MEDIA
Company Profile
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Communication
Contact the communications office: comunicazionebvtech@bvtech.com
Publications
CNN-AutoMIC: Combining convolutional neural
network and autoencoder to learn non-linear features for knn-based malware image classification
Authors: Simone Andriani, Stefano Galantucci, Andrea Iannacone, Antonio Maci, Giuseppe Pirlo
Magazine: Computers Security
SIEVE: Generating a cybersecurity log dataset collection for SIEM event classification
Authors: Pierpaolo Artioli, Vincenzo Dentamaro, Stefano Galantucci, Alessio Magrì, Gianluca Pellegrini, Gianfranco Semeraro
Magazine: Computer Networks Volume 266
“CARIOCA: prioritizing the use of IoC by threats assessment shared on the MISP platform”
Authors: Piero Delvecchio, Stefano Galantucci, Andrea Iannacone & Giuseppe Pirlo
Magazine: International Journal of Information SecurityVolume 24, article number 98, 2025
News
The “CNN-AutoMIC” research report has been published
16/05/2025
The research report “CNN-AutoMIC: combining Convolutional Neural Network and Autoencoder to learn non-linear features for knn-based Malware Image Classification” has been published.
BV TECH take part at ASPC ’25
14/05/2025
As part of the Aerospace Power Conference 2025, BV TECH presented at its stand the results of some of the research activities of interest to the aerospace sector for both civil and military applications.
The “SIEVE” research report has been accepted for publication
22/04/2025
The research report “SIEVE: Cybersecurity Log Dataset Collection for SIEM Event Classification” has been accepted for publication in the prestigious first-rate scientific journal “Computer Networks”.
Events
Cyberchallenge 2024
29/06/2024 – 30/06/2024
Turin
Cybersecurity for Digital Transformation
16/12/2021
Bari – Conference Room Cruise Terminal Port of Bari
ITASEC21
7/04/2021 – 9/04/2021
Rome
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GROTTAGLIE:
Corso Europa, 3
74023 Grottaglie (TA)
Tel.: +39.02.8596171
Fax: +39.02.89093321
RUTIGLIANO:
S.P. 84 Adelfia-Rutigliano, C.da Caggiano
70018 Rutigliano (BA)
Tel.: +39.02.8596171
Fax: +39.02.89093321
Project funded by the European Regional Development Fund Puglia POR Puglia 2014 - 2020 - Axis I - Specific Objective 1a - Action 1.1 (R&D), and with the support of the University of Bari and the Massachusetts Institute of Technology (MIT).