Adversarial robust EEG-based brain-computer interfaces using a hierarchical convolutional neural network. [PDF]
Samuel J +5 more
europepmc +1 more source
Adversarial and Secure Machine Learning
We present the state-of-art study of a recent emerging research area named as Adversarial Machine Learning, it investigates the vulnerabilities of current learning algorithms from the perspective of an adversary. We show that several state-of-art learning systems are intrinsically vulnerable under carefully designed adversarial attacks.
openaire +1 more source
Robust detection framework for adversarial threats in Autonomous Vehicle Platooning. [PDF]
Ness S.
europepmc +1 more source
Detection of disturbances and cyber-attacks in smart grids using explainable machine learning. [PDF]
Farsi M +7 more
europepmc +1 more source
Adversarial susceptibility analysis for water quality prediction models. [PDF]
Zalte J, Rai A, Shah H, Fulekar MH.
europepmc +1 more source
Enhancing security in IoMT using federated TinyGAN for lightweight and accurate malware detection. [PDF]
S D, Shankar MG, Daniel E, R BGV.
europepmc +1 more source
Comprehensive analysis of security threats and privacy issues in indoor localization systems. [PDF]
Ayub A +6 more
europepmc +1 more source
Editorial: Machine learning and applied neuroscience, volume II. [PDF]
Dos Santos WP +3 more
europepmc +1 more source
Bearing Anomaly Detection Method Based on Multimodal Fusion and Self-Adversarial Learning. [PDF]
Liu H, Qin Y, Tu D.
europepmc +1 more source
Novel transformer-based model for NID in fog computing environment. [PDF]
Abdelnaby KM, Khedr AY, Elsemary AM.
europepmc +1 more source

