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Found 9 papers, 0 papers with code
CAN-BERT do it? Controller Area Network Intrusion Detection System based on BERT Language Model
Due to the rising number of sophisticated customer functionalities, electronic control units (ECUs) are increasingly integrated into modern automotive systems.
Unsupervised Network Intrusion Detection System for AVTP in Automotive Ethernet Networks
Hence, in this paper, we compare the performance of different unsupervised deep and machine learning based anomaly detection algorithms, for real-time detection of anomalies on the Audio Video Transport Protocol (AVTP), an application layer protocol implemented in the recent Automotive Ethernet based in-vehicle network.
SOME/IP Intrusion Detection using Deep Learning-based Sequential Models in Automotive Ethernet Networks
Intrusion Detection Systems are widely used to detect cyberattacks, especially on protocols vulnerable to hacking attacks such as SOME/IP.
Dual Optimization for Kolmogorov Model Learning Using Enhanced Gradient Descent
To make our method more scalable to large-dimensional problems, we propose two acceleration schemes, namely, the eigenvalue decomposition (EVD) elimination strategy and an approximate EVD algorithm.
Enhanced Beam Alignment for Millimeter Wave MIMO Systems: A Kolmogorov Model
We present an enhancement to the problem of beam alignment in millimeter wave (mmWave) multiple-input multiple-output (MIMO) systems, based on a modification of the machine learning-based criterion, called Kolmogorov model (KM), previously applied to the beam alignment problem.
A Hybrid Model-based and Data-driven Approach to Spectrum Sharing in mmWave Cellular Networks
Inter-operator spectrum sharing in millimeter-wave bands has the potential of substantially increasing the spectrum utilization and providing a larger bandwidth to individual user equipment at the expense of increasing inter-operator interference.
Learning Kolmogorov Models for Binary Random Variables
We summarize our recent findings, where we proposed a framework for learning a Kolmogorov model, for a collection of binary random variables.
BIG-bench Machine Learning
Interpretable Machine Learning
+1
A Unified Framework for Training Neural Networks
The lack of mathematical tractability of Deep Neural Networks (DNNs) has hindered progress towards having a unified convergence analysis of training algorithms, in the general setting.
Learning-Based Resource Allocation Scheme for TDD-Based CRAN System
Since, the trajectory of movement for high-mobility users is predictable; therefore, fairly accurate position estimates for those users can be obtained, and can be used for resource allocation to serve the considered users.
