Massimo Guarascio

Publication Activity (10 Years)

Years Active: 2009-2023
Publications (10 Years): 38

Top Topics

Intrusion Detection

Business Process

Integrating Heterogeneous

Top Venues

Publications

Gianluigi Folino, Massimo Guarascio, Francesco Chiaravalloti
Learning ensembles of deep neural networks for extreme rainfall event detection. Neural Comput. Appl. 35 (14) (2023)
Massimo Guarascio, Marco Zuppelli, Nunziato Cassavia, Luca Caviglione, Giuseppe Manco
Revealing MageCart-like Threats in Favicons via Artificial Intelligence. ARES (2022)
Vito Barbara, Dimitri Buelli, Massimo Guarascio, Stefano Ierace, Salvatore Iiritano, Giovanni Laboccetta, Nicola Leone, Giuseppe Manco, Valerio Pesenti, Alessandro Quarta, Francesco Ricca, Ettore Ritacco
A Loosely-coupled Neural-symbolic approach to Compliance of Electric Panels. CILC (2022)
Nunziato Cassavia, Luca Caviglione, Massimo Guarascio, Angelica Liguori, Marco Zuppelli
Ensembling Sparse Autoencoders for Network Covert Channel Detection in IoT Ecosystems. ISMIS (2022)
Massimo Guarascio, Gianluigi Folino, Francesco Chiaravalloti, Salvatore Gabriele, Antonio Procopio, Pietro Sabatino
A Machine Learning Approach for Rainfall Estimation Integrating Heterogeneous Data Sources. IEEE Trans. Geosci. Remote. Sens. 60 (2022)
Nunziato Cassavia, Francesco Folino, Massimo Guarascio
Detecting DoS and DDoS Attacks through Sparse U-Net-like Autoencoders. ICTAI (2022)
Marco Minici, Francesco Sergio Pisani, Massimo Guarascio, Erika De Francesco, Pasquale Lambardi
Learning and Explanation of Extreme Multi-label Deep Classification Models for Media Content. ISMIS (2022)
Francesco Folino, Gianluigi Folino, Massimo Guarascio, Luigi Pontieri
Combining Active Learning and Fast DNN Ensembles for Process Deviance Discovery. ISMIS (2022)
Paolo Zicari, Gianluigi Folino, Massimo Guarascio, Luigi Pontieri
Combining deep ensemble learning and explanation for intelligent ticket management. Expert Syst. Appl. 206 (2022)
Francesco Folino, Gianluigi Folino, Massimo Guarascio, Luigi Pontieri
Semi-Supervised Discovery of DNN-Based Outcome Predictors from Scarcely-Labeled Process Logs. Bus. Inf. Syst. Eng. 64 (6) (2022)
Massimo Guarascio, Nunziato Cassavia, Francesco Sergio Pisani, Giuseppe Manco
Boosting Cyber-Threat Intelligence via Collaborative Intrusion Detection. Future Gener. Comput. Syst. 135 (2022)
Marco Minici, Francesco Sergio Pisani, Massimo Guarascio, Giuseppe Manco
Towards Extreme Multi-Label Classification of Multimedia Content. SEBD (2022)
Massimo Guarascio, Marco Zuppelli, Nunziato Cassavia, Giuseppe Manco, Luca Caviglione
Detection of Network Covert Channels in IoT Ecosystems Using Machine Learning. ITASEC (2022)
Nunziato Cassavia, Luca Caviglione, Massimo Guarascio, Angelica Liguori, Giuseppe Surace, Marco Zuppelli
Federated Learning for the Efficient Detection of Steganographic Threats Hidden in Image Icons. PerSOM (2022)
Paolo Zicari, Gianluigi Folino, Massimo Guarascio, Luigi Pontieri
Discovering accurate deep learning based predictive models for automatic customer support ticket classification. SAC (2021)
Marco Zuppelli, Giuseppe Manco, Luca Caviglione, Massimo Guarascio
Sanitization of Images Containing Stegomalware via Machine Learning Approaches. ITASEC (2021)
Francesco Folino, Gianluigi Folino, Massimo Guarascio, Francesco Sergio Pisani, Luigi Pontieri
On learning effective ensembles of deep neural networks for intrusion detection. Inf. Fusion 72 (2021)
Francesco Folino, Massimo Guarascio, Angelica Liguori, Giuseppe Manco, Luigi Pontieri, Ettore Ritacco
Exploiting Temporal Convolution for Activity Prediction in Process Analytics. PKDD/ECML Workshops (2020)
Francesco Scicchitano, Angelica Liguori, Massimo Guarascio, Ettore Ritacco, Giuseppe Manco
Deep Autoencoder Ensembles for Anomaly Detection on Blockchain. ISMIS (2020)
Francesco Folino, Gianluigi Folino, Massimo Guarascio, Luigi Pontieri
A Multi-view Ensemble of Deep Models for the Detection of Deviant Process Instances. PKDD/ECML Workshops (2020)
Francesco Scicchitano, Angelica Liguori, Massimo Guarascio, Ettore Ritacco, Giuseppe Manco
A Deep Learning Approach for Detecting Security Attacks on Blockchain. ITASEC (2020)
Gianluigi Folino, Massimo Guarascio, Francesco Chiaravalloti, Salvatore Gabriele
Using Deep Learning and Data Integration for Accurate Rainfall Estimates. ERCIM News 2020 (122) (2020)
Gianluigi Folino, Massimo Guarascio, Francesco Chiaravalloti, Salvatore Gabriele
A Deep Learning based architecture for rainfall estimation integrating heterogeneous data sources. IJCNN (2019)
Alfredo Cuzzocrea, Francesco Folino, Massimo Guarascio, Luigi Pontieri
Predictive monitoring of temporally-aggregated performance indicators of business processes against low-level streaming events. Inf. Syst. 81 (2019)
Gianluigi Folino, Massimo Guarascio, Giuseppe Papuzzo
Exploiting fractal dimension and a distributed evolutionary approach to classify data streams with concept drifts. Appl. Soft Comput. 75 (2019)
Giuseppe Manco, Ettore Ritacco, Noveen Sachdeva, Massimo Guarascio
Deep Sequential Modeling for Recommendation. SEBD (2019)
Francesco Folino, Gianluigi Folino, Massimo Guarascio, Luigi Pontieri
Learning Effective Neural Nets for Outcome Prediction from Partially Labelled Log Data. ICTAI (2019)
Alfredo Cuzzocrea, Francesco Folino, Massimo Guarascio, Luigi Pontieri
A Predictive Learning Framework for Monitoring Aggregated Performance Indicators over Business Process Events. IDEAS (2018)
Alfredo Cuzzocrea, Francesco Folino, Massimo Guarascio, Luigi Pontieri
Deviance-Aware Discovery of High-Quality Process Models. Int. J. Artif. Intell. Tools 27 (7) (2018)
Alfredo Cuzzocrea, Francesco Folino, Massimo Guarascio, Luigi Pontieri
Deviance-Aware Discovery of High Quality Process Models. ICTAI (2017)
Francesco Folino, Massimo Guarascio, Luigi Pontieri
A descriptive clustering approach to the analysis of quantitative business-process deviances. SAC (2017)
Alfredo Cuzzocrea, Francesco Folino, Massimo Guarascio, Luigi Pontieri
Experimenting and Assessing a Probabilistic Business Process Deviance Mining Framework Based on Ensemble Learning. ICEIS (Revised Selected Papers) (2017)
Alfredo Cuzzocrea, Francesco Folino, Massimo Guarascio, Luigi Pontieri
Extensions, Analysis and Experimental Assessment of a Probabilistic Ensemble-learning Framework for Detecting Deviances in Business Process Instances. ICEIS (1) (2017)
Massimo Guarascio, Ettore Ritacco, Daniele Biondo, Rocco Mammoliti, Alessandra Toma
Integrating a Framework for Discovering Alternative App Stores in a Mobile App Monitoring Platform. NFMCP@PKDD/ECML (2017)
Eugenio Cesario, Francesco Folino, Massimo Guarascio, Luigi Pontieri
A Cloud-Based Prediction Framework for Analyzing Business Process Performances. CD-ARES (2016)
Alfredo Cuzzocrea, Francesco Folino, Massimo Guarascio, Luigi Pontieri
A Robust and Versatile Multi-View Learning Framework for the Detection of Deviant Business Process Instances. Int. J. Cooperative Inf. Syst. 25 (4) (2016)
Alfredo Cuzzocrea, Francesco Folino, Massimo Guarascio, Luigi Pontieri
A multi-view multi-dimensional ensemble learning approach to mining business process deviances. IJCNN (2016)
Massimo Guarascio, Francesco Sergio Pisani, Ettore Ritacco, Pietro Sabatino
Profiling Human Behavior Through Multidimensional Latent Factor Modeling. NFMCP@PKDD/ECML (2016)
Francesco Folino, Massimo Guarascio, Luigi Pontieri
On the Discovery of Explainable and Accurate Behavioral Models for Complex Lowly-structured Business Processes. ICEIS (1) (2015)
Francesco Folino, Massimo Guarascio, Luigi Pontieri
Mining Multi-variant Process Models from Low-Level Logs. BIS (2015)
Alfredo Cuzzocrea, Francesco Folino, Massimo Guarascio, Luigi Pontieri
A Multi-view Learning Approach to the Discovery of Deviant Process Instances. OTM Conferences (2015)
Francesco Folino, Massimo Guarascio, Luigi Pontieri
A Prediction Framework for Proactively Monitoring Aggregate Process-Performance Indicators. EDOC (2015)
Francesco Folino, Massimo Guarascio, Luigi Pontieri
A Framework for the Discovery of Predictive Fix-time Models. ICEIS (1) (2014)
Francesco Folino, Massimo Guarascio, Luigi Pontieri
Mining Predictive Process Models out of Low-level Multidimensional Logs. CAiSE (2014)
Francesco Folino, Massimo Guarascio, Luigi Pontieri
An Approach to the Discovery of Accurate and Expressive Fix-Time Prediction Models. ICEIS (Revised Selected Papers) (2014)
Antonio Bevacqua, Marco Carnuccio, Francesco Folino, Massimo Guarascio, Luigi Pontieri
Adaptive Trace Abstraction Approach for Predicting Business Process Performances. SEBD (2013)
Antonio Bevacqua, Marco Carnuccio, Francesco Folino, Massimo Guarascio, Luigi Pontieri
A Data-Driven Prediction Framework for Analyzing and Monitoring Business Process Performances. ICEIS (2013)
Antonio Bevacqua, Marco Carnuccio, Francesco Folino, Massimo Guarascio, Luigi Pontieri
A Data-adaptive Trace Abstraction Approach to the Prediction of Business Process Performances. ICEIS (1) (2013)
Francesco Folino, Massimo Guarascio, Luigi Pontieri
Discovering High-Level Performance Models for Ticket Resolution Processes. OTM Conferences (2013)
Lucantonio Ghionna, Luigi Granata, Gianluigi Greco, Massimo Guarascio
ProMetheuS: A Suite for Process Mining Applications. CAiSE Forum (2012)
Francesco Folino, Massimo Guarascio, Luigi Pontieri
Context-Aware Predictions on Business Processes: An Ensemble-Based Solution. NFMCP (2012)
Francesco Folino, Massimo Guarascio, Luigi Pontieri
Discovering Context-Aware Models for Predicting Business Process Performances. OTM Conferences (1) (2012)
Nicola Barbieri, Massimo Guarascio, Ettore Ritacco
An Empirical Comparison of Collaborative Filtering Approaches on Netflix Data. IIR (2010)
Nicola Barbieri, Massimo Guarascio, Giuseppe Manco
A Block Mixture Model for Pattern Discovery in Preference Data. ICDM Workshops (2010)
Gianni Costa, Fabio Fassetti, Massimo Guarascio, Giuseppe Manco, Riccardo Ortale
Mining models of exceptional objects through rule learning. SAC (2010)
Gianni Costa, Massimo Guarascio, Giuseppe Manco, Riccardo Ortale, Ettore Ritacco
Rule Learning with Probabilistic Smoothing. DaWaK (2009)
Gianni Costa, Massimo Guarascio, Giuseppe Manco, Riccardo Ortale, Ettore Ritacco
A Hierarchical Rule-based Framework for Accurate Classification in Imprecise Domains. SEBD (2009)
Stefano Basta, Fabio Fassetti, Massimo Guarascio, Giuseppe Manco, Fosca Giannotti, Dino Pedreschi, Laura Spinsanti, Gianfilippo Papi, Stefano Pisani
High Quality True-Positive Prediction for Fiscal Fraud Detection. ICDM Workshops (2009)