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Cyber-Physical Systems Virtual Organization
Fostering collaboration among CPS professionals in academia, government, and industry
CPS-VO
machine learning
file
Sharif_Gen_framework_adv_examples_Bauer.pdf
Submitted by
Jamie Presken
on Mon, 07/08/2019 - 10:33am
Neural networks
machine learning
face recognition
adversarial examples
Safety Critical ML
biblio
A General Framework for Adversarial Examples with Objectives
Submitted by
Jamie Presken
on Mon, 07/08/2019 - 10:33am
adversarial examples
face recognition
machine learning
Neural networks
Metrics
Resilient Architectures
CMU
Safety Critical ML
2019: July
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
program debugging
Naive Bayes
Decision trees
security breaches
feedforward neural nets
Computer bugs
Metrics
Decision Tree
pubcrawl
multilayer deep feedforward network
Feedforward Artificial Network
deep learning technique
deep learning
Bug Propensity Correlational Analysis
software quality
Predictive models
Security Metrics
software security bugs
software quality metrics
software metrics
software insecurity
security-related bugs
Random Forest
machine learning
learning (artificial intelligence)
Support vector machines
Bayes methods
Software
security
security of data
biblio
Machine Learning for Reliable Network Attack Detection in SCADA Systems
Submitted by
aekwall
on Mon, 07/01/2019 - 10:10am
Anomaly Detection
composability
control engineering computing
critical infrastructures
data normalization
F1 score
gas pipeline system
Human behavior
Intrusion Detection Systems
learning (artificial intelligence)
machine learning
malicious intrusions
missing data estimation
network attack detection
network attacks
open SCADA protocols
Payloads
Pipelines
Protocols
pubcrawl
Random Forest
Resiliency
SCADA
SCADA systems
SCADA Systems Security
security of data
supervisory control and data acquisition systems
support vector machine
Support vector machines
SVM
Training
biblio
A Multi-Classifier Framework for Open Source Malware Forensics
Submitted by
grigby1
on Mon, 07/01/2019 - 10:06am
automated manner
Bayes methods
computer network security
computer viruses
cyber attack pattern
Cyber Attacks
data cleaning
Data mining
Data models
ever-evolving threats
extensive pre-modeling techniques
feature extraction
future cyber threats
Gaussian Naive Bayes classifier
heuristics updates
invasive software
learning (artificial intelligence)
machine learning
machine learning algorithms
machine learning models
malware
malware analysis reports
malware attacks
malware forensics
manual analysis
multiclassifier framework
open source malware forensics
open source malware sandbox
pattern classification
pubcrawl
resilience
Resiliency
Scalability
Security Heuristics
security of data
traditional anti-virus technologies
Training
biblio
Static and Dynamic Malware Analysis Using Machine Learning
Submitted by
aekwall
on Mon, 06/24/2019 - 2:41pm
APIs
application program interfaces
Binary
Classification algorithms
cuckoo sandbox
Data mining
DLLs
dynamic analysis
Dynamic Malware Analysis
evade
feature extraction
Human behavior
Internet oriented machines security
invasive software
learning (artificial intelligence)
machine learning
malware
Malware Analysis
malwares
Metrics
obfuscate
PEFILE
pubcrawl
registry keys changed
Resiliency
static analysis
static malware analysis
summary information
biblio
Low Power and Trusted Machine Learning
Submitted by
aekwall
on Mon, 06/17/2019 - 10:28am
neuromorphic hardware security
neuromorphic hardware acceleration
low power neuromorphic computing
composability
pubcrawl
machine learning
security scalability
biblio
Defending IT Systems against Intelligent Malware
Submitted by
grigby1
on Mon, 06/10/2019 - 2:02pm
adversarial examples
Antivirus Software vendors
ART
Classification algorithms
dynamic analysis
Gallium nitride
generative adversarial network
generative adversarial networks
Human behavior
intelligent malware
invasive software
IT systems
learning (artificial intelligence)
machine learning
machine learning algorithms
malware
Malware Analysis
malware binaries
malware classification
malware detection
malware families
malware images
malware variants
Metrics
neural nets
privacy
pubcrawl
resilience
Resiliency
Signatures
static analysis
Training
unsupervised deep neural networks
biblio
Intelligent Malware Detection Using Oblique Random Forest Paradigm
Submitted by
grigby1
on Mon, 06/10/2019 - 2:02pm
privacy
resilience
machine learning
pubcrawl
Human behavior
Metrics
feature extraction
invasive software
Trojan horses
learning (artificial intelligence)
Support vector machines
pattern classification
Decision trees
malware classification
Forestry
Resiliency
behavior-based detection techniques
classification accuracy
comprehensive malware detection
computerized online applications
decision tree learning models
false positive rate
intelligent malware detection
machine learning solutions
malware behavior
malware classification datasets
Oblique Random Forest
oblique random forest ensemble learning technique
oblique random forest paradigm
security community
signature-based detection techniques
stealthy malware
unknown malware
biblio
Classifying Malware Using Convolutional Gated Neural Network
Submitted by
grigby1
on Mon, 06/10/2019 - 2:01pm
privacy
resilience
pubcrawl
Human behavior
Metrics
invasive software
Task Analysis
convolutional neural networks
feedforward neural nets
machine learning
Logic gates
malware
pattern classification
malware detection
Recurrent neural networks
neural network
malware classification
CNN
Resiliency
recurrent neural nets
convolutional gated recurrent neural network model
Deep Neural Network
Gated Recurrent Unit
information technology society
malicious software
microsoft malware classification challenge
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