8 papers
RuleAutoPilot: Synthesizing Deployable Suricata Rules from Network Traffic
Mughees Ur Rehman, Aritran Piplai, Murat Kantarcioglu
Rule-based Intrusion Detection Systems (IDS) such as Suricata are central to network security, yet crafting effective detection rules demands deep expert knowledge and cannot keep…
AI Deployment Accountability Engineering: A Vision for Accountable AI in Safety-Critical Socio-Technical Systems
Murat Kantarcioglu
Artificial intelligence systems are rapidly becoming critical components in healthcare, finance, public services, and other safety-critical domains. Yet the engineering practices u…
Auditing Fairness-Privacy Trade-offs: Subpopulation-Level Effects of Fairness-Enhancing Algorithms
Umid Suleymanov, Ilhama Novruzova, Khalid Mammadov +2
Machine learning (ML) models deployed in sensitive domains such as healthcare, law enforcement, and finance must satisfy not only utility requirements but also fairness and privacy…
GitInject: Real-World Prompt Injection Attacks in AI-Powered CI/CD Pipelines
Jafar Isbarov, Umid Suleymanov, Ilia Shumailov +1
AI-powered agents are increasingly embedded in continuous integration and continuous delivery/deployment (CI/CD) pipelines to autonomously review pull requests (PRs), triage issues…
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…
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…
Beyond Refusal: Probing the Limits of Agentic Self-Correction for Semantic Sensitive Information
Umid Suleymanov, Zaur Rajabov, Emil Mirzazada +1
While defenses for structured PII are mature, Large Language Models (LLMs) pose a new threat: Semantic Sensitive Information (SemSI), where models infer sensitive identity attribut…
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…