Organization sPecific Threat Intelligence Mining and sharing

Informations projet

OPTIMA

N° de convention de subvention: 101063107

DOI

10.3030/101063107

Projet clôturé

Date de signature de la CE 11 Juillet 2022

Date de début 1 Decembre 2022

Date de fin 31 Mars 2025

Financé au titre de

• Marie Skłodowska-Curie Actions (MSCA)

Coût total

Aucune donnée

Contribution de l’UE

€ 188 590,08

Coordonné par

UNIVERSITA DEGLI STUDI DI PADOVA
Italy

CORDIS fournit des liens vers les livrables publics et les publications des projets HORIZON.

Les liens vers les livrables et les publications des projets du 7e PC, ainsi que les liens vers certains types de résultats spécifiques tels que les jeux de données et les logiciels, sont récupérés dynamiquement sur OpenAIRE .

Livrables

Data Management Plan (1)

Data Management Plan

The Data Management Plan describes the data management life cycle for all data sets that will be collected processed or generated by the action It is a document describing what data will be collected processed or generated and following what methodology and standards whether and how this data will be shared andor made open and how it will be curated and preserved

Documents, reports (1)

Communication, Dissemination & Outreach Plan

The plan describes the planned measures to maximize the impact of the project, including the dissemination and exploitation measures that are planned, and the target group(s) addressed. Regarding communication measures and public engagement strategy, the aim is to inform and reach out to society and show the activities performed, and the use and the benefits the project will have for citizens

Publications

Peer reviewed articles (11)

Effectiveness of machine learning based android malware detectors against adversarial attacks

Auteurs: Jyothish, A., Mathew, A. & Vinod, P
Publié dans: Cluster Computing, 2023, ISSN 1573-7543
Éditeur: Springer
DOI: 10.1007/s10586-023-04086-8

Computer Communications

Auteurs: Sameera, K. M., Serena Nicolazzo, Marco Arazzi, Antonino Nocera, Rafidha Rehiman KA, P. Vinod, and Mauro Conti.
Publié dans: Computer Communications, 2024, ISSN 0140-3664
Éditeur: Elsevier BV
DOI: 10.1016/j.comcom.2024.04.024

vDefender: An explainable and introspection-based approach for identifying emerging malware behaviour at hypervisor-layer in virtualization environment

Auteurs: Avantika Gaur, Preeti Mishra, Vinod P., Arjun Singh, Vijay Varadharajan, Uday Tupakula, Mauro Conti
Publié dans: Computers and Electrical Engineering, Numéro 120, 2024, ISSN 0045-7906
Éditeur: Elsevier BV
DOI: 10.1016/j.compeleceng.2024.109742

SecDefender: Detecting low-quality models in multidomain federated learning systems

Auteurs: Sameera K.M., Arnaldo Sgueglia, Vinod P., Rafidha Rehiman K.A., Corrado Aaron Visaggio, Andrea Di Sorbo, Mauro Conti
Publié dans: Future Generation Computer Systems, Numéro 164, 2024, ISSN 0167-739X
Éditeur: Elsevier BV
DOI: 10.1016/j.future.2024.107587

Deep learning fusion for effective malware detection: leveraging visual features

Auteurs: Jahez Abraham Johny, K. A. Asmitha, P. Vinod, G. Radhamani, K. A. Rafidha Rehiman, Mauro Conti
Publié dans: Cluster Computing, Numéro 28, 2024, ISSN 1386-7857
Éditeur: Springer Science and Business Media LLC
DOI: 10.1007/s10586-024-04723-w

Android malware defense through a hybrid multi-modal approach

Auteurs: Asmitha K.A., Vinod P., Rafidha Rehiman K.A., Neeraj Raveendran, Mauro Conti
Publié dans: Journal of Network and Computer Applications, Numéro 233, 2024, ISSN 1084-8045
Éditeur: Elsevier BV
DOI: 10.1016/j.jnca.2024.104035

Through the static: Demystifying malware visualization via explainability

Auteurs: Matteo Brosolo, Vinod P., Mauro Conti
Publié dans: Journal of Information Security and Applications, Numéro 91, 2025, ISSN 2214-2126
Éditeur: Elsevier BV
DOI: 10.1016/J.JISA.2025.104063

Deep learning vs. adversarial noise: a battle in malware image analysis

Auteurs: Asmitha, K. A., Vinod Puthuvath, K. A. Rafidha Rehiman, and S. L. Ananth.
Publié dans: Cluster Computing, 2024, ISSN 1573-7543
Éditeur: Springer
DOI: 10.1007/s10586-024-04397-4

OSTIS: A novel Organization-Specific Threat Intelligence System

Auteurs: Dincy R. Arikkat, Vinod P., Rafidha Rehiman K.A., Serena Nicolazzo, Antonino Nocera, Georgiana Timpau, Mauro Conti
Publié dans: Computers & Security, Numéro 145, 2024, ISSN 0167-4048
Éditeur: Elsevier BV
DOI: 10.1016/j.cose.2024.103990

LFGurad: A Defense against Label Flipping Attack in Federated Learning for Vehicular Network

Auteurs: Sameera K.M., Vinod P., Rafidha Rehiman K.A., Mauro Conti
Publié dans: Computer Networks, Numéro 254, 2024, ISSN 1389-1286
Éditeur: Elsevier BV
DOI: 10.1016/j.comnet.2024.110768

SeCTIS: A framework to Secure CTI Sharing

Auteurs: Dincy R. Arikkat, Mert Cihangiroglu, Mauro Conti, Rafidha Rehiman K.A., Serena Nicolazzo, Antonino Nocera, Vinod P.
Publié dans: Future Generation Computer Systems, Numéro 164, 2024, ISSN 0167-739X
Éditeur: Elsevier BV
DOI: 10.1016/j.future.2024.107562

Conference proceedings (3)

Interpretable PDF Malware Detector

Auteurs: Sneha Rajagopal C.H.M.M College For Advanced Studies, Trivandrum, Kerala, India ; Avanthika Gaur; P. Vinod
Publié dans: SINCONF, 2023, ISBN 979-8-3503-4321-2
Éditeur: IEEE
DOI: 10.1109/SIN60469.2023.10474653

Relation Extraction Techniques in Cyber Threat Intelligence

Auteurs: Dincy R. Arikkat, P. Vinod, Rafidha Rehiman K. A., Serena Nicolazzo, Antonino Nocera, Mauro Conti
Publié dans: Lecture Notes in Computer Science, Natural Language Processing and Information Systems, 2024
Éditeur: Springer Nature Switzerland
DOI: 10.1007/978-3-031-70239-6_24

SoK: Visualization-based Malware Detection Techniques

Auteurs: Matteo Brosolo, Vinod Puthuvath, Asmitha KA, Rafidha Rehiman, Mauro Conti
Publié dans: Proceedings of the 19th International Conference on Availability, Reliability and Security, 2025
Éditeur: ACM
DOI: 10.1145/3664476.3664514