6 citations · 21 across the 23 of their papers we have counts for
26 papers
Where Rules End and Judges Begin: Measuring the Judgment Boundary in Multi-Agent Systems Security
Shaswata Mitra, Raj Patel, Subash Neupane +3
LLM-based multi-agent systems (MAS) engage tools, share memory, and delegate tasks, often encountering adversarial content. Current defenses for MAS are typically evaluated in isol…
Staying on the Attractor: Supervising Neural Surrogates of 3D Turbulence Where They Leave It
Yilong Dai, Shaswata Mitra, Raj Patel +7
Neural surrogates are trained to predict 3D turbulent flows in place of direct numerical simulation (DNS). For chaotic flows, the goal is short-term pointwise accuracy followed by…
Evaluating the NIST Bugs Framework Against CWE as a Successor for Automated Vulnerability Classification
Md Nazmul Hoque, Shaswata Mitra, Subash Neupane +2
Vulnerability classification based on root cause weaknesses is essential for numerous cybersecurity activities, where the Common Weakness Enumeration (CWE) serves as a public repos…
Gated Activation Steering for Reducing Sycophancy & Hallucination in Medical Question Answering
Himanshu Tripathi, Subash Neupane, Shaswata Mitra +3
Sycophancy and hallucination are persistent failure modes of Large Language Models (LLMs) across domains. However, it becomes particularly consequential in clinical question answer…
Find Before You Fine-Tune: A Diagnostic Study of Small LLMs for Cybersecurity QA
Shaswata Mitra, Subash Neupane, Trisha Chakraborty +4
Large Language Models (LLMs) are increasingly fine-tuned for critical-domain Question-Answering (QA), yet choosing which small model to adapt, before paying the cost of adaptation,…
Agentra: A Supervisable Multi-Agent Framework for Enterprise Intrusion Response
Raj Patel, Shaswata Mitra, Michele Guida +3
Enterprise intrusion response still depends on static playbooks and analyst-driven triage, creating delay between alert generation and containment. We present Agentra, a supervisab…
Evaluating Open-Source LLMs for Multi-Label ATT&CK Technique Classification on CTI Reports
Ahmed Ryan, Saad Sakib Noor, Md Erfan +3
Classifying Cyber Threat Intelligence (CTI) using MITRE Adversarial Tactics, Techniques, and Common Knowledge (ATT&CK) is essential for proactive defense, but historically required…
The Value of Spike Timing: A Leakage-Resistant Benchmark of SNN Design Choices for Network Intrusion Detection
Raj Patel, Shaswata Mitra, David Amebley +4
Spiking neural networks (SNNs) are increasingly studied for network intrusion detection, but comparative evidence on how neuron models and spike encodings affect performance remain…
What Are Adversaries Doing? Automating Tactics, Techniques, and Procedures Extraction: A Systematic Review
Mahzabin Tamanna, Shaswata Mitra, Md Erfan +4
Adversaries continuously evolve their tactics, techniques, and procedures (TTPs) to achieve their objectives while evading detection, requiring defenders to continually update thei…
AgenticCyOps: Securing Multi-Agentic AI Integration in Enterprise Cyber Operations
Shaswata Mitra, Raj Patel, Sudip Mittal +2
Multi-agent systems (MAS) powered by LLMs promise adaptive, reasoning-driven enterprise workflows, yet granting agents autonomous control over tools, memory, and communication intr…
IRSDA: An Agent-Orchestrated Framework for Enterprise Intrusion Response
Damodar Panigrahi, Raj Patel, Shaswata Mitra +2
Modern enterprise systems face escalating cyber threats that are increasingly dynamic, distributed, and multi-stage in nature. Traditional intrusion detection and response systems…
FALCON: Transforming Cyber Threat Intelligence into Deployable IDS Rules with Self-Reflection
Shaswata Mitra, Subash Neupane, Martin Duclos +5
Signature-based Intrusion Detection Systems (IDS) detect malicious activity by matching network or host events against predefined rules. Security analysts manually develop these ru…
Towards a HIPAA Compliant Agentic AI System in Healthcare
Subash Neupane, Sudip Mittal, Shahram Rahimi
Agentic AI systems powered by Large Language Models (LLMs) as their foundational reasoning engine, are transforming clinical workflows such as medical report generation and clinica…
Semantic-Aware Contrastive Fine-Tuning: Boosting Multimodal Malware Classification with Discriminative Embeddings
Ivan Montoya Sanchez, Shaswata Mitra, Aritran Piplai +1
The rapid evolution of malware variants requires robust classification methods to enhance cybersecurity. While Large Language Models (LLMs) offer potential for generating malware d…
CLINICSUM: Utilizing Language Models for Generating Clinical Summaries from Patient-Doctor Conversations
Subash Neupane, Himanshu Tripathi, Shaswata Mitra +4
This paper presents ClinicSum, a novel framework designed to automatically generate clinical summaries from patient-doctor conversations. It utilizes a two-module architecture: a r…
IRSKG: Unified Intrusion Response System Knowledge Graph Ontology for Cyber Defense
Damodar Panigrahi, Shaswata Mitra, Subash Neupane +2
Cyberattacks are becoming increasingly difficult to detect and prevent due to their sophistication. In response, Autonomous Intelligent Cyber-defense Agents (AICAs) are emerging as…
Transfer Learning Applied to Computer Vision Problems: Survey on Current Progress, Limitations, and Opportunities
Aaryan Panda, Damodar Panigrahi, Shaswata Mitra +2
The field of Computer Vision (CV) has faced challenges. Initially, it relied on handcrafted features and rule-based algorithms, resulting in limited accuracy. The introduction of m…
A Survey on Privacy Attacks Against Digital Twin Systems in AI-Robotics
Ivan A. Fernandez, Subash Neupane, Trisha Chakraborty +5
Industry 4.0 has witnessed the rise of complex robots fueled by the integration of Artificial Intelligence/Machine Learning (AI/ML) and Digital Twin (DT) technologies. While these…
MedInsight: A Multi-Source Context Augmentation Framework for Generating Patient-Centric Medical Responses using Large Language Models
Subash Neupane, Shaswata Mitra, Sudip Mittal +3
Large Language Models (LLMs) have shown impressive capabilities in generating human-like responses. However, their lack of domain-specific knowledge limits their applicability in h…
Use of Graph Neural Networks in Aiding Defensive Cyber Operations
Shaswata Mitra, Trisha Chakraborty, Subash Neupane +2
In an increasingly interconnected world, where information is the lifeblood of modern society, regular cyber-attacks sabotage the confidentiality, integrity, and availability of di…
LOCALINTEL: Generating Organizational Threat Intelligence from Global and Local Cyber Knowledge
Shaswata Mitra, Subash Neupane, Trisha Chakraborty +4
Security Operations Center (SoC) analysts gather threat reports from openly accessible global threat repositories and tailor the information to their organization's needs, such as…
Security Considerations in AI-Robotics: A Survey of Current Methods, Challenges, and Opportunities
Subash Neupane, Shaswata Mitra, Ivan A. Fernandez +5
Robotics and Artificial Intelligence (AI) have been inextricably intertwined since their inception. Today, AI-Robotics systems have become an integral part of our daily lives, from…
URA*: Uncertainty-aware Path Planning using Image-based Aerial-to-Ground Traversability Estimation for Off-road Environments
Charles Moore, Shaswata Mitra, Nisha Pillai +4
A major challenge with off-road autonomous navigation is the lack of maps or road markings that can be used to plan a path for autonomous robots. Classical path planning methods mo…
Survey of Malware Analysis through Control Flow Graph using Machine Learning
Shaswata Mitra, Stephen A. Torri, Sudip Mittal
Malware is a significant threat to the security of computer systems and networks which requires sophisticated techniques to analyze the behavior and functionality for detection. Tr…