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Tommaso Zoppi
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2020 – today
- 2024
- [j16]Tommaso Zoppi
, Stefano Gazzini, Andrea Ceccarelli
Anomaly-based error and intrusion detection in tabular data: No DNN outperforms tree-based classifiers. Future Gener. Comput. Syst. 160: 951-965 (2024) - [c29]Tommaso Puccetti, Tommaso Zoppi, Andrea Ceccarelli:
On attacks (dis)similarities to test adversarial defense: can we reduce the attack set? ITASEC 2024 - [c28]Tommaso Zoppi
Position Paper - Bringing Classifiers into Critical Systems: Are We Barking up the Wrong Tree? SAFECOMP (Workshops) 2024: 351-357 - [i6]Tommaso Puccetti, Simone Nardi, Cosimo Cinquilli, Tommaso Zoppi, Andrea Ceccarelli:
ROSpace: Intrusion Detection Dataset for a ROS2-Based Cyber-Physical System. CoRR abs/2402.08468 (2024) - [i5]Simona Bernardi, Tommaso Zoppi:
Fast Abstracts and Student Forum Proceedings - EDCC 2024 - 19th European Dependable Computing Conference. CoRR abs/2404.17465 (2024) - 2023
- [j15]Muhammad Atif
Tolerate Failures of the Visual Camera With Robust Image Classifiers. IEEE Access 11: 5132-5143 (2023) - [j14]Tommaso Zoppi
Which algorithm can detect unknown attacks? Comparison of supervised, unsupervised and meta-learning algorithms for intrusion detection. Comput. Secur. 127: 103107 (2023) - [j13]Tommaso Zoppi
Safe Maintenance of Railways using COTS Mobile Devices: The Remote Worker Dashboard. ACM Trans. Cyber Phys. Syst. 7(4): 25:1-25:20 (2023) - [c27]Tommaso Zoppi
Ensembling Uncertainty Measures to Improve Safety of Black-Box Classifiers. ECAI 2023: 3156-3164 - [c26]Andrea Ceccarelli
Intrusion detection without attack knowledge: generating out-of-distribution tabular data. ISSRE 2023: 125-136 - [c25]Tommaso Zoppi, Giovanni Merlino, Andrea Ceccarelli
Anomaly Detectors for Self-Aware Edge and IoT Devices. QRS 2023: 24-35 - [c24]Tommaso Puccetti
Detection of Adversarial Attacks by Observing Deep Features with Structured Data Algorithms. SAC 2023: 125-134 - [i4]Tommaso Puccetti, Tommaso Zoppi, Andrea Ceccarelli:
On the Efficacy of Metrics to Describe Adversarial Attacks. CoRR abs/2301.13028 (2023) - [i3]Tommaso Zoppi, Andrea Ceccarelli, Andrea Bondavalli:
Ensembling Uncertainty Measures to Improve Safety of Black-Box Classifiers. CoRR abs/2308.12065 (2023) - 2022
- [j12]Muhammad Atif
Towards Enhancing Traffic Sign Recognition through Sliding Windows. Sensors 22(7): 2683 (2022) - [j11]Mohamad Gharib
On the Properness of Incorporating Binary Classification Machine Learning Algorithms Into Safety-Critical Systems. IEEE Trans. Emerg. Top. Comput. 10(4): 1671-1686 (2022) - [c23]Tommaso Zoppi
Towards a General Model for Intrusion Detection: An Exploratory Study. PKDD/ECML Workshops (2) 2022: 186-201 - [i2]Tommaso Zoppi, Andrea Ceccarelli:
Prepare for Trouble and Make it Double. Supervised and Unsupervised Stacking for AnomalyBased Intrusion Detection. CoRR abs/2202.13611 (2022) - 2021
- [j10]Tommaso Zoppi
Unsupervised Algorithms to Detect Zero-Day Attacks: Strategy and Application. IEEE Access 9: 90603-90615 (2021) - [j9]Tommaso Zoppi
Detect Adversarial Attacks Against Deep Neural Networks With GPU Monitoring. IEEE Access 9: 150579-150591 (2021) - [j8]Duccio Bertieri
Development and validation of a safe communication protocol compliant to railway standards. J. Braz. Comput. Soc. 27(1): 5 (2021) - [j7]Tommaso Zoppi
Prepare for trouble and make it double! Supervised - Unsupervised stacking for anomaly-based intrusion detection. J. Netw. Comput. Appl. 189: 103106 (2021) - [j6]Tommaso Zoppi, Mohamad Gharib
Meta-Learning to Improve Unsupervised Intrusion Detection in Cyber-Physical Systems. ACM Trans. Cyber Phys. Syst. 5(4): 42:1-42:27 (2021) - [j5]Tommaso Zoppi
Unsupervised Anomaly Detectors to Detect Intrusions in the Current Threat Landscape. Trans. Data Sci. 2(2): 7:1-7:26 (2021) - [j4]Tommaso Zoppi
MADneSs: A Multi-Layer Anomaly Detection Framework for Complex Dynamic Systems. IEEE Trans. Dependable Secur. Comput. 18(2): 796-809 (2021) - [c22]Tommaso Zoppi, Enrico Schiavone, Irene Bicchierai, Francesco Brancati, Andrea Bondavalli:
Spoofing Detectability as a Property of Biometric Characteristics. ITASEC 2021: 92-105 - [c21]Tommaso Zoppi, Andrea Ceccarelli
Feature Rankers to Predict Classification Performance of Unsupervised Intrusion Detectors. LADC 2021: 1-9 - [c20]Tommaso Zoppi, Andrea Ceccarelli
Detecting Intrusions by Voting Diverse Machine Learners: Is It Really Worth? PRDC 2021: 57-66 - [c19]Muhammad Atif, Tommaso Zoppi, Mohamad Gharib
Quantitative comparison of supervised algorithms and feature sets for traffic sign recognition. SAC 2021: 174-177 - [c18]Mohamad Gharib
Understanding the properness of incorporating machine learning algorithms in safety-critical systems. SAC 2021: 232-234 - 2020
- [j3]Tommaso Zoppi
On the educated selection of unsupervised algorithms via attacks and anomaly classes. J. Inf. Secur. Appl. 52: 102474 (2020) - [c17]Tommaso Zoppi
Into the Unknown: Unsupervised Machine Learning Algorithms for Anomaly-Based Intrusion Detection. DSN (Supplements) 2020: 81 - [i1]Tommaso Zoppi, Andrea Ceccarelli, Tommaso Capecchi, Andrea Bondavalli:
Unsupervised Anomaly Detectors to Detect Intrusions in the Current Threat Landscape. CoRR abs/2012.11354 (2020)
2010 – 2019
- 2019
- [j2]Andrea Ceccarelli
Threat Analysis in Systems-of-Systems: An Emergence-Oriented Approach. ACM Trans. Cyber Phys. Syst. 3(2): 18:1-18:24 (2019) - [c16]Tommaso Zoppi
Evaluation of Anomaly Detection Algorithms Made Easy with RELOAD. ISSRE 2019: 446-455 - [c15]Duccio Bertieri, Tommaso Zoppi
Practical Experience Report: Implementation, Verification and Validation of a Safe and Secure Communication Protocol for the Railway Domain. LADC 2019: 1-6 - [c14]Filipe Falcão, Tommaso Zoppi
Quantitative comparison of unsupervised anomaly detection algorithms for intrusion detection. SAC 2019: 318-327 - [c13]Tommaso Zoppi
An Initial Investigation on Sliding Windows for Anomaly-Based Intrusion Detection. SERVICES 2019: 99-104 - 2018
- [j1]Tommaso Zoppi
Labelling relevant events to support the crisis management operator. J. Softw. Evol. Process. 30(3) (2018) - [c12]Tommaso Zoppi
On Algorithms Selection for Unsupervised Anomaly Detection. PRDC 2018: 279-288 - 2017
- [c11]Alexandr Vasenev, Dan Ionita, Tommaso Zoppi, Andrea Ceccarelli, Roel J. Wieringa:
Towards Security Requirements: Iconicity as a Feature of an Informal Modeling Language. REFSQ Workshops 2017 - [c10]Tommaso Zoppi
Exploring anomaly detection in systems of systems. SAC 2017: 1139-1146 - [c9]Tommaso Zoppi
A Tool for Evolutionary Threat Analysis of Smart Grids. SmartGIFT 2017: 205-211 - [c8]Tommaso Zoppi
A Modeling Framework to Support Resilient Evolution Planning of Smart Grids. SmartGIFT 2017: 233-242 - 2016
- [c7]Tommaso Zoppi
Presenting the Proper Data to the Crisis Management Operator: A Relevance Labelling Strategy. HASE 2016: 228-235 - [c6]Tommaso Zoppi
Context-Awareness to Improve Anomaly Detection in Dynamic Service Oriented Architectures. SAFECOMP 2016: 145-158 - [c5]Tommaso Zoppi
Challenging Anomaly Detection in Complex Dynamic Systems. SRDS 2016: 213-214 - [c4]Marco Mori, Andrea Ceccarelli
On the impact of emergent properties on SoS security. SoSE 2016: 1-6 - 2015
- [c3]Andrea Ceccarelli
A Multi-layer Anomaly Detector for Dynamic Service-Based Systems. SAFECOMP 2015: 166-180 - 2014
- [c2]Andrea Ceccarelli
A Testbed for Evaluating Anomaly Detection Monitors through Fault Injection. ISORC 2014: 358-365
2000 – 2009
- 2006
- [c1]Andrea D'Andrea, Giulia Marchese, Tommaso Zoppi:
Ontological Modelling for Archaeological Data. VAST 2006: 211-218
Coauthor Index
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last updated on 2024-10-07 22:18 CEST by the dblp team
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