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Cyber-Physical Systems Virtual Organization
Read-only archive of site from September 29, 2023.
CPS-VO
modern industrial control systems
biblio
SeqFuzzer: An Industrial Protocol Fuzzing Framework from a Deep Learning Perspective
Submitted by grigby1 on Fri, 04/03/2020 - 12:43pm
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
biblio
Research of Classical Machine Learning Methods and Deep Learning Models Effectiveness in Detecting Anomalies of Industrial Control System
Submitted by grigby1 on Mon, 06/10/2019 - 1:56pm
resilience
machine learning algorithms
machine learning methods
modern industrial control systems
neural nets
Neural networks
privacy
production engineering computing
pubcrawl
machine learning
Resiliency
security
security of data
signal correlations
Support vector machines
Tennessee Eastman process simulation data
Training
Anomaly Detection
linear algorithms
learning (artificial intelligence)
industrial process anomaly detection task
industrial control
ICS security
ICs
Feeds
deep learning models
deep learning
Decision trees
Data processing
Cyber Attacks
control engineering computing
composability
anomaly detection evaluation dataset
