6 papers
Botnet Detection on CTU-13 Using Lightweight Machine Learning Models
Subhash Gurappa, Yashas Hariprasad, Sundararaj Sitharama Iyengar +1
Botnets are among the most persistent cyber threats, enabling large-scale attacks such as spam, credential theft, and distributed denial-of-service (DDoS). While deep learning appr…
MedSR-Vision: Deep Learning Framework for Multi-Domain Medical Image Super-Resolution
Subhash Gurappa, Trivikram Satharasi, Yashas Hariprasad +1
Medical image super-resolution (MedSR) is essential for improving diagnostic precision across diverse imaging modalities such as MRI, CT, X-ray, Ultrasound, and Fundus imaging. Des…
Empowering Future Cybersecurity Leaders: Advancing Students through FINDS Education for Digital Forensic Excellence
Yashas Hariprasad, Subhash Gurappa, Sundararaj S. Iyengar +3
The Forensics Investigations Network in Digital Sciences (FINDS) Research Center of Excellence (CoE), funded by the U.S. Army Research Laboratory, advances Digital Forensic Enginee…
State Dependent Optimization with Quantum Circuit Cutting
Xinpeng Li, Ji Liu, Jeffrey M. Larson +4
Quantum circuits can be reduced through optimization to better fit the constraints of quantum hardware. One such method, initial-state dependent optimization (ISDO), reduces gate c…
Distributed LLMs and Multimodal Large Language Models: A Survey on Advances, Challenges, and Future Directions
Hadi Amini, Md Jueal Mia, Yasaman Saadati +6
Language models (LMs) are machine learning models designed to predict linguistic patterns by estimating the probability of word sequences based on large-scale datasets, such as tex…
Do We Really Need to Design New Byzantine-robust Aggregation Rules?
Minghong Fang, Seyedsina Nabavirazavi, Zhuqing Liu +3
Federated learning (FL) allows multiple clients to collaboratively train a global machine learning model through a server, without exchanging their private training data. However,…