39 citations · 64 across the 16 of their papers we have counts for
5 papers · 1 filter
Adaptive Anomaly Detection for Identifying Attacks in Cyber-Physical Systems: A Systematic Literature Review
Pablo Moriano, Steven C. Hespeler, Mingyan Li +1
Modern cyberattacks in cyber-physical systems (CPS) rapidly evolve and cannot be deterred effectively with most current methods which focused on characterizing past threats. Adapti…
Advancing NLP Security by Leveraging LLMs as Adversarial Engines
Sudarshan Srinivasan, Maria Mahbub, Amir Sadovnik
This position paper proposes a novel approach to advancing NLP security by leveraging Large Language Models (LLMs) as engines for generating diverse adversarial attacks. Building u…
Hiding-in-Plain-Sight (HiPS) Attack on CLIP for Targetted Object Removal from Images
Arka Daw, Megan Hong-Thanh Chung, Maria Mahbub +1
Machine learning models are known to be vulnerable to adversarial attacks, but traditional attacks have mostly focused on single-modalities. With the rise of large multi-modal mode…
Leveraging Large Language Models to Extract Information on Substance Use Disorder Severity from Clinical Notes: A Zero-shot Learning Approach
Maria Mahbub, Gregory M. Dams, Sudarshan Srinivasan +4
Substance use disorder (SUD) poses a major concern due to its detrimental effects on health and society. SUD identification and treatment depend on a variety of factors such as sev…
Dynamic Q&A of Clinical Documents with Large Language Models
Ran Elgedawy, Ioana Danciu, Maria Mahbub +1
Electronic health records (EHRs) house crucial patient data in clinical notes. As these notes grow in volume and complexity, manual extraction becomes challenging. This work introd…