021	Successfuly defended my Bachelor’s Major Project!

selected publications

ICDSAI

Strengthening Deep-Learning-Based Malware Detection Models Against Adversarial Attacks

R. Pai, M. Purohit, and P. Vinayakray

In Advances in Data Science and Artificial Intelligence , 2022

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Detecting malware is no easy feat as there are many families with exponentially more variants. Much research has been carried out into deep-learning-based malware detection models due to their ability to handle large volumes of data and learn complex features. However, classical deep learning models are unable to adapt to malware variants and specially crafted adversarial samples. Moreover, these models have been trained on older and much smaller datasets. Therefore, there is a need for new models capable of withstanding adversarial attacks while providing accurate results. Hence, we propose a model trained on the latest dataset, capable of handling various malicious adversarial samples while providing a low false-positive rate and high precision, recall, and F1 score.
ICAC3

Vigila: Application for General Safety

R. Pai, A. Naik, H. Sandesara, and S. Dholay

In 2021 International Conference on Advances in Computing, Communication, and Control (ICAC3) , 2021

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Most safety applications already existing in the market send SOS messages to the victim’s saved contacts and the police, which could prove to be slow in situations which demand urgency. We propose a system to counter this and to respond to such emergencies. We store real-time location of our users and when anyone presses the SOS button, all users in a 100 meter radius, around that user, are notified about the emergency along with the coordinates of the victim. Our application also maintains a comprehensive first-aid and emergency response guide which the users can peruse so they can be more helpful in such situations.