activity
20072026
most citedDeepSweep: An Evaluation Framework for Mitigating DNN Backdoor Attacks using Data Augmentation

25 citations · 77 across the 18 of their papers we have counts for

collaborators

21 papers

cs.AI2026

Agentic-ZTA: A Multi-Agent Architecture for Autonomous Zero Trust Enforcement

Shovan Roy, Lopamudra Praharaj, Maanak Gupta +1

Agentic AI is emerging as a promising paradigm for automating complex cybersecurity decisions, yet its use in enforcing zero trust introduces significant challenges in safety, reli…

cs.CL2026

TRIS: A Tri-Layer Retrieval Integrity Sieve Against Knowledge Poisoning

Muhaimin Bin Munir, Akib Jawad Ononto, Nazia Shehnaz Joynab +2

Retrieval-Augmented Generation (RAG) grounds large language models in external corpora, but implicit trust in retrieved documents creates a critical attack surface: PoisonedRAG sho…

cs.LG2026

Robust and Explainable Divide-and-Conquer Learning for Intrusion Detection

Yan Zhou, Kevin Hamlen, Michael De Lucia +5

Machine learning-based intrusion detection requires complex models to capture patterns in high-dimensional, noisy, and class-imbalanced raw network traffic, yet deploying such mode…

cs.CV2026

SPRINT: Semi-supervised Prototypical Representation for Few-Shot Class-Incremental Tabular Learning

Umid Suleymanov, Murat Kantarcioglu, Kevin S Chan +6

Real-world systems must continuously adapt to novel concepts from limited data without forgetting previously acquired knowledge. While Few-Shot Class-Incremental Learning (FSCIL) i…

cs.DB2025

NOMAD -- Navigating Optimal Model Application to Datastreams

Ashwin Gerard Colaco, Sharad Mehrotra, Michael J De Lucia +5

NOMAD (Navigating Optimal Model Application for Datastreams) is an intelligent framework for data enrichment during ingestion that optimizes realtime multiclass classification by d…

cs.LG2025

PEAR: Planner-Executor Agent Robustness Benchmark

Shen Dong, Mingxuan Zhang, Pengfei He +4

Large Language Model (LLM)-based Multi-Agent Systems (MAS) have emerged as a powerful paradigm for tackling complex, multi-step tasks across diverse domains. However, despite their…