Ontological Modelling for Archaeological Data. - Andrea D'Andrea; Giulia Marchese; Tommaso Zoppi (VAST, 2006)

A Testbed for Evaluating Anomaly Detection Monitors through Fault Injection. - Andrea Ceccarelli; Tommaso Zoppi; Andrea Bondavalli; Fabio Duchi; Giuseppe Vella (ISORC, 2014)

A Multi-layer Anomaly Detector for Dynamic Service-Based Systems. - Andrea Ceccarelli; Tommaso Zoppi; Massimiliano Leone Itria; Andrea Bondavalli (SAFECOMP, 2015)

Presenting the Proper Data to the Crisis Management Operator: A Relevance Labelling Strategy. - Tommaso Zoppi; Andrea Ceccarelli; Paolo Lollini; Andrea Bondavalli; Francesco Lo Piccolo; Gabriele Giunta; Vito Morreale (HASE, 2016)

Context-Awareness to Improve Anomaly Detection in Dynamic Service Oriented Architectures. - Tommaso Zoppi; Andrea Ceccarelli; Andrea Bondavalli (SAFECOMP, 2016)

Challenging Anomaly Detection in Complex Dynamic Systems. - Tommaso Zoppi; Andrea Ceccarelli; Andrea Bondavalli (SRDS, 2016)

On the impact of emergent properties on SoS security. - Marco Mori; Andrea Ceccarelli; Tommaso Zoppi; Andrea Bondavalli (SoSE, 2016)

Towards Security Requirements: Iconicity as a Feature of an Informal Modeling Language. - Alexandr Vasenev; Dan Ionita; Tommaso Zoppi; Andrea Ceccarelli; Roel J. Wieringa (REFSQ Workshops, 2017)

Exploring anomaly detection in systems of systems. - Tommaso Zoppi; Andrea Ceccarelli; Andrea Bondavalli (SAC, 2017)

A Modeling Framework to Support Resilient Evolution Planning of Smart Grids. - Tommaso Zoppi; Sandford Bessler; Andrea Ceccarelli; Edward Lambert; Eng Tseng Lau; Alexandr Vasenev (SmartGIFT, 2017)

A Tool for Evolutionary Threat Analysis of Smart Grids. - Tommaso Zoppi; Andrea Ceccarelli; Marco Mori (SmartGIFT, 2017)

On Algorithms Selection for Unsupervised Anomaly Detection. - Tommaso Zoppi; Andrea Ceccarelli; Andrea Bondavalli (PRDC, 2018)

Labelling relevant events to support the crisis management operator. - Tommaso Zoppi; Andrea Ceccarelli; Francesco Lo Piccolo; Paolo Lollini; Gabriele Giunta; Vito Morreale; Andrea Bondavalli (J. Softw. Evol. Process., 2018)

Evaluation of Anomaly Detection Algorithms Made Easy with RELOAD. - Tommaso Zoppi; Andrea Ceccarelli; Andrea Bondavalli (ISSRE, 2019)

Practical Experience Report: Implementation, Verification and Validation of a Safe and Secure Communication Protocol for the Railway Domain. - Duccio Bertieri; Tommaso Zoppi; Innocenzo Mungiello; Andrea Ceccarelli; Mario Barbareschi; Andrea Bondavalli (LADC, 2019)

Quantitative comparison of unsupervised anomaly detection algorithms for intrusion detection. - Filipe Falcão; Tommaso Zoppi; Caio Barbosa Viera Silva; Anderson Santos 002; Baldoino Fonseca; Andrea Ceccarelli; Andrea Bondavalli (SAC, 2019)

An Initial Investigation on Sliding Windows for Anomaly-Based Intrusion Detection. - Tommaso Zoppi; Andrea Ceccarelli; Andrea Bondavalli (SERVICES, 2019)

Threat Analysis in Systems-of-Systems: An Emergence-Oriented Approach. - Andrea Ceccarelli; Tommaso Zoppi; Alexandr Vasenev; Marco Mori; Dan Ionita; Lorena Montoya; Andrea Bondavalli (ACM Trans. Cyber Phys. Syst., 2019)

Into the Unknown: Unsupervised Machine Learning Algorithms for Anomaly-Based Intrusion Detection. - Tommaso Zoppi; Andrea Ceccarelli; Andrea Bondavalli (DSN (Supplements), 2020)

On the educated selection of unsupervised algorithms via attacks and anomaly classes. - Tommaso Zoppi; Andrea Ceccarelli; Lorenzo Salani; Andrea Bondavalli (J. Inf. Secur. Appl., 2020)

Spoofing Detectability as a Property of Biometric Characteristics. - Tommaso Zoppi; Enrico Schiavone; Irene Bicchierai; Francesco Brancati; Andrea Bondavalli (ITASEC, 2021)

Feature Rankers to Predict Classification Performance of Unsupervised Intrusion Detectors. - Tommaso Zoppi; Andrea Ceccarelli; Andrea Bondavalli (LADC, 2021)

Detecting Intrusions by Voting Diverse Machine Learners: Is It Really Worth? - Tommaso Zoppi; Andrea Ceccarelli; Andrea Bondavalli (PRDC, 2021)

Quantitative comparison of supervised algorithms and feature sets for traffic sign recognition. - Muhammad Atif; Tommaso Zoppi; Mohamad Gharib; Andrea Bondavalli (SAC, 2021)

Understanding the properness of incorporating machine learning algorithms in safety-critical systems. - Mohamad Gharib; Tommaso Zoppi; Andrea Bondavalli (SAC, 2021)

Detect Adversarial Attacks Against Deep Neural Networks With GPU Monitoring. - Tommaso Zoppi; Andrea Ceccarelli (IEEE Access, 2021)

Unsupervised Algorithms to Detect Zero-Day Attacks: Strategy and Application. - Tommaso Zoppi; Andrea Ceccarelli; Andrea Bondavalli (IEEE Access, 2021)

Development and validation of a safe communication protocol compliant to railway standards. - Duccio Bertieri; Andrea Ceccarelli; Tommaso Zoppi; Innocenzo Mungiello; Mario Barbareschi; Andrea Bondavalli (J. Braz. Comput. Soc., 2021)

Prepare for trouble and make it double! Supervised - Unsupervised stacking for anomaly-based intrusion detection. - Tommaso Zoppi; Andrea Ceccarelli (J. Netw. Comput. Appl., 2021)

Meta-Learning to Improve Unsupervised Intrusion Detection in Cyber-Physical Systems. - Tommaso Zoppi; Mohamad Gharib; Muhammad Atif; Andrea Bondavalli (ACM Trans. Cyber Phys. Syst., 2021)

Unsupervised Anomaly Detectors to Detect Intrusions in the Current Threat Landscape. - Tommaso Zoppi; Andrea Ceccarelli; Tommaso Capecchi; Andrea Bondavalli (Trans. Data Sci., 2021)

MADneSs: A Multi-Layer Anomaly Detection Framework for Complex Dynamic Systems. - Tommaso Zoppi; Andrea Ceccarelli; Andrea Bondavalli (IEEE Trans. Dependable Secur. Comput., 2021)

Towards a General Model for Intrusion Detection: An Exploratory Study. - Tommaso Zoppi; Andrea Ceccarelli; Andrea Bondavalli (PKDD/ECML Workshops (2), 2022)

Prepare for Trouble and Make it Double. Supervised and Unsupervised Stacking for AnomalyBased Intrusion Detection. - Tommaso Zoppi; Andrea Ceccarelli (CoRR, 2022)

Towards Enhancing Traffic Sign Recognition through Sliding Windows. - Muhammad Atif; Tommaso Zoppi; Mohamad Gharib; Andrea Bondavalli (Sensors, 2022)

On the Properness of Incorporating Binary Classification Machine Learning Algorithms Into Safety-Critical Systems. - Mohamad Gharib; Tommaso Zoppi; Andrea Bondavalli (IEEE Trans. Emerg. Top. Comput., 2022)

Ensembling Uncertainty Measures to Improve Safety of Black-Box Classifiers. - Tommaso Zoppi; Andrea Ceccarelli; Andrea Bondavalli (ECAI, 2023)

Intrusion detection without attack knowledge: generating out-of-distribution tabular data. - Andrea Ceccarelli; Tommaso Zoppi (ISSRE, 2023)

Anomaly Detectors for Self-Aware Edge and IoT Devices. - Tommaso Zoppi; Giovanni Merlino; Andrea Ceccarelli; Antonio Puliafito; Andrea Bondavalli (QRS, 2023)

Detection of Adversarial Attacks by Observing Deep Features with Structured Data Algorithms. - Tommaso Puccetti; Andrea Ceccarelli; Tommaso Zoppi; Andrea Bondavalli (SAC, 2023)

Tolerate Failures of the Visual Camera With Robust Image Classifiers. - Muhammad Atif; Andrea Ceccarelli; Tommaso Zoppi; Andrea Bondavalli (IEEE Access, 2023)

On the Efficacy of Metrics to Describe Adversarial Attacks. - Tommaso Puccetti; Tommaso Zoppi; Andrea Ceccarelli (CoRR, 2023)

Which algorithm can detect unknown attacks? Comparison of supervised, unsupervised and meta-learning algorithms for intrusion detection. - Tommaso Zoppi; Andrea Ceccarelli; Tommaso Puccetti; Andrea Bondavalli (Comput. Secur., 2023)

Safe Maintenance of Railways using COTS Mobile Devices: The Remote Worker Dashboard. - Tommaso Zoppi; Innocenzo Mungiello; Andrea Ceccarelli; Alberto Cirillo; Lorenzo Sarti; Lorenzo Esposito; Giuseppe Scaglione; Sergio Repetto; Andrea Bondavalli (ACM Trans. Cyber Phys. Syst., 2023)

On attacks (dis)similarities to test adversarial defense: can we reduce the attack set? - Tommaso Puccetti; Tommaso Zoppi; Andrea Ceccarelli (ITASEC, 2024)

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 (PRDC, 2024)

Fail-Controlled Classifiers: Do they Know when they don't Know? - Tommaso Zoppi; Fahad Ahmed KhoKhar; Andrea Ceccarelli; Leonardo Montecchi; Andrea Bondavalli (PRDC, 2024)

Position Paper - Bringing Classifiers into Critical Systems: Are We Barking up the Wrong Tree? - Tommaso Zoppi; Fahad Ahmed KhoKhar; Andrea Ceccarelli; Andrea Bondavalli (SAFECOMP (Workshops), 2024)

ROSpace: Intrusion Detection Dataset for a ROS2-Based Cyber-Physical System. - Tommaso Puccetti; Simone Nardi; Cosimo Cinquilli; Tommaso Zoppi; Andrea Ceccarelli (CoRR, 2024)

Fast Abstracts and Student Forum Proceedings - EDCC 2024 - 19th European Dependable Computing Conference. - Simona Bernardi 001; Tommaso Zoppi (CoRR, 2024)

Anomaly-based error and intrusion detection in tabular data: No DNN outperforms tree-based classifiers. - Tommaso Zoppi; Stefano Gazzini; Andrea Ceccarelli (Future Gener. Comput. Syst., 2024)

System-Awareness: An Enabling Condition to Design and Deploy Anomaly Detectors. - Muhammad Atif; Tommaso Zoppi; Andrea Bondavalli (ICSA Companion, 2025)

Bringing Machine Learning Classifiers Into Critical Cyber-Physical Systems: A Matter of Design. - Burcu Sayin; Tommaso Zoppi; Nicolò Marchini; Fahad Ahmed KhoKhar; Andrea Passerini (IEEE Access, 2025)

Confidence ensembles: Tabular data classifiers on steroids. - Tommaso Zoppi; Peter Popov (Inf. Fusion, 2025)

A Strategy for Predicting the Performance of Supervised and Unsupervised Tabular Data Classifiers. - Tommaso Zoppi; Andrea Ceccarelli; Andrea Bondavalli (Data Sci. Eng., 2025)