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Found 7 papers, 3 papers with code
Graph Neural Networks for Jamming Source Localization
Graph-based learning has emerged as a transformative approach for modeling complex relationships across diverse domains, yet its potential in wireless security remains largely unexplored.
3D Gaussian Splat Vulnerabilities
With 3D Gaussian Splatting (3DGS) being increasingly used in safety-critical applications, how can an adversary manipulate the scene to cause harm?
Learning Compact and Robust Representations for Anomaly Detection
We address these limitations by proposing a contrastive pretext task for anomaly detection that enforces three key properties: (1) compact ID clustering to reduce intra-class variance, (2) inlier-outlier separation to enhance inter-class separation, and (3) outlier-outlier separation to maintain diversity among synthetic outliers and prevent representation collapse.
Non-Robust Features are Not Always Useful in One-Class Classification
The robustness of machine learning models has been questioned by the existence of adversarial examples.
TII-SSRC-23 Dataset: Typological Exploration of Diverse Traffic Patterns for Intrusion Detection
The effectiveness of network intrusion detection systems, predominantly based on machine learning, are highly influenced by the dataset they are trained on.
Ranked #1 on
Anomaly Detection
on TII-SSRC-23
ARCADE: Adversarially Regularized Convolutional Autoencoder for Network Anomaly Detection
With a convolutional \ac{AE}, ARCADE automatically builds a profile of the normal traffic using a subset of raw bytes of a few initial packets of network flows so that potential network anomalies and intrusions can be efficiently detected before they cause more damage to the network.
Metaheuristics for the Online Printing Shop Scheduling Problem
This challenging real scheduling problem, that emerged in the nowadays printing industry, corresponds to a flexible job shop scheduling problem with sequencing flexibility; and it presents several complicating specificities such as resumable operations, periods of unavailability of the machines, sequence-dependent setup times, partial overlapping between operations with precedence constraints, and fixed operations, among others.
