Rule Learning with Probabilistic Smoothing. - Gianni Costa; Massimo Guarascio 001; Giuseppe Manco 001; Riccardo Ortale; Ettore Ritacco (DaWaK, 2009)

High Quality True-Positive Prediction for Fiscal Fraud Detection. - Stefano Basta; Fabio Fassetti; Massimo Guarascio 001; Giuseppe Manco 001; Fosca Giannotti; Dino Pedreschi; Laura Spinsanti; Gianfilippo Papi; Stefano Pisani (ICDM Workshops, 2009)

A Hierarchical Rule-based Framework for Accurate Classification in Imprecise Domains. - Gianni Costa; Massimo Guarascio 001; Giuseppe Manco 001; Riccardo Ortale; Ettore Ritacco (SEBD, 2009)

A Block Mixture Model for Pattern Discovery in Preference Data. - Nicola Barbieri; Massimo Guarascio 001; Giuseppe Manco 001 (ICDM Workshops, 2010)

An Empirical Comparison of Collaborative Filtering Approaches on Netflix Data. - Nicola Barbieri; Massimo Guarascio 001; Ettore Ritacco (IIR, 2010)

Mining models of exceptional objects through rule learning. - Gianni Costa; Fabio Fassetti; Massimo Guarascio 001; Giuseppe Manco 001; Riccardo Ortale (SAC, 2010)

ProMetheuS: A Suite for Process Mining Applications. - Lucantonio Ghionna; Luigi Granata; Gianluigi Greco; Massimo Guarascio 001 (CAiSE Forum, 2012)

Discovering Context-Aware Models for Predicting Business Process Performances. - Francesco Folino; Massimo Guarascio 001; Luigi Pontieri (OTM Conferences (1), 2012)

Context-Aware Predictions on Business Processes: An Ensemble-Based Solution. - Francesco Folino; Massimo Guarascio 001; Luigi Pontieri (NFMCP, 2012)

A Data-adaptive Trace Abstraction Approach to the Prediction of Business Process Performances. - Antonio Bevacqua; Marco Carnuccio; Francesco Folino; Massimo Guarascio 001; Luigi Pontieri (ICEIS (1), 2013)

A Data-Driven Prediction Framework for Analyzing and Monitoring Business Process Performances. - Antonio Bevacqua; Marco Carnuccio; Francesco Folino; Massimo Guarascio 001; Luigi Pontieri (ICEIS, 2013)

Discovering High-Level Performance Models for Ticket Resolution Processes. - Francesco Folino; Massimo Guarascio 001; Luigi Pontieri (OTM Conferences, 2013)

Adaptive Trace Abstraction Approach for Predicting Business Process Performances. - Antonio Bevacqua; Marco Carnuccio; Francesco Folino; Massimo Guarascio 001; Luigi Pontieri (SEBD, 2013)

Mining Predictive Process Models out of Low-level Multidimensional Logs. - Francesco Folino; Massimo Guarascio 001; Luigi Pontieri (CAiSE, 2014)

A Framework for the Discovery of Predictive Fix-time Models. - Francesco Folino; Massimo Guarascio 001; Luigi Pontieri (ICEIS (1), 2014)

An Approach to the Discovery of Accurate and Expressive Fix-Time Prediction Models. - Francesco Folino; Massimo Guarascio 001; Luigi Pontieri (ICEIS (Revised Selected Papers), 2014)

Mining Multi-variant Process Models from Low-Level Logs. - Francesco Folino; Massimo Guarascio 001; Luigi Pontieri (BIS, 2015)

A Prediction Framework for Proactively Monitoring Aggregate Process-Performance Indicators. - Francesco Folino; Massimo Guarascio 001; Luigi Pontieri (EDOC, 2015)

On the Discovery of Explainable and Accurate Behavioral Models for Complex Lowly-structured Business Processes. - Francesco Folino; Massimo Guarascio 001; Luigi Pontieri (ICEIS (1), 2015)

A Multi-view Learning Approach to the Discovery of Deviant Process Instances. - Alfredo Cuzzocrea; Francesco Folino; Massimo Guarascio 001; Luigi Pontieri (OTM Conferences, 2015)

A Cloud-Based Prediction Framework for Analyzing Business Process Performances. - Eugenio Cesario; Francesco Folino; Massimo Guarascio 001; Luigi Pontieri (CD-ARES, 2016)

A multi-view multi-dimensional ensemble learning approach to mining business process deviances. - Alfredo Cuzzocrea; Francesco Folino; Massimo Guarascio 001; Luigi Pontieri (IJCNN, 2016)

Profiling Human Behavior Through Multidimensional Latent Factor Modeling. - Massimo Guarascio 001; Francesco Sergio Pisani; Ettore Ritacco; Pietro Sabatino (NFMCP@PKDD/ECML, 2016)

A Robust and Versatile Multi-View Learning Framework for the Detection of Deviant Business Process Instances. - Alfredo Cuzzocrea; Francesco Folino; Massimo Guarascio 001; Luigi Pontieri (Int. J. Cooperative Inf. Syst., 2016)

Extensions, Analysis and Experimental Assessment of a Probabilistic Ensemble-learning Framework for Detecting Deviances in Business Process Instances. - Alfredo Cuzzocrea; Francesco Folino; Massimo Guarascio 001; Luigi Pontieri (ICEIS (1), 2017)

Experimenting and Assessing a Probabilistic Business Process Deviance Mining Framework Based on Ensemble Learning. - Alfredo Cuzzocrea; Francesco Folino; Massimo Guarascio 001; Luigi Pontieri (ICEIS (Revised Selected Papers), 2017)

Integrating a Framework for Discovering Alternative App Stores in a Mobile App Monitoring Platform. - Massimo Guarascio 001; Ettore Ritacco; Daniele Biondo; Rocco Mammoliti; Alessandra Toma (NFMCP@PKDD/ECML, 2017)

A descriptive clustering approach to the analysis of quantitative business-process deviances. - Francesco Folino; Massimo Guarascio 001; Luigi Pontieri (SAC, 2017)

A Predictive Learning Framework for Monitoring Aggregated Performance Indicators over Business Process Events. - Alfredo Cuzzocrea; Francesco Folino; Massimo Guarascio 001; Luigi Pontieri (IDEAS, 2018)

Deviance-Aware Discovery of High-Quality Process Models. - Alfredo Cuzzocrea; Francesco Folino; Massimo Guarascio 001; Luigi Pontieri (Int. J. Artif. Intell. Tools, 2018)

Learning Effective Neural Nets for Outcome Prediction from Partially Labelled Log Data. - Francesco Folino; Gianluigi Folino; Massimo Guarascio 001; Luigi Pontieri (ICTAI, 2019)

A Deep Learning based architecture for rainfall estimation integrating heterogeneous data sources. - Gianluigi Folino; Massimo Guarascio 001; Francesco Chiaravalloti; Salvatore Gabriele (IJCNN, 2019)

Deep Sequential Modeling for Recommendation. - Giuseppe Manco 001; Ettore Ritacco; Noveen Sachdeva; Massimo Guarascio 001 (SEBD, 2019)

Exploiting fractal dimension and a distributed evolutionary approach to classify data streams with concept drifts. - Gianluigi Folino; Massimo Guarascio 001; Giuseppe Papuzzo (Appl. Soft Comput., 2019)

Predictive monitoring of temporally-aggregated performance indicators of business processes against low-level streaming events. - Alfredo Cuzzocrea; Francesco Folino; Massimo Guarascio 001; Luigi Pontieri (Inf. Syst., 2019)

Deep Learning on Big Data. - Gianluigi Folino; Massimo Guarascio 001; Maryam Amir Haeri (Encyclopedia of Big Data Technologies, 2019)

Network Topology. - Giuseppe Manco 001; Ettore Ritacco; Massimo Guarascio 001 (Encyclopedia of Bioinformatics and Computational Biology (1), 2019)

Knowledge Discovery in Databases. - Massimo Guarascio 001; Giuseppe Manco 001; Ettore Ritacco (Encyclopedia of Bioinformatics and Computational Biology (1), 2019)

Deep Learning. - Massimo Guarascio 001; Giuseppe Manco 001; Ettore Ritacco (Encyclopedia of Bioinformatics and Computational Biology (1), 2019)

Network Models. - Massimo Guarascio 001; Giuseppe Manco 001; Ettore Ritacco (Encyclopedia of Bioinformatics and Computational Biology (1), 2019)

Deep Autoencoder Ensembles for Anomaly Detection on Blockchain. - Francesco Scicchitano; Angelica Liguori; Massimo Guarascio 001; Ettore Ritacco; Giuseppe Manco 001 (ISMIS, 2020)

A Deep Learning Approach for Detecting Security Attacks on Blockchain. - Francesco Scicchitano; Angelica Liguori; Massimo Guarascio 001; Ettore Ritacco; Giuseppe Manco 001 (ITASEC, 2020)

A Multi-view Ensemble of Deep Models for the Detection of Deviant Process Instances. - Francesco Folino; Gianluigi Folino; Massimo Guarascio 001; Luigi Pontieri (PKDD/ECML Workshops, 2020)

Exploiting Temporal Convolution for Activity Prediction in Process Analytics. - Francesco Folino; Massimo Guarascio 001; Angelica Liguori; Giuseppe Manco 001; Luigi Pontieri; Ettore Ritacco (PKDD/ECML Workshops, 2020)

Using Deep Learning and Data Integration for Accurate Rainfall Estimates. - Gianluigi Folino; Massimo Guarascio 001; Francesco Chiaravalloti; Salvatore Gabriele (ERCIM News, 2020)

Sanitization of Images Containing Stegomalware via Machine Learning Approaches. - Marco Zuppelli; Giuseppe Manco 001; Luca Caviglione; Massimo Guarascio 001 (ITASEC, 2021)

Discovering accurate deep learning based predictive models for automatic customer support ticket classification. - Paolo Zicari; Gianluigi Folino; Massimo Guarascio 001; Luigi Pontieri (SAC, 2021)

On learning effective ensembles of deep neural networks for intrusion detection. - Francesco Folino; Gianluigi Folino; Massimo Guarascio 001; Francesco Sergio Pisani; Luigi Pontieri (Inf. Fusion, 2021)

Revealing MageCart-like Threats in Favicons via Artificial Intelligence. - Massimo Guarascio 001; Marco Zuppelli; Nunziato Cassavia; Luca Caviglione; Giuseppe Manco 001 (ARES, 2022)

A Loosely-coupled Neural-symbolic approach to Compliance of Electric Panels. - Vito Barbara; Dimitri Buelli; Massimo Guarascio 001; Stefano Ierace; Salvatore Iiritano; Giovanni Laboccetta; Nicola Leone; Giuseppe Manco 001; Valerio Pesenti; Alessandro Quarta; Francesco Ricca; Ettore Ritacco (CILC, 2022)

Generative Methods for Out-of-distribution Prediction and Applications for Threat Detection and Analysis: A Short Review. - Erica Coppolillo; Angelica Liguori; Massimo Guarascio 001; Francesco Sergio Pisani; Giuseppe Manco 001 (CyberSec4Europe, 2022)

Detecting DoS and DDoS Attacks through Sparse U-Net-like Autoencoders. - Nunziato Cassavia; Francesco Folino; Massimo Guarascio 001 (ICTAI, 2022)

Ensembling Sparse Autoencoders for Network Covert Channel Detection in IoT Ecosystems. - Nunziato Cassavia; Luca Caviglione; Massimo Guarascio 001; Angelica Liguori; Marco Zuppelli (ISMIS, 2022)

Combining Active Learning and Fast DNN Ensembles for Process Deviance Discovery. - Francesco Folino; Gianluigi Folino; Massimo Guarascio 001; Luigi Pontieri (ISMIS, 2022)

Learning and Explanation of Extreme Multi-label Deep Classification Models for Media Content. - Marco Minici; Francesco Sergio Pisani; Massimo Guarascio 001; Erika De Francesco; Pasquale Lambardi (ISMIS, 2022)

Detection of Network Covert Channels in IoT Ecosystems Using Machine Learning. - Massimo Guarascio 001; Marco Zuppelli; Nunziato Cassavia; Giuseppe Manco 001; Luca Caviglione (ITASEC, 2022)

Federated Learning for the Efficient Detection of Steganographic Threats Hidden in Image Icons. - Nunziato Cassavia; Luca Caviglione; Massimo Guarascio 001; Angelica Liguori; Giuseppe Surace; Marco Zuppelli (PerSOM, 2022)

Towards Extreme Multi-Label Classification of Multimedia Content. - Marco Minici; Francesco Sergio Pisani; Massimo Guarascio 001; Giuseppe Manco 001 (SEBD, 2022)

Semi-Supervised Discovery of DNN-Based Outcome Predictors from Scarcely-Labeled Process Logs. - Francesco Folino; Gianluigi Folino; Massimo Guarascio 001; Luigi Pontieri (Bus. Inf. Syst. Eng., 2022)

Combining deep ensemble learning and explanation for intelligent ticket management. - Paolo Zicari; Gianluigi Folino; Massimo Guarascio 001; Luigi Pontieri (Expert Syst. Appl., 2022)

Boosting Cyber-Threat Intelligence via Collaborative Intrusion Detection. - Massimo Guarascio 001; Nunziato Cassavia; Francesco Sergio Pisani; Giuseppe Manco 001 (Future Gener. Comput. Syst., 2022)

Detection of Steganographic Threats Targeting Digital Images in Heterogeneous Ecosystems Through Machine Learning. - Nunziato Cassavia; Luca Caviglione; Massimo Guarascio 001; Giuseppe Manco 001; Marco Zuppelli (J. Wirel. Mob. Networks Ubiquitous Comput. Dependable Appl., 2022)

A Machine Learning Approach for Rainfall Estimation Integrating Heterogeneous Data Sources. - Massimo Guarascio 001; Gianluigi Folino; Francesco Chiaravalloti; Salvatore Gabriele; Antonio Procopio; Pietro Sabatino (IEEE Trans. Geosci. Remote. Sens., 2022)

Occupancy Prediction in Multi-Occupant IoT Environments Leveraging Federated Learning. - Irfanullah Khan; Flávia Coimbra Delicato; Emilio Greco; Massimo Guarascio 001; Antonio Guerrieri; Giandomenico Spezzano (DASC/PiCom/CBDCom/CyberSciTech, 2023)

Learning Deep Fake-News Detectors from Scarcely-Labelled News Corpora. - Paolo Zicari; Massimo Guarascio 001; Luigi Pontieri; Gianluigi Folino (ICEIS (1), 2023)

Exploiting Deep Learning and Explanation Methods for Movie Tag Prediction. - Erica Coppolillo; Massimo Guarascio 001; Marco Minici; Francesco Sergio Pisani (IDEAS, 2023)

Fighting Misinformation, Radicalization and Bias in Social Media. - Erica Coppolillo; Carmela Comito; Marco Minici; Ettore Ritacco; Gianluigi Folino; Francesco Sergio Pisani; Massimo Guarascio 001; Giuseppe Manco 001 (Ital-IA, 2023)

Using AI to face covert attacks in IoT and softwarized scenarios: challenges and opportunities. - Angelica Liguori; Simone Mungari; Marco Zuppelli; Carmela Comito; Enrico Cambiaso; Matteo Repetto; Massimo Guarascio 001; Luca Caviglione; Giuseppe Manco 001 (Ital-IA, 2023)

Towards Self-Supervised Cross-Domain Fake News Detection. - Carmela Comito; Francesco Sergio Pisani; Erica Coppolillo; Angelica Liguori; Massimo Guarascio 001; Giuseppe Manco 001 (ITASEC, 2023)

Explainable Process Deviance Discovery with Data-Efficient Deep Learning. - Francesco Folino; Gianluigi Folino; Massimo Guarascio 001; Luigi Pontieri (NUMTA (1), 2023)

ORISHA: Improving Threat Detection through Orchestrated Information Sharing (Discussion Paper). - Luca Caviglione; Carmela Comito; Massimo Guarascio 001; Giuseppe Manco 001; Francesco Sergio Pisani; Marco Zuppelli (SEBD, 2023)

An Explainable Deep Ensemble Framework for Intelligent Ticket Management. - Gianluigi Folino; Massimo Guarascio 001; Luigi Pontieri; Paolo Zicari (ERCIM News, 2023)

Learning ensembles of deep neural networks for extreme rainfall event detection. - Gianluigi Folino; Massimo Guarascio 001; Francesco Chiaravalloti (Neural Comput. Appl., 2023)

Neuro-Symbolic AI for Compliance Checking of Electrical Control Panels. - Vito Barbara; Massimo Guarascio 001; Nicola Leone; Giuseppe Manco 001; Alessandro Quarta; Francesco Ricca; Ettore Ritacco (Theory Pract. Log. Program., 2023)

A Deep Anomaly Detection System for IoT-Based Smart Buildings. - Simona Cicero; Massimo Guarascio 001; Antonio Guerrieri; Simone Mungari (Sensors, 2023)

A federated approach for detecting data hidden in icons of mobile applications delivered via web and multiple stores. - Nunziato Cassavia; Luca Caviglione; Massimo Guarascio 001; Angelica Liguori; Giuseppe Manco 001; Marco Zuppelli (Soc. Netw. Anal. Min., 2023)

No Country for Leaking Containers: Detecting Exfiltration of Secrets Through AI and Syscalls. - Marco Zuppelli; Massimo Guarascio 001; Luca Caviglione; Angelica Liguori (ARES, 2024)

A Deep Neural Framework for Fault Detection in IoT-Based Sensor Networks. - Simona Cicero; Massimo Guarascio 001; Antonio Guerrieri; Simone Mungari; Andrea Vinci (ASONAM (Workshops), 2024)

Beyond the Horizon: Using Mixture of Experts for Domain Agnostic Fake News Detection. - Carmela Comito; Massimo Guarascio 001; Angelica Liguori; Giuseppe Manco 001; Francesco Sergio Pisani (DS (2), 2024)

A Few to Unveil Them All: Leveraging Mixture of Experts on Minimal Data for Detecting Covert Channels in Containerized Cloud Infrastructures. - Luca Caviglione; Massimo Guarascio 001; Francesco Sergio Pisani; Marco Zuppelli (EuroS&P Workshops, 2024)

Erasing the Shadow: Sanitization of Images with Malicious Payloads Using Deep Autoencoders. - Angelica Liguori; Marco Zuppelli; Daniela Gallo; Massimo Guarascio 001; Luca Caviglione (ISMIS, 2024)

Dawn of LLM4Cyber: Current Solutions, Challenges, and New Perspectives in Harnessing LLMs for Cybersecurity. - Luca Caviglione; Carmela Comito; Erica Coppolillo; Daniela Gallo; Massimo Guarascio 001; Angelica Liguori; Giuseppe Manco 001; Marco Minici; Simone Mungari; Francesco Sergio Pisani; Ettore Ritacco; Antonino Rullo; et al. (Ital-IA, 2024)

Mitigation of Covert Communications in MQTT Topics Through Small Language Models. - Camilla Cespi Polisiani; Marco Zuppelli; Maria Carla Calzarossa; Luca Caviglione; Massimo Guarascio 001 (MASCOTS, 2024)

Boosting MATE Security through Small Language Models. - Luca Caviglione; Gianluigi Folino; Massimo Guarascio 001; Paolo Zicari (ERCIM News, 2024)

Towards Data- and Compute-Efficient Fake-News Detection: An Approach Combining Active Learning and Pre-Trained Language Models. - Francesco Folino; Gianluigi Folino; Massimo Guarascio 001; Luigi Pontieri; Paolo Zicari (SN Comput. Sci., 2024)

Learning autoencoder ensembles for detecting malware hidden communications in IoT ecosystems. - Nunziato Cassavia; Luca Caviglione; Massimo Guarascio 001; Angelica Liguori; Marco Zuppelli (J. Intell. Inf. Syst., 2024)

Data- & compute-efficient deviance mining via active learning and fast ensembles. - Francesco Folino; Gianluigi Folino; Massimo Guarascio 001; Luigi Pontieri (J. Intell. Inf. Syst., 2024)

Movie tag prediction: An extreme multi-label multi-modal transformer-based solution with explanation. - Massimo Guarascio 001; Marco Minici; Francesco Sergio Pisani; Erika De Francesco; Pasquale Lambardi (J. Intell. Inf. Syst., 2024)

Detecting DDoS Attacks in Microservice Architectures via AI-Based Agents. - Giacomo Benedetti; Luca Caviglione; Alberto Falcone; Massimo Ficco; Massimo Guarascio 001; Antonio Guerriero (ICCSA (Workshops 4), 2025)

Improving MQTT Security Through the Generation of Malicious Test Cases. - Camilla Cespi Polisiani; Maria Carla Calzarossa; Marco Zuppelli; Luca Caviglione; Massimo Guarascio 001 (ITASEC/SERICS, 2025)

Discovering ensembles of small language models out of scarcely labelled data for fake news detection. - Gianluigi Folino; Massimo Guarascio 001; Luigi Pontieri; Paolo Zicari (Appl. Soft Comput., 2025)

The force of few: boosting deviance detection in data scarcity scenarios through self-supervised learning and pattern-based encoding. - Francesco Folino; Gianluigi Folino; Massimo Guarascio 001; Luigi Pontieri (Soft Comput., 2025)

Breaking domain barriers: mixture of experts for cross-domain fake news detection. - Angelica Liguori; Francesco Sergio Pisani; Carmela Comito; Massimo Guarascio 001; Giuseppe Manco 001 (Mach. Learn., 2025)

M3DUSA: A Modular Multi-Modal Deep fUSion Architecture for fake news detection on social media. - Liliana Martirano; Carmela Comito; Massimo Guarascio 001; Francesco Sergio Pisani; Paolo Zicari (Soc. Netw. Anal. Min., 2025)