Personal information

Italy

Biography

I work as research fellow at the Institute of Informatics and Telematics (IIT) of the National Research Council (CNR) in Pisa (Italy), and I am also a PhD student at the Computer Science Department of the University of Pisa.
My field of research is the Cybersecurity, and my research interests include Software Testing, Malware Analysis, Formal Methods and Machine Learning applied to cybersecurity problems, and Explainable AI.

Activities

Employment (2)

Università degli Studi di Pisa: Pisa, Toscana, IT

2019-10 to present | PhD student (Computer Science)
Employment
Source: Self-asserted source
Giacomo Iadarola

National Research Council: Pisa, IT

2019-01 to present (Institute of Informatics and Telematics (IIT))
Employment
Source: Self-asserted source
Giacomo Iadarola

Education and qualifications (3)

Technische Universitat Darmstadt: Darmstadt, Hessen, DE

2017-09 to 2018-09 | Master Degree (2nd Year) (Computer Science)
Education
Source: Self-asserted source
Giacomo Iadarola

University of Twente: Enschede, NL

2016-08 to 2017-07 | Master Degree (1st Year) (Computer Science)
Education
Source: Self-asserted source
Giacomo Iadarola

Università degli Studi di Pisa: Pisa, Toscana, IT

2012-09 to 2016-07 | Bachelor Degree (Computer Science)
Education
Source: Self-asserted source
Giacomo Iadarola

Works (8)

Assessing Deep Learning Predictions in Image-Based Malware Detection with Activation Maps

2023 | Book chapter
Contributors: Giacomo Iadarola; Francesco Mercaldo; Fabio Martinelli; Antonella Santone
Source: check_circle
Crossref

Towards Explainable Quantum Machine Learning for Mobile Malware Detection and Classification

Applied Sciences
2022-11-24 | Journal article
Contributors: Francesco Mercaldo; Giovanni Ciaramella; Giacomo Iadarola; Marco Storto; Fabio Martinelli; Antonella Santone
Source: check_circle
Crossref
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Preferred source (of 2)‎

Towards an interpretable deep learning model for mobile malware detection and family identification

Computers & Security
2021-06 | Journal article
Contributors: Giacomo Iadarola; Fabio Martinelli; Francesco Mercaldo; Antonella Santone
Source: check_circle
Crossref

Evaluating Deep Learning Classification Reliability in Android Malware Family Detection

2020 IEEE International Symposium on Software Reliability Engineering Workshops (ISSREW)
2020 | Conference paper
Source: Self-asserted source
Giacomo Iadarola

Image-based Malware Family Detection: An Assessment between Feature Extraction and Classification Techniques.

IoTBDS
2020 | Conference paper
Source: Self-asserted source
Giacomo Iadarola

Call Graph and Model Checking for Fine-Grained Android Malicious Behaviour Detection

Applied Sciences
2020-11-10 | Journal article
Contributors: Giacomo Iadarola; Fabio Martinelli; Francesco Mercaldo; Antonella Santone
Source: check_circle
Crossref
grade
Preferred source (of 2)‎

Formal Methods for Android Banking Malware Analysis and Detection

2019 Sixth International Conference on Internet of Things: Systems, Management and Security (IOTSMS)
2019 | Conference paper
Source: Self-asserted source
Giacomo Iadarola

Graph-based classification for detecting instances of bug patterns

2018 | Supervised student publication
Source: Self-asserted source
Giacomo Iadarola