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Cyber-Physical Systems Virtual Organization
Fostering collaboration among CPS professionals in academia, government, and industry
CPS-VO
deep learning
biblio
Is Predicting Software Security Bugs Using Deep Learning Better Than the Traditional Machine Learning Algorithms?
Submitted by
aekwall
on Mon, 07/01/2019 - 10:14am
Bayes methods
Bug Propensity Correlational Analysis
Computer bugs
Decision Tree
Decision trees
deep learning
deep learning technique
Feedforward Artificial Network
feedforward neural nets
learning (artificial intelligence)
machine learning
Metrics
multilayer deep feedforward network
Naive Bayes
Predictive models
program debugging
pubcrawl
Random Forest
security
security breaches
Security Metrics
security of data
security-related bugs
Software
software insecurity
software metrics
software quality
software quality metrics
software security bugs
Support vector machines
biblio
Attack and Defense of Dynamic Analysis-Based, Adversarial Neural Malware Detection Models
Submitted by
aekwall
on Mon, 06/24/2019 - 2:43pm
adversarial attacks
adversarial learning
adversarial learning-based attacks
adversarial neural malware detection models
anti-malware companies
anti-malware engine
classification algorithm
computer security
crafting adversarial samples
deep learning
deep learning classification systems
deep learning-based systems
dynamic analysis-based
Dynamic Malware Classification
Engines
Human behavior
invasive software
Jacobian matrices
learning (artificial intelligence)
malware
Malware Analysis
malware classification accuracy
malware detection
Metrics
Neural networks
pattern classification
program diagnostics
pubcrawl
Resiliency
static analysis-based malware classifiers
Training
biblio
Malware Classification with Deep Convolutional Neural Networks
Submitted by
grigby1
on Mon, 06/10/2019 - 2:01pm
challenging malware classification datasets
CNN
computer architecture
convolution
convolutional neural networks
deep convolutional neural networks
deep learning
deep learning approach
deep learning framework
feedforward neural nets
Gray-scale
grayscale images
Human behavior
image classification
invasive software
learning (artificial intelligence)
Learning systems
machine learning
machine learning approaches
Malimg malware
malware
malware binaries
malware classification
Metrics
Microsoft malware
privacy
pubcrawl
resilience
Resiliency
Support vector machines
biblio
DLGraph: Malware Detection Using Deep Learning and Graph Embedding
Submitted by
grigby1
on Mon, 06/10/2019 - 1:59pm
application program interfaces
combined feature vector classification
deep learning
DLGraph
embedded systems
embedded vector
feature extraction
function-call graph
function-call graphs
graph embedding
graph theory
Human behavior
invasive software
learning (artificial intelligence)
Malware Analysis
malware detection
Metrics
microsoft windows
neural nets
noise reduction
pattern classification
privacy
pubcrawl
representation learning
Resiliency
SDA
softmax regression
stacked denoising autoencoders
static analysis
Trojan horses
Windows API calls
Windows application programming interface calls
biblio
Obfuscation Resilient Search Through Executable Classification
Submitted by
grigby1
on Mon, 06/10/2019 - 1:58pm
bytecode analysis
bytecode search
deep learning
executable search
graph theory
Human behavior
Malware Analysis
Metrics
obfuscation resilience
privacy
pubcrawl
Resiliency
biblio
Cloud Insider Attack Detection Using Machine Learning
Submitted by
grigby1
on Mon, 06/10/2019 - 1:56pm
Anomaly Detection
anomaly node
attackers
broken node
Cloud Computing
cloud insider attack detection
cloud network
cloud security issues
cloud user
composability
compromised node
Data models
data sources
deep learning
improvised long short-term memory model
internal attacker
internal attackers compromise
learning (artificial intelligence)
Logic gates
Long short-term memory
machine learning
machine learning approaches
malicious node
misbehaving node
Monitoring
privacy
pubcrawl
resilience
Resiliency
security
security approaches
security of data
short-term behavioral data
trusted users
User behavior
valuable information
vulnerable information
vulnerable user node
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
Anomaly Detection
anomaly detection evaluation dataset
composability
control engineering computing
Cyber Attacks
Data processing
Decision trees
deep learning
deep learning models
Feeds
ICs
ICS security
industrial control
industrial process anomaly detection task
learning (artificial intelligence)
linear algorithms
machine learning
machine learning algorithms
machine learning methods
modern industrial control systems
neural nets
Neural networks
privacy
production engineering computing
pubcrawl
resilience
Resiliency
security
security of data
signal correlations
Support vector machines
Tennessee Eastman process simulation data
Training
biblio
Optimal Machine Learning Algorithms for Cyber Threat Detection
Submitted by
grigby1
on Mon, 06/10/2019 - 1:56pm
advanced targeted cyber threats
Anomaly Detection
automated cyber threat detection
classification
Classification algorithms
Clustering algorithms
composability
cyber security
cyber threat detection model
Data mining
data science
Decision trees
deep learning
Dimensionality
efficient machine
Ensemble Learning
exponential hike
false detection rates
false-positive detections
global Security Operations Center environments
Kernel
learning (artificial intelligence)
Logistics
machine learning
machine learning algorithms
minimisation
ML-based analytics
Numerical Clustering
optimal machine learning algorithm
prediction
privacy
pubcrawl
Regression
resilience
Resiliency
security
security data
security log analytics
security logs
security machine data
security of data
SoC
biblio
Deep Learning Based Attribute Classification Insider Threat Detection for Data Security
Submitted by
aekwall
on Wed, 05/08/2019 - 9:49am
Anomaly Detection
attribute classification insider threat detection method
attribute classifiers
CERT insider threat dataset
Data Security
deep learning
end-to-end detection framework
feature extraction
high detection rate
Human behavior
insider threat
Kernel
learning (artificial intelligence)
Logic gates
long short term memory recurrent neural networks
machine learning
malicious insiders
Metrics
network threat
pattern classification
principal component analysis
Principal Component Analysis based threat detection methods
pubcrawl
recurrent neural nets
Recurrent neural networks
resilience
security of data
threat detection recall
biblio
Role-based Log Analysis Applying Deep Learning for Insider Threat Detection
Submitted by
aekwall
on Wed, 05/08/2019 - 9:46am
log data analysis
resilience
insider threat
Metrics
deep learning
pubcrawl
Human behavior
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