| 2026 | SAC | Back to the Future: Refurbishing Critical Software Engineering to Enable Trustworthy Classification. | Tommaso Zoppi, Muhammad Atif, Fahad Ahmed KhoKhar, Andrea Bondavalli |
| 2025 | ICSA | System-Awareness: An Enabling Condition to Design and Deploy Anomaly Detectors. | Muhammad Atif, Tommaso Zoppi, Andrea Bondavalli |
| 2025 | PRDC | Orchestrating Fail-Safe, Black-Box Models Within Federated Learning Scenarios. | Fahad Ahmed KhoKhar, Tommaso Zoppi, Jamal Hussain Shah |
| 2024 | PRDC | Deploying a Generic Threat Model for Detecting Anomalies in a Power Grid Digital Twin. | Tommaso Zoppi, Irene Bicchierai, Francesco Brancati, Andrea Bondavalli, Hans-Peter Schwefel |
| 2024 | PRDC | Fail-Controlled Classifiers: Do they Know when they don't Know? | Tommaso Zoppi, Fahad Ahmed KhoKhar, Andrea Ceccarelli, Leonardo Montecchi, Andrea Bondavalli |
| 2024 | SAFECOMP | Position Paper - Bringing Classifiers into Critical Systems: Are We Barking up the Wrong Tree? | Tommaso Zoppi, Fahad Ahmed KhoKhar, Andrea Ceccarelli, Andrea Bondavalli |
| 2023 | ECAI | Ensembling Uncertainty Measures to Improve Safety of Black-Box Classifiers. | Tommaso Zoppi, Andrea Ceccarelli, Andrea Bondavalli |
| 2023 | ISSRE | Intrusion detection without attack knowledge: generating out-of-distribution tabular data. | Andrea Ceccarelli, Tommaso Zoppi |
| 2023 | QRS | Anomaly Detectors for Self-Aware Edge and IoT Devices. | Tommaso Zoppi, Giovanni Merlino, Andrea Ceccarelli, Antonio Puliafito, Andrea Bondavalli |
| 2023 | SAC | Detection of Adversarial Attacks by Observing Deep Features with Structured Data Algorithms. | Tommaso Puccetti, Andrea Ceccarelli, Tommaso Zoppi, Andrea Bondavalli |
| 2021 | PRDC | Detecting Intrusions by Voting Diverse Machine Learners: Is It Really Worth? | Tommaso Zoppi, Andrea Ceccarelli, Andrea Bondavalli |
| 2021 | SAC | Quantitative comparison of supervised algorithms and feature sets for traffic sign recognition. | Muhammad Atif, Tommaso Zoppi, Mohamad Gharib, Andrea Bondavalli |
| 2021 | SAC | Understanding the properness of incorporating machine learning algorithms in safety-critical systems. | Mohamad Gharib, Tommaso Zoppi, Andrea Bondavalli |
| 2020 | DSN | Into the Unknown: Unsupervised Machine Learning Algorithms for Anomaly-Based Intrusion Detection. | Tommaso Zoppi, Andrea Ceccarelli, Andrea Bondavalli |
| 2019 | ISSRE | Evaluation of Anomaly Detection Algorithms Made Easy with RELOAD. | Tommaso Zoppi, Andrea Ceccarelli, Andrea Bondavalli |
| 2019 | SAC | Quantitative comparison of unsupervised anomaly detection algorithms for intrusion detection. | Filipe Falco, Tommaso Zoppi, Caio Barbosa Viera Silva, Anderson Santos, Baldoino Fonseca, Andrea Ceccarelli, Andrea Bondavalli |
| 2019 | SERVICES | An Initial Investigation on Sliding Windows for Anomaly-Based Intrusion Detection. | Tommaso Zoppi, Andrea Ceccarelli, Andrea Bondavalli |
| 2018 | PRDC | On Algorithms Selection for Unsupervised Anomaly Detection. | Tommaso Zoppi, Andrea Ceccarelli, Andrea Bondavalli |
| 2017 | SAC | Exploring anomaly detection in systems of systems. | Tommaso Zoppi, Andrea Ceccarelli, Andrea Bondavalli |
| 2017 | REFSQ | Towards Security Requirements: Iconicity as a Feature of an Informal Modeling Language. | Alexandr Vasenev, Dan Ionita, Tommaso Zoppi, Andrea Ceccarelli, Roel J. Wieringa |
| 2016 | SAFECOMP | Context-Awareness to Improve Anomaly Detection in Dynamic Service Oriented Architectures. | Tommaso Zoppi, Andrea Ceccarelli, Andrea Bondavalli |
| 2016 | SRDS | Challenging Anomaly Detection in Complex Dynamic Systems. | Tommaso Zoppi, Andrea Ceccarelli, Andrea Bondavalli |
| 2015 | SAFECOMP | A Multi-layer Anomaly Detector for Dynamic Service-Based Systems. | Andrea Ceccarelli, Tommaso Zoppi, Massimiliano Leone Itria, Andrea Bondavalli |
| 2014 | ISORC | A Testbed for Evaluating Anomaly Detection Monitors through Fault Injection. | Andrea Ceccarelli, Tommaso Zoppi, Andrea Bondavalli, Fabio Duchi, Giuseppe Vella |