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Cyber-Physical Systems Virtual Organization
Read-only archive of site from September 29, 2023.
CPS-VO
security checks
biblio
Fraud Detection using Machine Learning and Deep Learning
Submitted by aekwall on Mon, 08/24/2020 - 12:37pm
credit card
Europe
Forestry
Credit cards
area under the ROC curve
Australian dataset
autoencoder
benchmark multiple machine learning methods
Boltzmann machines
cost of failure
financial data processing
data mining techniques
Deep belief networks
EU
European dataset
German dataset
k nearest neighbor
Matthews correlation coefficient
restricted boltzmann machine
security checks
pattern classification
Support vector machines
support vector machine
learning (artificial intelligence)
machine learning
Random Forest
Resiliency
pubcrawl
composability
deep learning
Data models
convolutional neural nets
deep learning methods
Data mining
convolutional neural networks
Artificial Neural Networks
belief networks
fraud
fraud detection
biblio
SeqFuzzer: An Industrial Protocol Fuzzing Framework from a Deep Learning Perspective
Submitted by grigby1 on Fri, 04/03/2020 - 11:43am
Protocols
learning (artificial intelligence)
Local area networks
modern industrial control systems
Policy Based Governance
policy-based governance
privacy
protocol frame structures
protocol frames
protocol verification
Industrial Safety
pubcrawl
security
security checks
security vulnerabilities
self learning
SeqFuzzer
stateful protocols
target protocol
vulnerability mining
deep learning perspective
composability
Compositionality
computer architecture
computer network security
Control Automation Technology devices
Data models
Decoding
deep learning
deep learning model
collaboration
EtherCAT
Fuzz Testing
fuzzing
fuzzing framework
industrial communication processes
industrial communication protocols
industrial network
industrial protocol fuzzing framework
