8 research outputs found
Data-Driven Approach based on Deep Learning and Probabilistic Models for PHY-Layer Security in AI-enabled Cognitive Radio IoT.
PhD Theses.Cognitive Radio Internet of Things (CR-IoT) has revolutionized almost every eld of life
and reshaped the technological world. Several tiny devices are seamlessly connected in
a CR-IoT network to perform various tasks in many applications. Nevertheless, CR-IoT
su ers from malicious attacks that pulverize communication and perturb network performance.
Therefore, recently it is envisaged to introduce higher-level Arti cial Intelligence
(AI) by incorporating Self-Awareness (SA) capabilities into CR-IoT objects to facilitate
CR-IoT networks to establish secure transmission against vicious attacks autonomously.
In this context, sub-band information from the Orthogonal Frequency Division Multiplexing
(OFDM) modulated transmission in the spectrum has been extracted from the
radio device receiver terminal, and a generalized state vector (GS) is formed containing
low dimension in-phase and quadrature components. Accordingly, a probabilistic method
based on learning a switching Dynamic Bayesian Network (DBN) from OFDM transmission
with no abnormalities has been proposed to statistically model signal behaviors
inside the CR-IoT spectrum. A Bayesian lter, Markov Jump Particle Filter (MJPF),
is implemented to perform state estimation and capture malicious attacks.
Subsequently, GS containing a higher number of subcarriers has been investigated. In
this connection, Variational autoencoders (VAE) is used as a deep learning technique
to extract features from high dimension radio signals into low dimension latent space
z, and DBN is learned based on GS containing latent space data. Afterward, to perform
state estimation and capture abnormalities in a spectrum, Adapted-Markov Jump
Particle Filter (A-MJPF) is deployed. The proposed method can capture anomaly that
appears due to either jammer attacks in transmission or cognitive devices in a network
experiencing di erent transmission sources that have not been observed previously. The
performance is assessed using the receiver
Actas de las VI Jornadas Nacionales (JNIC2021 LIVE)
Estas jornadas se han convertido en un foro de encuentro de los actores más relevantes en el ámbito de la ciberseguridad en España. En ellas, no sólo se presentan algunos de los trabajos científicos punteros en las diversas áreas de ciberseguridad, sino que se presta especial atención a la formación e innovación educativa en materia de ciberseguridad, y también a la conexión con la industria, a través de propuestas de transferencia de tecnología. Tanto es así que, este año se presentan en el Programa de Transferencia algunas modificaciones sobre su funcionamiento y desarrollo que han sido diseñadas con la intención de mejorarlo y hacerlo más valioso para toda la comunidad investigadora en ciberseguridad
The Border of Lights Reader
Border of Lights, a volunteer collective, returns each October to Dominican-Haitian border towns to bear witness to the 1937 Haitian Massacre ordered by Dominican dictator Rafael Leónidas Trujillo. This crime against humanity has never been acknowledged by the Dominican government and no memorial exists for its victims. A multimodal, multi-vocal space for activists, artists, scholars, and others connected to the BOL movement, The Border of Lights Reader provides an alternative to the dominant narrative that positions Dominicans and Haitians as eternal adversaries and ignores cross-border and collaborative histories. This innovative anthology asks large-scale, universal questions regarding historical memory and revisionism that countries around the world grapple with today