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CORDIS

Cybersecurity for AI-Augmented Systems

CORDIS provides links to public deliverables and publications of HORIZON projects.

Links to deliverables and publications from FP7 projects, as well as links to some specific result types such as dataset and software, are dynamically retrieved from OpenAIRE .

Deliverables

Interim Open Science Results (opens in new window)

Description of the components available as Open Science (dataset) (T2.2).

Communication and Dissemination Strategy (opens in new window)

List of Sec4AI4Sec dissemination targets, channels and activities the project will use to reach them, and the related plan for each identified pathway (T2.1, T 2.2 and T2.3).

Sec4AI4Sec Integrated Toolflow Evaluation and Demonstration Plan – Report (opens in new window)

Framework for the execution of the demonstrations to be run in T7.2 to T7.4, defining KPIs for the evaluation of the toolflow.

Interim Report on Communication and Dissemination (opens in new window)

A report on general and pathway's dissemination and communication activities and results (T2.1, T2.2 and T2.3).

Initial Report on Evaluation of Trustworthy AI Models (opens in new window)

Taxonomy of attacks against AI models (T4.1, T4.2) O3.R6, O3.R7

Intermediate Report on the Assurance Methodologies for Products and Services (opens in new window)

Design and rules for security and gaps for AI/ML components (T6.1) O1.R1

ML-based Methods for Vulnerability Assessment - v1 (opens in new window)

Description of the projects approaches and tools for vulnerability assessment (T3.3) O5.R11

Repository Mining Toolkit -v1 (opens in new window)

Design and first implementation of the repository mining toolkit (T3.1) O2.R3, P3.1

Publications

Known Vulnerabilities of Open Source Projects: Where Are the Fixes? (opens in new window)

Author(s): Antonino Sabetta; Serena Elisa Ponta; Rocio Cabrera Lozoya; Michele Bezzi; Tommaso Sacchetti; Matteo Greco; Gergő Balogh; Péter Hegedűs; Rudolf Ferenc; Ranindya Paramitha; Ivan Pashchenko; Aurora Papotti; Ákos Milánkovich; Fabio Massacci
Published in: IEEE Security & Privacy, 2024, ISSN 1558-4046
Publisher: IEEE
DOI: 10.1109/msec.2023.3343836

On the acceptance by code reviewers of candidate security patches suggested by Automated Program Repair tools (opens in new window)

Author(s): Aurora Papotti, Ranindya Paramitha, Fabio Massacci
Published in: Empirical Software Engineering, Issue 29, 2024, ISSN 1382-3256
Publisher: Springer Science and Business Media LLC
DOI: 10.1007/s10664-024-10506-z

A Case-Control Study to Measure Behavioral Risks of Malware Encounters in Organizations (opens in new window)

Author(s): Marcello Meschini, Giorgio Di Tizio, Marco Balduzzi, Fabio Massacci
Published in: IEEE Transactions on Information Forensics and Security, Issue 19, 2024, ISSN 1556-6013
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
DOI: 10.1109/TIFS.2024.3456960

Addressing combinatorial experiments and scarcity of subjects by provably orthogonal and crossover experimental designs (opens in new window)

Author(s): Fabio Massacci, Aurora Papotti, Ranindya Paramitha
Published in: Journal of Systems and Software, Issue 211, 2024, ISSN 0164-1212
Publisher: Elsevier BV
DOI: 10.1016/j.jss.2024.111990

Technical leverage analysis in the Python ecosystem (opens in new window)

Author(s): Ranindya Paramitha, Fabio Massacci
Published in: Empirical Software Engineering, Issue 28, 2024, ISSN 1382-3256
Publisher: Springer Science and Business Media LLC
DOI: 10.1007/s10664-023-10355-2

HO-FMN: Hyperparameter optimization for fast minimum-norm attacks (opens in new window)

Author(s): Raffaele Mura, Giuseppe Floris, Luca Scionis, Giorgio Piras, Maura Pintor, Ambra Demontis, Giorgio Giacinto, Battista Biggio, Fabio Roli
Published in: Neurocomputing, Issue 616, 2024, ISSN 0925-2312
Publisher: Elsevier BV
DOI: 10.1016/j.neucom.2024.128918

APR4Vul: an empirical study of automatic program repair techniques on real-world Java vulnerabilities (opens in new window)

Author(s): Quang-Cuong Bui, Ranindya Paramitha, Duc-Ly Vu, Fabio Massacci, Riccardo Scandariato
Published in: Empirical Software Engineering, Issue 29, 2024, ISSN 1382-3256
Publisher: Springer Science and Business Media LLC
DOI: 10.1007/s10664-023-10415-7

Towards the Use of Domain Knowledge to Enhance Transformer-Based Vulnerability Detection (opens in new window)

Author(s): Alessandro Marchetto, Rosmaël Zidane Lekeufack Foulefack
Published in: Communications in Computer and Information Science, Quality of Information and Communications Technology, 2024
Publisher: Springer Nature Switzerland
DOI: 10.1007/978-3-031-70245-7_26

A Rapid Review on Graph-Based Learning Vulnerability Detection (opens in new window)

Author(s): Rosmaël Zidane Lekeufack Foulefack, Alessandro Marchetto
Published in: Communications in Computer and Information Science, Quality of Information and Communications Technology, 2024
Publisher: Springer Nature Switzerland
DOI: 10.1007/978-3-031-70245-7_25

Can explainability and deep-learning be used for localizing vulnerabilities in source code? (opens in new window)

Author(s): Alessandro Marchetto
Published in: Proceedings of the 5th ACM/IEEE International Conference on Automation of Software Test (AST 2024), 2024
Publisher: ACM
DOI: 10.1145/3644032.3644448

Hash4Patch: A Lightweight Low False Positive Tool for Finding Vulnerability Patch Commits (opens in new window)

Author(s): Simone Scalco, Ranindya Paramitha
Published in: Proceedings of the 21st International Conference on Mining Software Repositories, 2024
Publisher: ACM
DOI: 10.1145/3643991.3644871

Designing Secure AI-based Systems: a Multi-Vocal Literature Review (opens in new window)

Author(s): Simon Schneider, Ananya Saha, Emanuele Mezzi, Katja Tuma, Riccardo Scandariato
Published in: 2024 IEEE Secure Development Conference (SecDev), 2024
Publisher: IEEE
DOI: 10.1109/SecDev61143.2024.00007

Adversarial Testing with Reinforcement Learning: A Case Study on Autonomous Driving (opens in new window)

Author(s): Andréa Doreste, Matteo Biagiola, Paolo Tonella
Published in: 2024 IEEE Conference on Software Testing, Verification and Validation (ICST), 2024
Publisher: IEEE
DOI: 10.1109/ICST60714.2024.00034

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