activity
20242026
collaborators

6 papers

cs.CR2026

ThermoCAPTCHA: Privacy-Preserving Human Verification with Farm-Resistant Traceable Tokens

Shovon Paul, Md Imran Hossen, Xiali Hei

CAPTCHAs remain a critical defense against automated abuse, yet modern systems suffer from well-known limitations in usability, accessibility, and resistance to increasingly capabl…

cs.CR2025

Double Backdoored: Converting Code Large Language Model Backdoors to Traditional Malware via Adversarial Instruction Tuning Attacks

Md Imran Hossen, Sai Venkatesh Chilukoti, Liqun Shan +3

Instruction-tuned Large Language Models designed for coding tasks are increasingly employed as AI coding assistants. However, the cybersecurity vulnerabilities and implications ari…

cs.LG2025

Unified Kernel-Segregated Transpose Convolution Operation

Vijay Srinivas Tida, Md Imran Hossen, Liqun Shan +3

The optimization of the transpose convolution layer for deep learning applications is achieved with the kernel segregation mechanism. However, kernel segregation has disadvantages,…

cs.CV2025

Differentially private fine-tuned NF-Net to predict GI cancer type

Sai Venkatesh Chilukoti, Imran Hossen Md, Liqun Shan +2

Based on global genomic status, the cancer tumor is classified as Microsatellite Instable (MSI) and Microsatellite Stable (MSS). Immunotherapy is used to diagnose MSI, whereas radi…

cs.LG2025

DP-SGD-Global-Adapt-V2-S: Triad Improvements of Privacy, Accuracy and Fairness via Step Decay Noise Multiplier and Step Decay Upper Clipping Threshold

Sai Venkatesh Chilukoti, Md Imran Hossen, Liqun Shan +4

Differentially Private Stochastic Gradient Descent (DP-SGD) has become a widely used technique for safeguarding sensitive information in deep learning applications. Unfortunately,…

cs.SE2024

On the Adversarial Robustness of Instruction-Tuned Large Language Models for Code

Md Imran Hossen, Xiali Hei

The advent of instruction-tuned Large Language Models designed for coding tasks (Code LLMs) has transformed software engineering practices. However, their robustness against variou…