An Adversarial Machine Learning Approach to Evaluate the Robustness of a Security Solution. - Ciprian-Alin Simion; Dragos Teodor Gavrilut; Henri Luchian (SYNASC, 2019)

Using GANs to Improve the Accuracy of Machine Learning Models for Malware Detection. - Ciprian-Alin Simion; Gheorghe Balan; Dragos Teodor Gavrilut (IDEAL, 2022)

Improving detection of malicious samples by using state-of-the-art adversarial machine learning algorithms. - Ciprian-Alin Simion; Gheorghe Balan; Dragos Teodor Gavrilut (SIN, 2022)

Reducing Adversarial Vulnerability Using GANs. - Ciprian-Alin Simion (SYNASC, 2022)

Feature mining and classifier selection for API calls-based malware detection. - Gheorghe Balan; Ciprian-Alin Simion; Dragos Teodor Gavrilut; Henri Luchian (Appl. Intell., 2023)

Benchmarking Out of the Box Open-Source LLMs for Malware Detection Based on API Calls Sequences. - Ciprian-Alin Simion; Gheorghe Balan; Dragos Teodor Gavrilut (IDEAL (1), 2024)

Fine Tuning LLMs vs Non-Generative Machine Learning Models: A Comparative Study of Malware Detection. - Gheorghe Balan; Ciprian-Alin Simion; Dragos Teodor Gavrilut (ICAART (3), 2025)