Tommaso ZOPPI

Ruolo attuale:: Ricercatore Legge 240/10 a tempo determinato
SSD:: INFO-01/A - Informatica
Afferenza organizzativa:: Dipartimento di Matematica e Informatica 'Ulisse Dini'

Recapiti

	0552751479
	tommaso.zoppi(AT)unifi.it

Ulteriori Recapiti

	Stanza 156 - Primo Piano (Citofono 1479) - Viale Morgagni 65
	0552751479
	tommaso.zoppi(AT)unifi.it
	http://rcl.dsi.unifi.it/member/13/show-3

Tommaso ZOPPI

Orario di ricevimento (aggiornato al 08/10/2018)

Ricevimento su appuntamento (contattare preferibilmente via email).

Tommaso ZOPPI

Biografia

Tommaso Zoppi è attualmente un RTD-A ad UNIFI.

Ha conseguito le lauree triennali e magistrali in Informatica presso la stessa università rispettivamente nell'ottobre 2012 e nel luglio 2014. Da novembre 2014 a novembre 2017 è stato dottorando in Matematica, Informatica, Statistica (curriculum: Informatica), sotto la supervisione del Prof. Andrea Bondavalli.

Da Gennaio 2014 a Marzo 2015 è stato titolare di un incarico Co.Co.Co mirato a trovare una soluzione efficiente per il rilevamento di anomalie software (nel contesto di dependability). Da Marzo 2015 ad Aprile 2018 è stato tutor per il corso di laurea triennale in Scienze informatiche. Un tutor contribuisce a sostenere gli studenti del primo anno aiutandoli nell'organizzazione degli studi e semplificando le relazioni tra studenti e professori.

Docente a contratto per 3 CFU di "Quantitative Analysis of Systems" per il CDL Magistrale in Informatica SMFN AA.1819

Docente per 3 CFU di "Architetture degli Elaboratori" per il CDL Triennale in Informatica SMFN AA.1920, 2021, 2122, 2223

Docente per 3 CFU di "Quantitative Analysis of Systems" per il CDL Magistrale in Informatica SMFN AA.1920, 2021

Docente per 4 CFU di "Data Collection and Machine Learning for Critical Cyber-Physical Systems" per il CDL Magistrale in Informatica SMFN AA.2122

Nonostante i suoi principali interessi di ricerca siano relativi allo studio delle anomalie software (anomaly detection), sta anche esplorando:

- sicurezza (safety) nel settore ferroviario

- rilevamento di anomalie (anomaly detection) in sistemi dinamici e complessi

- rilevamento delle intrusioni (intrusion detection) basato sul rilevamento di anomalie

- sistemi di supporto per la gestione delle crisi (crisis management systems)

Ufficio: Dipartimento di Matematica e Informatica (DiMaI)

Viale Morgagni, 65 - 50134 - Firenze Italia

Tommaso ZOPPI

Curriculum

Link CV

Tommaso ZOPPI

Interessi

- sicurezza (safety) nel settore ferroviario

- rilevamento di anomalie (anomaly detection) in sistemi dinamici e complessi

- rilevamento delle intrusioni (intrusion detection) basato sul rilevamento di anomalie

- machine learning per sistemi critici

Tommaso ZOPPI

Pubblicazioni

Legenda

Contributo su rivista |

Articolo su libro |

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Contributo in atti di convegno (proceeding) |

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Tesi di Dottorato

Puccetti T.; Zoppi T.; Ceccarelli A. (2024). On Attacks (Dis)Similarities to Test Adversarial Defense: Can We Reduce the Attack Set?. In: 8th Italian Conference on Cyber Security, ITASEC 2024, ita, 2024, CEUR-WS, vol. 3731, pp. 0-0.

Puccetti T.; Nardi S.; Cinquilli C.; Zoppi T.; Ceccarelli A. (2024). ROSPaCe: Intrusion Detection Dataset for a ROS2-Based Cyber-Physical System and IoT Networks. SCIENTIFIC DATA, vol. 11, pp. 0-0, ISSN:2052-4463 DOI Accesso ONLINE all'editore

Zoppi T.; Kohkar F.A.; Ceccarelli A.; Bondavalli A. (2024). Position Paper - Bringing Classifiers into Critical Systems: Are We Barking up the Wrong Tree?. In: 19th Workshop on Dependable Smart Embedded and Cyber-Physical Systems and Systems-of-Systems, DECSoS 2024, 11th International Workshop on Next Generation of System Assurance Approaches for Critical Systems, SASSUR 2024, Towards A Safer Systems architecture Through Security, TOASTS 2024 and 7th International Workshop on Artificial Intelligence Safety Engineering, WAISE 2024 held in conjunction with the 43rd International Conference on Computer Safety, Reliability, and Security, SAFECOMP 2024, ita, 2024, Springer Science and Business Media Deutschland GmbH, vol. 14989, pp. 351-357, ISBN:9783031687372 DOI

Zoppi T.; Gazzini S.; Ceccarelli A. (2024). Anomaly-based error and intrusion detection in tabular data: No DNN outperforms tree-based classifiers. FUTURE GENERATION COMPUTER SYSTEMS, vol. 160, pp. 951-965, ISSN:0167-739X DOI

Zoppi T.; Mungiello I.; Ceccarelli A.; Cirillo A.; Sarti L.; Esposito L.; Scaglione G.; Repetto S.; Bondavalli A. (2023). Safe Maintenance of Railways using COTS Mobile Devices: The Remote Worker Dashboard. ACM TRANSACTIONS ON CYBER-PHYSICAL SYSTEMS, vol. 7, pp. 0-20, ISSN:2378-962X DOI

Tommaso Puccetti; Andrea Ceccarelli; Tommaso Zoppi; Andrea Bondavalli; (2023). Detection of Adversarial Attacks by Observing Deep Features with Structured Data Algorithms. In: 38th Annual ACM Symposium on Applied Computing, SAC 2023, est, 2023, Association for Computing Machinery, pp. 125-134, ISBN:9781450395175 DOI

Tommaso Zoppi, Andrea Ceccarelli, Andrea Bondavalli (2023). Towards a General Model for Intrusion Detection: An Exploratory Study. In: Machine Learning and Principles and Practice of Knowledge Discovery in Databases. ECML PKDD 2022, Grenoble, Francia, 19-23 Settembre 2022, Springer, Cham, vol. 1753, pp. 186-201, ISBN:978-3-031-23633-4 DOI Accesso ONLINE all'editore

Zoppi T.; Merlino G.; Ceccarelli A.; Puliafito A.; Bondavalli A. (2023). Anomaly Detectors for Self-Aware Edge and IoT Devices. In: 23rd IEEE International Conference on Software Quality, Reliability, and Security, QRS 2023, tha, 2023, Institute of Electrical and Electronics Engineers Inc., pp. 24-35, ISBN:979-8-3503-1958-3 DOI

Ceccarelli A.; Zoppi T. (2023). Intrusion detection without attack knowledge: Generating out-of-distribution tabular data. In: 34th IEEE International Symposium on Software Reliability Engineering, ISSRE 2023, ita, 2023, IEEE Computer Society, pp. 125-136, ISBN:979-8-3503-1594-3 DOI

Zoppi T.; Ceccarelli A.; Bondavalli A. (2023). Ensembling Uncertainty Measures to Improve Safety of Black-Box Classifiers. In: European Conference on Artificial Intelligence, IOS Press, vol. 372, pp. 3156-3164, ISBN:9781643684369 DOI

Muhammad Atif; Andrea Ceccarelli; Tommaso Zoppi; Andrea Bondavalli (2023). Tolerate Failures of the Visual Camera With Robust Image Classifiers. IEEE ACCESS, vol. 11, pp. 5132-5143, ISSN:2169-3536 DOI Accesso ONLINE all'editore

Tommaso Zoppi, Andrea Ceccarelli, Tommaso Puccetti, Andrea Bondavalli (2023). Which algorithm can detect unknown attacks? Comparison of supervised, unsupervised and meta-learning algorithms for intrusion detection. COMPUTERS & SECURITY, vol. 127, pp. 0-0, ISSN:0167-4048 DOI Accesso ONLINE all'editore

Gharib, Mohamad; Zoppi, Tommaso; Bondavalli, Andrea (2022). On the Properness of Incorporating Binary Classification Machine Learning Algorithms into Safety-Critical Systems. IEEE TRANSACTIONS ON EMERGING TOPICS IN COMPUTING, pp. 1-1, ISSN:2168-6750 DOI Accesso ONLINE all'editore

Atif M.; Zoppi T.; Gharib M.; Bondavalli A. (2022). Towards Enhancing Traffic Sign Recognition through Sliding Windows. SENSORS, vol. 22, pp. 2683-2708, ISSN:1424-8220 DOI Accesso ONLINE all'editore

MUHAMMAD ATIF , ANDREA CECCARELLI , TOMMASO ZOPPI , MOHAMAD GHARIB , ANDREA BONDAVALLI (2022). Robust Traffic Sign Recognition Against Camera Failures. IEEE OPEN JOURNAL OF INTELLIGENT TRANSPORTATION SYSTEMS, vol. 3, pp. 709-722, ISSN:2687-7813 DOI Accesso ONLINE all'editore

tommaso zoppi, andrea ceccarelli, tommaso capecchi, andrea bondavalli (2021). Unsupervised Anomaly Detectors to Detect Intrusions in the Current Threat Landscape. ACM/IMS TRANSACTIONS ON DATA SCIENCE, vol. 2, pp. 1-26, ISSN:2691-1922 DOI Accesso ONLINE all'editore

Zoppi Tommaso ; Ceccarelli Andrea; Bondavalli Andrea (2021). Unsupervised Algorithms to Detect Zero-Day Attacks: Strategy and Application. IEEE ACCESS, vol. 9, pp. 90603-90615, ISSN:2169-3536 DOI

Zoppi T.; Ceccarelli A. (2021). Prepare for trouble and make it double! Supervised – Unsupervised stacking for anomaly-based intrusion detection. JOURNAL OF NETWORK AND COMPUTER APPLICATIONS, vol. 189, pp. 0-0, ISSN:1084-8045 DOI Accesso ONLINE all'editore

Zoppi T.; Ceccarelli A.; Bondavalli A. (2021). MADneSs: a Multi-layer Anomaly Detection Framework for Complex Dynamic Systems. IEEE TRANSACTIONS ON DEPENDABLE AND SECURE COMPUTING, vol. 18, pp. 796-809, ISSN:1545-5971 DOI Accesso ONLINE all'editore

Zoppi T.; Gharib M.; Atif M.; Bondavalli A. (2021). Meta-learning to improve unsupervised intrusion detection in cyber-physical systems. ACM TRANSACTIONS ON CYBER-PHYSICAL SYSTEMS, vol. 5, pp. 1-27, ISSN:2378-962X DOI Accesso ONLINE all'editore

Bertieri D.; Ceccarelli A.; Zoppi T.; Mungiello I.; Barbareschi M.; Bondavalli A. (2021). Development and validation of a safe communication protocol compliant to railway standards. JOURNAL OF THE BRAZILIAN COMPUTER SOCIETY, vol. 27, pp. 0-0, ISSN:0104-6500 DOI

Gharib M.; Zoppi T.; Bondavalli A. (2021). Understanding the properness of incorporating machine learning algorithms in safety-critical systems. In: 36th Annual ACM Symposium on Applied Computing, SAC 2021, online, 2021, Association for Computing Machinery, pp. 232-234, ISBN:9781450381048 DOI Accesso ONLINE all'editore

Atif M.; Zoppi T.; Gharib M.; Bondavalli A. (2021). Quantitative comparison of supervised algorithms and feature sets for traffic sign recognition. In: 36th Annual ACM Symposium on Applied Computing, SAC 2021, online, 2021, Association for Computing Machinery, pp. 174-177, ISBN:9781450381048 DOI Accesso ONLINE all'editore

Zoppi Tommaso, Ceccarelli Andrea, Bondavalli Andrea (2021). Feature Rankers to Predict Classification Performance of Unsupervised Intrusion Detectors. In: 2021 10th Latin-American Symposium on Dependable Computing (LADC), IEEE, pp. 1-9. DOI

Tommaso Zoppi, Andrea Bondavalli, Andrea Ceccarelli (2021). Detecting Intrusions by Voting Diverse Machine Learners: Is It Really Worth?. In: 2021 IEEE 26th Pacific Rim International Symposium on Dependable Computing (PRDC), aus, 2021, IEEE, vol. 2021-, pp. 57-66, ISBN:9781665424769 DOI

Zoppi T.; Ceccarelli A.; (2021). Detect Adversarial Attacks against Deep Neural Networks with GPU Monitoring. IEEE ACCESS, vol. 9, pp. 150579-150591, ISSN:2169-3536 DOI Accesso ONLINE all'editore

Zoppi T.; Schiavone E.; Bicchierai I.; Brancati F.; Bondavalli A. (2021). Spoofing detectability as a property of biometric characteristics. In: 5th Italian Conference on Cybersecurity, ITASEC 2021, 2021, CEUR-WS, vol. 2940, pp. 92-105. Accesso ONLINE all'editore

Zoppi T.; Ceccarelli A.; Bondavalli A. (2020). Into the unknown: Unsupervised machine learning algorithms for anomaly-based intrusion detection. In: DEPENDABLE SYSTEMS AND NETWORKS, esp, 2020, Institute of Electrical and Electronics Engineers Inc., pp. 81-81, ISBN:978-1-7281-7260-6 DOI

Zoppi T.; Ceccarelli A.; Salani L.; Bondavalli A. (2020). On the educated selection of unsupervised algorithms via attacks and anomaly classes. JOURNAL OF INFORMATION SECURITY AND APPLICATIONS, vol. 52, pp. 0-0, ISSN:2214-2134 DOI

ANDREA CECCARELLI, TOMMASO ZOPPI, ALEXANDR VASENEV, MARCO MORI, DAN IONITA, LORENA MONTOYA, ANDREA BONDAVALLI (2019). Threat Analysis in Systems-of-Systems: An Emergence-Oriented Approach. ACM TRANSACTIONS ON CYBER-PHYSICAL SYSTEMS, vol. 3, pp. 1-24, ISSN:2378-962X DOI Accesso ONLINE all'editore

Filipe Falcao, Tommaso Zoppi, Caio Barbosa, Anderson Santos, Baldoino Fonseca, Andrea Ceccarelli, Andrea Bondavalli (2019). Quantitative Comparison of Unsupervised Anomaly Detection Algorithms for Intrusion Detection. In: ACM SYMPOSIUM ON APPLIED COMPUTING, Limassol, Cyprus, 8-12/4/2019, ACM, New York, NY, USA, pp. 318-327, ISBN:978-1-4503-5933-7 DOI

tommaso zoppi, andrea ceccarelli, andrea bondavalli (2019). An Initial Investigation on Sliding Windows for Anomaly-Based Intrusion Detection. In: Workshop on Cyber Security & Resilience in the Internet of Things (CSRIoT 2019), Milan, Italy, 8-11/7/2019, IEEE Computer Society, pp. 99-104. DOI Accesso ONLINE all'editore

Bertieri D.; Zoppi T.; Mungiello I.; Ceccarelli A.; Barbareschi M.; Bondavalli A. (2019). Practical Experience Report: Implementation, verification and validation of a safe and secure communication protocol for the railway domain. In: 9th Latin-American Symposium on Dependable Computing, LADC 2019, Instituto Metroplole Digital (IMD), Federal University of Rio Grande do Norte (UFRN), bra, 2019, Institute of Electrical and Electronics Engineers Inc., pp. 1-6, ISBN:978-1-7281-6622-3 DOI

Tommaso Zoppi, Andrea Ceccarelli, Andrea Bondavalli (2019). Evaluation of Anomaly Detection algorithms made easy with RELOAD. In: INTERNATIONAL SYMPOSIUM ON SOFTWARE RELIABILITY ENGINEERING, IEEE Computer Society, pp. 0-0. DOI Accesso ONLINE all'editore

Zoppi, Tommaso; Ceccarelli, Andrea; Lo Piccolo, Francesco; Lollini, Paolo; Giunta, Gabriele; Morreale, Vito; Bondavalli, Andrea (2018). Labelling Relevant Events to Support the Crisis Management Operator. JOURNAL OF SOFTWARE, vol. 30, pp. 0-0, ISSN:2047-7481 DOI Accesso ONLINE all'editore

tommaso zoppi, andrea ceccarelli, andrea bondavalli (2018). On Algorithms Selection for Unsupervised Anomaly Detection. In: PACIFIC RIM INTERNATIONAL SYMPOSIUM ON DEPENDABLE COMPUTING, Taipei, Taiwan, 4-7/12/2018, IEEE Computer Society, vol. 2018-December, pp. 279-288, ISBN:978-153865700-3 DOI

tommaso zoppi (2018). Towards Effective Anomaly Detection in Complex Dynamic Systems. (Tutor: Andrea Bondavalli, Andrea Ceccarelli)

Vasenev, Alexandr; Ionita, Dan; Zoppi, Tommaso; Ceccarelli, Andrea; Wieringa, Roel (2017). Towards security requirements: Iconicity as a feature of an informal modeling language. In: 2017 Joint REFSQ Workshops, Doctoral Symposium, Research Method Track, and Poster Track, co-located with the 23rd International Conference on Requirements Engineering: Foundation for Software Quality, REFSQ 2017, Essen, Germany, 2017, CEUR-WS, vol. 1796, pp. 0-0. Accesso ONLINE all'editore

Zoppi, Tommaso; Bessler, Sandford; Ceccarelli, Andrea; Lambert, Edward; Lau, Eng Tseng; Vasenev, Alexandr (2017). A Modeling Framework to Support Resilient Evolution Planning of Smart Grids. In: Smart Grid Inspired Future Technologies, London, UK, 27-28/03/2017, Springer, vol. 203, pp. 0-0, ISBN:978-3-319-61813-5 DOI Accesso ONLINE all'editore

Zoppi, Tommaso; Ceccarelli, Andrea; Mori, Marco (2017). A Tool for Evolutionary Threat Analysis of Smart Grids. In: Smart Grid Inspired Future Technologies, London, UK, 27-28/03/2017, Springer, vol. 203, pp. 205-211, ISBN:978-3-319-61813-5 DOI Accesso ONLINE all'editore

Zoppi, Tommaso (2017). Executing Online Anomaly Detection in Complex Dynamic Systems. In: 24th PhD MiniSymposium, Budapest, January, 30th-31st, 2017, Department of Measurement and Information Systems, Budapest University of Technology and Economics, pp. 86-89, ISBN:978-963-313-243-2 DOI Accesso ONLINE all'editore

Zoppi, Tommaso; Ceccarelli, Andrea; Bondavalli, Andrea (2017). Exploring Anomaly Detection in Systems of Systems. In: ACM SYMPOSIUM ON APPLIED COMPUTING, Marrakech, Marocco, 4-7/4/2017, ACM, vol. ..., pp. 1139-1146, ISBN:978-1-4503-4486-9 DOI Accesso ONLINE all'editore

Mario Rui Baptista; Nuno Silva; Nicola Nostro; Tommaso Zoppi; Andrea Ceccarelli; (2017). STECA – Security Threats, Effects and Criticality Analysis: Definition and Application to Smart Grids. In: Mario Rui Baptista, Nuno Silva, Nicola Nostro, Tommaso Zoppi and Andrea Ceccarelli. Certifications of Critical Systems - The CECRIS Experience, pp. 167-182 Andrea Bondavalli, Francesco Brancati, ISBN:9788793519565. DOI Accesso ONLINE all'editore

Zoppi, Tommaso; Ceccarelli, Andrea; Bondavalli, Andrea (2016). Challenging Anomaly Detection in Complex Dynamic Systems. In: 35th IEEE International Symposium on Reliable Distributed Systems, SRDS 2016, Budapest, 2016, IEEE, pp. 213-214, ISBN:978-1-5090-3513-7 DOI

Mori, Marco; Ceccarelli, Andrea; Zoppi, Tommaso; Bondavalli, Andrea (2016). On the impact of emergent properties on SoS security. In: 11th Systems of Systems Engineering Conference, SoSE 2016, Kongsberg, Norway, 12-16/6/2016, IEEE, pp. 0-0, ISBN:978-1-4673-8727-9 DOI

Zoppi, Tommaso; Ceccarelli, Andrea; Bondavalli, Andrea (2016). Context-Awareness to improve Anomaly Detection in Dynamic Service Oriented Architectures. In: INTERNATIONAL CONFERENCE ON COMPUTER SAFETY, RELIABILITY AND SECURITY, Trondheim, Norway, 20-23 September 2016, Springer, vol. 9922, pp. 145-158, ISBN:978-3-319-45476-4 DOI

Zoppi, Tommaso; Ceccarelli, Andrea; Lollini, Paolo; Bondavalli, Andrea; Lo Piccolo, Francesco; Giunta, Gabriele; Morreale, Vito (2016). Presenting the Proper Data to the Crisis Management Operator: A Relevance Labelling Strategy. In: IEEE INTERNATIONAL SYMPOSIUM ON HIGH ASSURANCE SYSTEMS ENGINEERING, Orlando, Florida, 7-9/1/2016, IEEE, vol. 2016 IEEE 17th International Symposium on High Assurance Systems Engineering (HASE), pp. 228-235, ISBN:978-1-4673-9913-5 DOI Accesso ONLINE all'editore

Jung, Oliver; Bessler, Sandford; Ceccarelli, Andrea; Zoppi, Tommaso; Vasenev, Alexandr; Montoya, Lorena; Clarke, Tony; Chappell, Keith (2016). Towards a Collaborative Framework to Improve Urban Grid Resilience. In: IEEE INTERNATIONAL ENERGY CONFERENCE, Leuven, Belgium, 4-8/4/2016, IEEE, pp. 0-0, ISBN:978-1-4673-8463-6 DOI

Tommaso Zoppi; Andrea Bondavalli; Andrea Ceccarelli; Massimiliano Itria (2015). A Multi-layer Anomaly Detector for Dynamic Service-Based Systems. In: INTERNATIONAL CONFERENCE ON COMPUTER SAFETY, RELIABILITY AND SECURITY, Delft, 22-09-2015, Springer, vol. 9337, pp. 166-180, ISBN:978-3-319-24254-5 DOI

Zoppi Tommaso (2015). Multi-Layer Anomaly Detection in Complex Dynamic Critical Systems. In: Dependable Systems And Networks (DSN 2015), IEEE, pp. 0-0.

Andrea Ceccarelli;Tommaso Zoppi;Andrea Bondavalli;Fabio Duchi;Giuseppe Vella (2014). A Testbed for Evaluating Anomaly Detection Monitors through Fault Injection. In: 2014 IEEE 17th International Symposium on Object/Component/Service-Oriented Real-Time Distributed Computing (ISORC), Reno, NV, USA, 10-12 June 2014, IEEE, pp. 358-365, ISBN:978-1-4799-4430-9 DOI

Tommaso ZOPPI

Biography

Tommaso Zoppi is currently a Research Associate (RTD-A) at UNIFI, RCL Group.

He received his Bachelor and Master degree in Computer Science from the University of Firenze, Italy, in October 2012 and July 2014, respectively. From November 2014 to November 2017 he was a PhD student at the Matematics, Computer Science, Statistics course (curriculum: Computer Science) at the same university, under the supervision of Prof. Andrea Bondavalli.

From January 2014 to March 2015 he was owner of a Co.Co.Co employment aimed at finding efficient solution for software anomaly detection (within the dependability context).

Since March 2015, he is a tutor at the same university for the bachelor course in Informatic Science. A tutor contributes to support first-year students helping them in the studies' organization and simplifying the relationships between students and professors.

Despite his main research efforts are directed to the study of software anomalies, his research is also exploring:

cyber-security analysis of smart grids
anomaly-based intrusion detection
support to smart city planners
crisis management systems

Office:

Dipartimento di Matematica e Informatica (DiMaI), Room 156

Viale Morgagni, 65 - 50134 - Firenze Italy

Tommaso ZOPPI

Interest

safety in railway systems
anomaly detection for dynamic and evolving systems
anomaly-based intrusion detection
crisis management systems