learning (artificial intelligence)

biblio

Towards Deep Federated Defenses Against Malware in Cloud Ecosystems

Submitted by grigby1 on Fri, 12/11/2020 - 2:33pm

neural nets
machine learning
machine learning models
malware
Malware Analysis
malware containment
malware detection
Malware-Detection-Cloud-Computing-Graph-Neural-Networks-Federated-Learning-Multicloud-Natural-Language-Processing
Metrics
learning (artificial intelligence)
privacy
Privacy Requirements
pubcrawl
resilience
Resiliency
Task Analysis
Training
virtual machines
feature representation
Biological system modeling
Bit error rate
Cloud Computing
cloud computing environments
cloud-specific optimization problems
data privacy
deep federated defenses
feature extraction
attentional sequence models
federated learning
graph neural networks
graph theory
Human behavior
hypergraph learning models
inductive graph
invasive software

biblio

AMDroid: Android Malware Detection Using Function Call Graphs

Submitted by grigby1 on Fri, 12/11/2020 - 2:32pm

learning (artificial intelligence)
structural semantic learning
static analysis
smart phones
Semantics
Resiliency
resilience
pubcrawl
privacy
opcode sequences
mobile operating system
mobile internet
Metrics
Malware Analysis
malware
machine learning
AMDroid
Kernel
invasive software
Human behavior
graph theory
graph kernels
function call graphs
function call graph
feature extraction
FCGs
countless malicious applications
application program interfaces
API calls
Android Malware Detection
Android (operating system)

biblio

Adversarial Learning Attacks on Graph-based IoT Malware Detection Systems

Submitted by grigby1 on Fri, 12/11/2020 - 2:32pm

privacy
invasive software
IoT malware samples
learning (artificial intelligence)
malware
Malware Analysis
malware detection
Metrics
off-the-shelf adversarial attack methods
Internet of Things
pubcrawl
resilience
Resiliency
robust detection tools
security
static analysis
tools
adversarial learning
Human behavior
graph-based IoT malware detection systems
graph theory
graph embedding
graph analysis
generated adversarial sample
GEA approach
feature extraction
deep learning networks
deep learning
craft adversarial IoT software
control flow graph-based features
CFG-based features
benign sample
augmentation method

biblio

Graph Embedding Based Familial Analysis of Android Malware using Unsupervised Learning

Submitted by grigby1 on Fri, 12/11/2020 - 2:32pm

Malware Analysis
Unsupervised Learning
supervised learning
SRA
smart phones
similarity relationships
Semantics
security
Resiliency
resilience
pubcrawl
privacy
pattern clustering
pattern classification
Metrics
malware link network
analytical workload
malware
learning (artificial intelligence)
invasive software
Human behavior
graph theory
graph embedding techniques
graph embedding
GefDroid
feature extraction
familial analysis
Face
detection algorithms
application program interfaces
Android malware

biblio

Fidelity: Towards Measuring the Trustworthiness of Neural Network Classification

Submitted by aekwall on Mon, 12/07/2020 - 12:32pm

pattern classification
security-critical tasks
neural network system
neural network classification
adversarial settings
adversarial attack detection
adversarial examples
Perturbation methods
trustworthiness
machine learning model
machine learning
security of data
Neural networks
neural nets
Statistics
Sociology
Computational modeling
composability
pubcrawl
learning (artificial intelligence)
Trusted Computing
Task Analysis

biblio

Measuring Trustworthiness of IoT Image Sensor Data Using Other Sensors’ Complementary Multimodal Data

Submitted by aekwall on Mon, 12/07/2020 - 12:31pm

uncertainty handling
trustworthy measure
temperature sensor data
numerical data
multimodal
IoT sensor data
IoT image sensor data
image sensors
image sensor data
DST framework
Dempster-Shafer Theory
complementary multimodal data
authentic forged image data
Temperature distribution
Temperature sensors
security of data
Numerical models
inference mechanisms
Internet of Things applications
sensor fusion
trustworthiness
trust
composability
pubcrawl
learning (artificial intelligence)
Data models
Trusted Computing
IoT applications
Internet of Things

biblio

Separating Style and Content for Generalized Style Transfer

Submitted by aekwall on Mon, 12/07/2020 - 12:11pm

Gallium nitride
Training
style reference images
style encoder
Silicon
neural nets
multitask learning scenario
Mixers
learning (artificial intelligence)
learned model
image representation
Image coding
Generators
generalized style transfer network
neural style transfer
feature extraction
Decoding
decoder
convolution
content reference images
content encoder
Chinese Typeface transfer problem
bilinear model
pubcrawl
Predictive Metrics
Resiliency
Scalability

biblio

Image Style Transfer in Deep Learning Networks

Submitted by aekwall on Mon, 12/07/2020 - 12:11pm

convolution neural network
Semantics
Painting
Neural networks
learning (artificial intelligence)
images contents
image style transfer
image recognition
Image color analysis
deep learning network development process
deep learning
convolutional neural nets
neural style transfer
computer vision researchers
computer vision
CNN
classical style migration model
artistic styles
ART
pubcrawl
Predictive Metrics
Resiliency
Scalability

biblio

Image Style Transfer with Multi-target Loss for loT Applications

Submitted by aekwall on Mon, 12/07/2020 - 12:10pm

fundamental problem
visualization
pre-trained deep convolutional neural network VGG19
output image
neural nets
multitarget loss
loss function
learning (artificial intelligence)
input style image
input images
Information filters
image style transfer
Image reconstruction
gradient methods
neural style transfer
Filter banks
feature map
feature extraction
context image
content style
computer vision
artistic images
arbitrary images
pubcrawl
Predictive Metrics
Resiliency
Scalability

biblio

Flexible Selecting of Style to Content Ratio in Neural Style Transfer

Submitted by aekwall on Mon, 12/07/2020 - 12:09pm

learning (artificial intelligence)
weight ratio selection
user defined style weight ratio
texture synthesis
style transfer
style image selection
Scalability
Resiliency
Predictive Metrics
optimization
neural style transfer
Neural networks
pubcrawl
image texture
Image color analysis
Feature Selection
feature extraction
convolutional neural networks
convolutional neural nets
convolution neural networks
convolution
content ratio
Artificial Intelligence
ART

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Cyber-Physical Systems Virtual Organization

Read-only archive of site from September 29, 2023.

learning (artificial intelligence)

Towards Deep Federated Defenses Against Malware in Cloud Ecosystems

AMDroid: Android Malware Detection Using Function Call Graphs

Adversarial Learning Attacks on Graph-based IoT Malware Detection Systems

Graph Embedding Based Familial Analysis of Android Malware using Unsupervised Learning

Fidelity: Towards Measuring the Trustworthiness of Neural Network Classification

Measuring Trustworthiness of IoT Image Sensor Data Using Other Sensors’ Complementary Multimodal Data

Separating Style and Content for Generalized Style Transfer

Image Style Transfer in Deep Learning Networks

Image Style Transfer with Multi-target Loss for loT Applications

Flexible Selecting of Style to Content Ratio in Neural Style Transfer