167 citations · 244 across the 13 of their papers we have counts for
4 papers · 1 filter
APIRL: Deep Reinforcement Learning for REST API Fuzzing
Myles Foley, Sergio Maffeis
REST APIs have become key components of web services. However, they often contain logic flaws resulting in server side errors or security vulnerabilities. HTTP requests are used as…
HarmLevelBench: Evaluating Harm-Level Compliance and the Impact of Quantization on Model Alignment
Yannis Belkhiter, Giulio Zizzo, Sergio Maffeis
With the introduction of the transformers architecture, LLMs have revolutionized the NLP field with ever more powerful models. Nevertheless, their development came up with several…
Differentially Private and Adversarially Robust Machine Learning: An Empirical Evaluation
Janvi Thakkar, Giulio Zizzo, Sergio Maffeis
Malicious adversaries can attack machine learning models to infer sensitive information or damage the system by launching a series of evasion attacks. Although various work address…
Elevating Defenses: Bridging Adversarial Training and Watermarking for Model Resilience
Janvi Thakkar, Giulio Zizzo, Sergio Maffeis
Machine learning models are being used in an increasing number of critical applications; thus, securing their integrity and ownership is critical. Recent studies observed that adve…