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ORCIDMassimo Guarascio 0001
Person information
- affiliation: National Research Council, Italy
- affiliation (PhD 2011): University of Calabria, Cosenza, Italy
Other persons with the same name
- Massimo Guarascio 0002 — Sapienza University, Rome, Italy
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2020 – today
- 2024
[j18]Nunziato Cassavia, Luca Caviglione, Massimo Guarascio
, Angelica Liguori, Marco Zuppelli:
Learning autoencoder ensembles for detecting malware hidden communications in IoT ecosystems. J. Intell. Inf. Syst. 62(4): 925-949 (2024)- [j17]Francesco Folino, Gianluigi Folino, Massimo Guarascio, Luigi Pontieri:
Data- & compute-efficient deviance mining via active learning and fast ensembles. J. Intell. Inf. Syst. 62(4): 995-1019 (2024) - [j16]Massimo Guarascio, Marco Minici, Francesco Sergio Pisani, Erika De Francesco, Pasquale Lambardi:
Movie tag prediction: An extreme multi-label multi-modal transformer-based solution with explanation. J. Intell. Inf. Syst. 62(4): 1021-1043 (2024) - [j15]Francesco Folino, Gianluigi Folino, Massimo Guarascio, Luigi Pontieri, Paolo Zicari:
Towards Data- and Compute-Efficient Fake-News Detection: An Approach Combining Active Learning and Pre-Trained Language Models. SN Comput. Sci. 5(5): 470 (2024) - [c60]Marco Zuppelli, Massimo Guarascio, Luca Caviglione, Angelica Liguori:
No Country for Leaking Containers: Detecting Exfiltration of Secrets Through AI and Syscalls. ARES 2024: 78:1-78:8 - [c59]Luca Caviglione, Massimo Guarascio, Francesco Sergio Pisani, Marco Zuppelli:
A Few to Unveil Them All: Leveraging Mixture of Experts on Minimal Data for Detecting Covert Channels in Containerized Cloud Infrastructures. EuroS&P Workshops 2024: 731-739 - [c58]Angelica Liguori, Marco Zuppelli, Daniela Gallo, Massimo Guarascio, Luca Caviglione:
Erasing the Shadow: Sanitization of Images with Malicious Payloads Using Deep Autoencoders. ISMIS 2024: 115-125 - [c57]Luca Caviglione, Carmela Comito, Erica Coppolillo, Daniela Gallo, Massimo Guarascio, Angelica Liguori, Giuseppe Manco, Marco Minici, Simone Mungari, Francesco Sergio Pisani, Ettore Ritacco, Antonino Rullo, Paolo Zicari, Marco Zuppelli:
Dawn of LLM4Cyber: Current Solutions, Challenges, and New Perspectives in Harnessing LLMs for Cybersecurity. Ital-IA 2024: 170-175 - [c56]Camilla Cespi Polisiani, Marco Zuppelli, Maria Carla Calzarossa, Luca Caviglione, Massimo Guarascio:
Mitigation of Covert Communications in MQTT Topics Through Small Language Models. MASCOTS 2024: 1-6 - [i4]Luca Caviglione, Gianluigi Folino, Massimo Guarascio, Paolo Zicari:
Boosting MATE Security through Small Language Models. ERCIM News 139(138) (2024) - 2023
- [j14]Gianluigi Folino, Massimo Guarascio, Francesco Chiaravalloti:
Learning ensembles of deep neural networks for extreme rainfall event detection. Neural Comput. Appl. 35(14): 10347-10360 (2023) - [j13]Simona Cicero, Massimo Guarascio, Antonio Guerrieri, Simone Mungari:
A Deep Anomaly Detection System for IoT-Based Smart Buildings. Sensors 23(23): 9331 (2023) - [j12]Nunziato Cassavia, Luca Caviglione, Massimo Guarascio, Angelica Liguori, Giuseppe Manco, Marco Zuppelli:
A federated approach for detecting data hidden in icons of mobile applications delivered via web and multiple stores. Soc. Netw. Anal. Min. 13(1): 114 (2023) - [j11]Vito Barbara, Massimo Guarascio, Nicola Leone, Giuseppe Manco, Alessandro Quarta, Francesco Ricca, Ettore Ritacco:
Neuro-Symbolic AI for Compliance Checking of Electrical Control Panels. Theory Pract. Log. Program. 23(4): 748-764 (2023) - [c55]Irfanullah Khan, Flávia Coimbra Delicato, Emilio Greco, Massimo Guarascio, Antonio Guerrieri, Giandomenico Spezzano:
Occupancy Prediction in Multi-Occupant IoT Environments Leveraging Federated Learning. DASC/PiCom/CBDCom/CyberSciTech 2023: 36-43 - [c54]Paolo Zicari, Massimo Guarascio, Luigi Pontieri, Gianluigi Folino:
Learning Deep Fake-News Detectors from Scarcely-Labelled News Corpora. ICEIS (1) 2023: 344-353 - [c53]Erica Coppolillo, Massimo Guarascio, Marco Minici, Francesco Sergio Pisani:
Exploiting Deep Learning and Explanation Methods for Movie Tag Prediction. IDEAS 2023: 177-184 - [c52]Angelica Liguori, Simone Mungari, Marco Zuppelli, Carmela Comito, Enrico Cambiaso, Matteo Repetto, Massimo Guarascio, Luca Caviglione, Giuseppe Manco:
Using AI to face covert attacks in IoT and softwarized scenarios: challenges and opportunities. Ital-IA 2023: 397-402 - [c51]Erica Coppolillo, Carmela Comito, Marco Minici, Ettore Ritacco, Gianluigi Folino, Francesco Sergio Pisani, Massimo Guarascio, Giuseppe Manco:
Fighting Misinformation, Radicalization and Bias in Social Media. Ital-IA 2023: 443-448 - [c50]Carmela Comito, Francesco Sergio Pisani, Erica Coppolillo, Angelica Liguori, Massimo Guarascio, Giuseppe Manco:
Towards Self-Supervised Cross-Domain Fake News Detection. ITASEC 2023 - [c49]Luca Caviglione, Carmela Comito, Massimo Guarascio, Giuseppe Manco, Francesco Sergio Pisani, Marco Zuppelli:
ORISHA: Improving Threat Detection through Orchestrated Information Sharing (Discussion Paper). SEBD 2023: 514-524 - [i3]Vito Barbara, Massimo Guarascio, Nicola Leone, Giuseppe Manco, Alessandro Quarta, Francesco Ricca, Ettore Ritacco:
Neuro-Symbolic AI for Compliance Checking of Electrical Control Panels. CoRR abs/2305.10113 (2023) - [i2]Gianluigi Folino, Massimo Guarascio, Luigi Pontieri, Paolo Zicari:
An Explainable Deep Ensemble Framework for Intelligent Ticket Management. ERCIM News 2023(134) (2023) - 2022
- [j10]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): 729-749 (2022) - [j9]Paolo Zicari, Gianluigi Folino, Massimo Guarascio, Luigi Pontieri:
Combining deep ensemble learning and explanation for intelligent ticket management. Expert Syst. Appl. 206: 117815 (2022) - [j8]Massimo Guarascio, Nunziato Cassavia, Francesco Sergio Pisani, Giuseppe Manco:
Boosting Cyber-Threat Intelligence via Collaborative Intrusion Detection. Future Gener. Comput. Syst. 135: 30-43 (2022) - [j7]Nunziato Cassavia, Luca Caviglione, Massimo Guarascio, Giuseppe Manco, Marco Zuppelli:
Detection of Steganographic Threats Targeting Digital Images in Heterogeneous Ecosystems Through Machine Learning. J. Wirel. Mob. Networks Ubiquitous Comput. Dependable Appl. 13(3): 50-67 (2022) - [j6]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: 1-11 (2022) - [c48]Massimo Guarascio, Marco Zuppelli, Nunziato Cassavia, Luca Caviglione, Giuseppe Manco:
Revealing MageCart-like Threats in Favicons via Artificial Intelligence. ARES 2022: 45:1-45:7 - [c47]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: 247-253 - [c46]Erica Coppolillo, Angelica Liguori, Massimo Guarascio, Francesco Sergio Pisani, Giuseppe Manco:
Generative Methods for Out-of-distribution Prediction and Applications for Threat Detection and Analysis: A Short Review. CyberSec4Europe 2022: 65-79 - [c45]Nunziato Cassavia, Francesco Folino, Massimo Guarascio:
Detecting DoS and DDoS Attacks through Sparse U-Net-like Autoencoders. ICTAI 2022: 1342-1346 - [c44]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: 138-148 - [c43]Nunziato Cassavia, Luca Caviglione, Massimo Guarascio, Angelica Liguori, Marco Zuppelli:
Ensembling Sparse Autoencoders for Network Covert Channel Detection in IoT Ecosystems. ISMIS 2022: 209-218 - [c42]Francesco Folino, Gianluigi Folino, Massimo Guarascio, Luigi Pontieri:
Combining Active Learning and Fast DNN Ensembles for Process Deviance Discovery. ISMIS 2022: 346-356 - [c41]Massimo Guarascio, Marco Zuppelli, Nunziato Cassavia, Giuseppe Manco, Luca Caviglione:
Detection of Network Covert Channels in IoT Ecosystems Using Machine Learning. ITASEC 2022: 102-113 - [c40]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: 83-95 - [c39]Marco Minici, Francesco Sergio Pisani, Massimo Guarascio, Giuseppe Manco:
Towards Extreme Multi-Label Classification of Multimedia Content. SEBD 2022: 367-374 - 2021
- [j5]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: 48-69 (2021) - [c38]Marco Zuppelli, Giuseppe Manco, Luca Caviglione, Massimo Guarascio:
Sanitization of Images Containing Stegomalware via Machine Learning Approaches. ITASEC 2021: 374-386 - [c37]Paolo Zicari, Gianluigi Folino, Massimo Guarascio, Luigi Pontieri:
Discovering accurate deep learning based predictive models for automatic customer support ticket classification. SAC 2021: 1098-1101 - 2020
- [c36]Francesco Scicchitano, Angelica Liguori, Massimo Guarascio, Ettore Ritacco, Giuseppe Manco:
Deep Autoencoder Ensembles for Anomaly Detection on Blockchain. ISMIS 2020: 448-456 - [c35]Francesco Scicchitano, Angelica Liguori, Massimo Guarascio, Ettore Ritacco, Giuseppe Manco:
A Deep Learning Approach for Detecting Security Attacks on Blockchain. ITASEC 2020: 212-222 - [c34]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: 249-262 - [c33]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: 263-275 - [i1]Gianluigi Folino, Massimo Guarascio, Francesco Chiaravalloti, Salvatore Gabriele:
Using Deep Learning and Data Integration for Accurate Rainfall Estimates. ERCIM News 2020(122) (2020)
2010 – 2019
- 2019
- [j4]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: 284-297 (2019) - [j3]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: 236-266 (2019) - [c32]Francesco Folino, Gianluigi Folino, Massimo Guarascio, Luigi Pontieri:
Learning Effective Neural Nets for Outcome Prediction from Partially Labelled Log Data. ICTAI 2019: 1396-1400 - [c31]Gianluigi Folino, Massimo Guarascio, Francesco Chiaravalloti, Salvatore Gabriele:
A Deep Learning based architecture for rainfall estimation integrating heterogeneous data sources. IJCNN 2019: 1-8 - [c30]Giuseppe Manco, Ettore Ritacco, Noveen Sachdeva, Massimo Guarascio:
Deep Sequential Modeling for Recommendation. SEBD 2019 - [r5]Gianluigi Folino, Massimo Guarascio, Maryam Amir Haeri:
Deep Learning on Big Data. Encyclopedia of Big Data Technologies 2019 - [r4]Massimo Guarascio, Giuseppe Manco, Ettore Ritacco:
Knowledge Discovery in Databases. Encyclopedia of Bioinformatics and Computational Biology (1) 2019: 336-341 - [r3]Massimo Guarascio, Giuseppe Manco, Ettore Ritacco:
Deep Learning. Encyclopedia of Bioinformatics and Computational Biology (1) 2019: 634-647 - [r2]Giuseppe Manco, Ettore Ritacco, Massimo Guarascio:
Network Topology. Encyclopedia of Bioinformatics and Computational Biology (1) 2019: 958-967 - [r1]Massimo Guarascio, Giuseppe Manco, Ettore Ritacco:
Network Models. Encyclopedia of Bioinformatics and Computational Biology (1) 2019: 968-977 - 2018
- [j2]Alfredo Cuzzocrea, Francesco Folino, Massimo Guarascio, Luigi Pontieri:
Deviance-Aware Discovery of High-Quality Process Models. Int. J. Artif. Intell. Tools 27(7): 1860009:1-1860009:27 (2018) - [c29]Alfredo Cuzzocrea, Francesco Folino, Massimo Guarascio, Luigi Pontieri:
A Predictive Learning Framework for Monitoring Aggregated Performance Indicators over Business Process Events. IDEAS 2018: 165-174 - 2017
- [c28]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: 96-124 - [c27]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: 162-173 - [c26]Alfredo Cuzzocrea, Francesco Folino, Massimo Guarascio, Luigi Pontieri:
Deviance-Aware Discovery of High Quality Process Models. ICTAI 2017: 724-731 - [c25]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: 107-121 - [c24]Francesco Folino, Massimo Guarascio, Luigi Pontieri:
A descriptive clustering approach to the analysis of quantitative business-process deviances. SAC 2017: 765-770 - 2016
- [j1]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): 1740003:1-1740003:56 (2016) - [c23]Eugenio Cesario, Francesco Folino, Massimo Guarascio, Luigi Pontieri:
A Cloud-Based Prediction Framework for Analyzing Business Process Performances. CD-ARES 2016: 63-80 - [c22]Alfredo Cuzzocrea, Francesco Folino, Massimo Guarascio, Luigi Pontieri:
A multi-view multi-dimensional ensemble learning approach to mining business process deviances. IJCNN 2016: 3809-3816 - [c21]Massimo Guarascio, Francesco Sergio Pisani, Ettore Ritacco, Pietro Sabatino:
Profiling Human Behavior Through Multidimensional Latent Factor Modeling. NFMCP@PKDD/ECML 2016: 148-162 - 2015
- [c20]Francesco Folino, Massimo Guarascio, Luigi Pontieri:
Mining Multi-variant Process Models from Low-Level Logs. BIS 2015: 165-177 - [c19]Francesco Folino, Massimo Guarascio, Luigi Pontieri:
A Prediction Framework for Proactively Monitoring Aggregate Process-Performance Indicators. EDOC 2015: 128-133 - [c18]Francesco Folino, Massimo Guarascio, Luigi Pontieri:
On the Discovery of Explainable and Accurate Behavioral Models for Complex Lowly-structured Business Processes. ICEIS (1) 2015: 206-217 - [c17]Alfredo Cuzzocrea, Francesco Folino, Massimo Guarascio, Luigi Pontieri:
A Multi-view Learning Approach to the Discovery of Deviant Process Instances. OTM Conferences 2015: 146-165 - 2014
- [c16]Francesco Folino, Massimo Guarascio, Luigi Pontieri:
Mining Predictive Process Models out of Low-level Multidimensional Logs. CAiSE 2014: 533-547 - [c15]Francesco Folino, Massimo Guarascio, Luigi Pontieri:
A Framework for the Discovery of Predictive Fix-time Models. ICEIS (1) 2014: 99-108 - [c14]Francesco Folino, Massimo Guarascio, Luigi Pontieri:
An Approach to the Discovery of Accurate and Expressive Fix-Time Prediction Models. ICEIS (Revised Selected Papers) 2014: 108-128 - 2013
- [c13]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: 56-65 - [c12]Antonio Bevacqua, Marco Carnuccio, Francesco Folino, Massimo Guarascio, Luigi Pontieri:
A Data-Driven Prediction Framework for Analyzing and Monitoring Business Process Performances. ICEIS 2013: 100-117 - [c11]Francesco Folino, Massimo Guarascio, Luigi Pontieri:
Discovering High-Level Performance Models for Ticket Resolution Processes. OTM Conferences 2013: 275-282 - [c10]Antonio Bevacqua, Marco Carnuccio, Francesco Folino, Massimo Guarascio, Luigi Pontieri:
Adaptive Trace Abstraction Approach for Predicting Business Process Performances. SEBD 2013: 437-444 - 2012
- [c9]Lucantonio Ghionna, Luigi Granata, Gianluigi Greco, Massimo Guarascio:
ProMetheuS: A Suite for Process Mining Applications. CAiSE Forum 2012: 58-65 - [c8]Francesco Folino, Massimo Guarascio, Luigi Pontieri:
Discovering Context-Aware Models for Predicting Business Process Performances. OTM Conferences (1) 2012: 287-304 - [c7]Francesco Folino, Massimo Guarascio, Luigi Pontieri:
Context-Aware Predictions on Business Processes: An Ensemble-Based Solution. NFMCP 2012: 215-229 - 2010
- [c6]Nicola Barbieri, Massimo Guarascio, Giuseppe Manco:
A Block Mixture Model for Pattern Discovery in Preference Data. ICDM Workshops 2010: 1100-1107 - [c5]Nicola Barbieri, Massimo Guarascio, Ettore Ritacco:
An Empirical Comparison of Collaborative Filtering Approaches on Netflix Data. IIR 2010: 23-27 - [c4]Gianni Costa, Fabio Fassetti, Massimo Guarascio, Giuseppe Manco, Riccardo Ortale:
Mining models of exceptional objects through rule learning. SAC 2010: 1078-1082
2000 – 2009
- 2009
- [c3]Gianni Costa, Massimo Guarascio, Giuseppe Manco, Riccardo Ortale, Ettore Ritacco:
Rule Learning with Probabilistic Smoothing. DaWaK 2009: 428-440 - [c2]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: 7-12 - [c1]Gianni Costa, Massimo Guarascio, Giuseppe Manco, Riccardo Ortale, Ettore Ritacco:
A Hierarchical Rule-based Framework for Accurate Classification in Imprecise Domains. SEBD 2009: 261-272
Coauthor Index
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