Publications

Papers & proceedings

A record of AICSIL's published and accepted work, spanning secure configuration, evolutionary algorithms, and privacy-preserving machine learning. Full profile and citation counts on Google Scholar.

2026
AST

HYDRA: A hybrid heuristic-guided deep representation architecture for predicting latent zero-day vulnerabilities in patched functions

Mohammad Farhad, Sabbir Rahman, Shuvalaxmi Dass — Accepted, IEEE Automated Software Testing (AST) 2026

CNC

Memory-Based Malware Detection under Limited Data Conditions: A Comparative Evaluation of TabPFN and Ensemble Models

Valentin Leroy, Shuvalaxmi Dass, Sharif Ullah — Accepted, 2026 Workshop on Computing, Networking and Communications

2025
JAICC

Advancing Moving Target Strategy with Bio-Inspired Reinforcement Learning to Secure Misconfigured Software Applications

Niloofar Heidarikohol, Shuvalaxmi Dass — Journal of Artificial Intelligence & Cloud Computing, 2025, SRC/JAICC-523

2024
Springer

Modeling the Dynamics of Bitcoin Overlay Network

J. Bou Abdo, S. Dass, B. Qolomany, L. Hossain — Complex Networks & Their Applications XII (COMPLEX NETWORKS 2023), Studies in Computational Intelligence, vol. 1143, Springer, Cham

2023
TALE

Cultivating Inclusivity: A Journey Towards Democratizing Cybersecurity Education

J. Schnell, S. Dass, J. B. Abdo, M. Chatterjee — 2023 IEEE International Conference on Teaching, Assessment and Learning for Engineering (TALE), Auckland, New Zealand, pp. 1–4

ICMLA

Towards Privacy-Preserving Financial Fraud Detection

Stephanie Abanilla, Moitrayee Chatterjee, S. Dass — 2023 International Conference on Machine Learning and Applications (ICMLA), Jacksonville, FL, pp. 1723–1726

AIBThings

XorshiftH128+: A hybrid random number generator for lightweight IoT

Serge Sandakly, Charbel Salem, Khalil Challita, Shuvalaxmi Dass, et al. — 2023 IEEE International Conference on Artificial Intelligence, Blockchain, and Internet of Things (AIBThings)

2021
Electronics

Reinforcement Learning for Generating Secure Configurations

Shuvalaxmi Dass, Akbar Siami Namin — Electronics 2021, 10, 2392

COMPSAC

A Hidden Markov Model for Attack Prediction

Shuvalaxmi Dass, Prerit Datta, Akbar Siami Namin — 2021 IEEE 45th Annual Computers, Software, and Applications Conference (COMPSAC), Madrid, Spain, pp. 1695–1702

2020
COMPSAC

Evolutionary Algorithms for Vulnerability Coverage

Shuvalaxmi Dass, Akbar Siami Namin — 2020 IEEE 44th Annual Computers, Software, and Applications Conference, Madrid, Spain, pp. 1795–1801

SAC

Vulnerability Coverage for Adequacy Security Testing

Shuvalaxmi Dass, Akbar Siami Namin — SAC '20: The 35th ACM/SIGAPP Symposium on Applied Computing, pp. 540–543

COMPSAC

Ensemble Random Forests Classifier for Detecting Coincidentally Correct Test Cases

S. Dass, X. Xue, A. Siami Namin — 2020 IEEE 44th Annual Computers, Software, and Applications Conference, Madrid, Spain, pp. 1326–1331

Big Data

A Sensitivity Analysis of Evolutionary Algorithms in Generating Secure Configurations

Shuvalaxmi Dass, Akbar Siami Namin — 2020 IEEE International Conference on Big Data, Atlanta, GA, pp. 2065–2072

Grants

Funded & active proposals

awarded — $10,000

ZeroAware

AI-Integrated Zero-Day Vulnerability Prediction in CI/CD Pipelines for Critical Infrastructure. NSF EPSCoR & LA-NEXT Graduate Student Supplements (GRASS), PI.

funded — $5,000

Visual Modelling Techniques for Cybersecurity Concepts

Internal research grant, University of Nebraska at Kearney, PI.

under review

MTD-CH

A Moving Target Defense — OS Configuration Hardening Framework for Real-Time Mitigation of Configuration Drift and Zero-Day Attacks. NSF SaTC RES, PI.

under review

SeCURE-CPS

AI and Security education through CUREs for Cyber-Physical Systems. NSF CyberAI Innovation, PI.

under review

AEGIS

An Agentic AI Framework for Automated Zero-Day Vulnerability Prediction and Remediation in Patched Code. Amazon Research Award, PI.