A Novel Open Set Energy-based Flow Classifier for Network Intrusion Detection

Autor: Souza, Manuela M. C., Pontes, Camila, Gondim, Joao, Garcia, Luis P. F., DaSilva, Luiz, Marotta, Marcelo A.

Network intrusion detection systems (NIDS) are one of many solutions that make up a computer security system. Several machine learning-based NIDS have been proposed in recent years, but most of them were developed and evaluated under the assumption t

Externí odkaz: http://arxiv.org/abs/2109.11224

A new method for flow-based network intrusion detection using the inverse Potts model

Autor: Pontes, Camila, Souza, Manuela, Gondim, João, Bishop, Matt, Marotta, Marcelo

Publikováno v: IEEE Transactions on Network and Service Management (Volume: 18, Issue: 2, June 2021, Page(s): 1125-1136) Date of Publication: 26 April 2021

Network Intrusion Detection Systems (NIDS) play an important role as tools for identifying potential network threats. In the context of ever-increasing traffic volume on computer networks, flow-based NIDS arise as good solutions for real-time traffic

Externí odkaz: http://arxiv.org/abs/1910.07266

Unraveling the molecular basis of host cell receptor usage in SARS-CoV-2 and other human pathogenic β-CoVs

Autor: Pontes, Camila, Ruiz-Serra, Victoria, Lepore, Rosalba, Valencia, Alfonso

Publikováno v: In Computational and Structural Biotechnology Journal 2021 19:759-766

Addressing sex bias in biological databases worldwide

Autor: Pontes, Camila, Cirillo, Davide, Ruiz-Serra, Victoria, Saby, Diego, Cortés, Átia, Rambla, Jordi, Jené, Aina, Valencia, Alfonso, Andirkó, Alejandro, Rementeria, María, Philippe, Olivier, Holliday, Gemma, Buslón, Nataly, Moldes, Mauricio, Morales, María

Precision medicine aims at tailoring treatments to individual patient needs. In this context, artificial intelligence (AI)-based technologies are viewed as revolutionary since they have the capacity to identify key features that link genomic and phen

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::aa3b5e134bff0d4c8f5aa6bf56ae32a2
https://doi.org/10.37044/osf.io/n9dkg

The Bioinfo4Women Research Working Group on Sex and Gender Bias in Healthcare and AI

Autor: Cortés, Àtia, Buslón, Nataly, Cirillo, Davide, Serra, Victoria Ruiz, Saby, Diego, Uciel Chorostecki, Baghdadi, Fatemeh, Philippe, Olivier, Pontes, Camila, Morales, Maria, Dueso, Ana, Puch, Ignasi, Othmane Hayoun-Mya, Sopena-Rios, Maria, Roc Farriol, López, Lidia, Urda, Beatriz, Alloza, Eva, Rementeria, Maria José

A brief graphical description of the work carried out within the Research Working Group within the Bioinfo4Women initiative at the Barcelona Supercomputing Center.
Historically, scientific research has been led by and focused on males, and in th

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::1514ba80b8c77af938e33321f162516a