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Cyber-Physical Systems Virtual Organization
Fostering collaboration among CPS professionals in academia, government, and industry
CPS-VO
malware detection
biblio
A Honeypot with Machine Learning based Detection Framework for defending IoT based Botnet DDoS Attacks
Submitted by
aekwall
on Mon, 06/01/2020 - 10:43am
composability
Computer crime
computer network security
Data models
DDoS attack detection
detection framework
honey pots
honeypot-based approach
Human behavior
Human Factors
Internet of Things
invasive software
IoT botnet DDoS attacks
IoT Botnets
IoT honeypot
IoT Honeypots
IoT malware
IoT security
learning (artificial intelligence)
machine learning
machine learning model
machine learning techniques
malware
malware detection
Metrics
network security
Protocols
pubcrawl
Resiliency
Scalability
Training
Zero-day attacks
Zero-Day DDoS Attack
zero-day DDoS attacks
biblio
Applying Convolutional Neural Network for Malware Detection
Submitted by
grigby1
on Mon, 04/06/2020 - 2:24pm
binary code analysis
composability
computer network security
convolutional neural nets
convolutional neural networks
Convolutional Neural Networks (CNN)
cyber physical systems
deep learning
feature extraction
internet
invasive software
knowledge based systems
learning (artificial intelligence)
machine learning
malware
malware detection
malware detection efficiency
malware renders conventional detection techniques
Metrics
network administrators
network coding
Personnel
Predictive models
pubcrawl
resilience
Resiliency
source code
Source code analysis
testing
Training
biblio
Cuckoo’s Malware Threat Scoring and Classification: Friend or Foe?
Submitted by
grigby1
on Fri, 03/27/2020 - 11:38am
tools
collaboration
information security
pubcrawl
policy-based governance
composability
pattern classification
malware
invasive software
sandboxing
cuckoo sandbox
dynamic analysis
automated tools
malicious software
malware behavior
Malware behavior analysis
malware detection
malware incident response
malware sample
malware threat classification
measured response
microsoft windows
sandbox
scoring classification
severity classification
threat alert
threat classification
threat classification rating
threat score
threat scoring
victim host system
Virtual machining
biblio
A Robust Malware Detection System Using Deep Learning on API Calls
Submitted by
grigby1
on Fri, 03/27/2020 - 11:37am
Logic gates
deep learning
learning (artificial intelligence)
collaboration
feature extraction
Neural networks
pubcrawl
policy-based governance
composability
malware
invasive software
sandboxing
application program interfaces
cuckoo sandbox
API
API calls
API sequences
BLSTM
component
computer security
malware detection
massive datasets
massive malware
neural nets
Object oriented modeling
redundant API
robust malware detection system
biblio
Analysis of Machine Learning Techniques for Ransomware Detection
Submitted by
aekwall
on Mon, 03/23/2020 - 1:25pm
malware detection
invasive software
learning (artificial intelligence)
machine learning
Random Forest
Resiliency
pubcrawl
composability
Ransomware
Metrics
pattern classification
computer networks
CICAndMal2017 dataset
classification methods
machine learning-based ransomware detection
ransomware families
biblio
Bytecode Heuristic Signatures for Detecting Malware Behavior
Submitted by
aekwall
on Mon, 03/09/2020 - 11:13am
Monitoring
Scalability
malware
security
malware detection
invasive software
Resiliency
pubcrawl
digital signatures
Virtual machining
computational complexity
malware behavior
Prototypes
low performance overhead
Computer languages
virtual machines
Instruction sets
response time
behavior
behavior based detection
bytecode
bytecode heuristic signatures
hash-based signatures
heuristic
malicious applications
proactive approaches
proactive behavior heuristics
reactive security solutions
signature
Security Heuristics
predictability
biblio
Malware Detection Using Honeypot and Machine Learning
Submitted by
grigby1
on Wed, 02/26/2020 - 4:42pm
Adware malware
computer malware
computer viruses
Decision Tree
Decision trees
digital signatures
firewalls
honeypot
honey pots
Human Factors
invasive software
learning (artificial intelligence)
machine learning
malware
malware detection
Measurement
Metrics
privacy
pubcrawl
Resiliency
Scalability
signature-based security systems
support vector machine
Support vector machines
SVM
threat vectors
Trojan Horse malware
biblio
Peer Based Tracking Using Multi-Tuple Indexing for Network Traffic Analysis and Malware Detection
Submitted by
grigby1
on Thu, 01/02/2020 - 2:41pm
5-tuple flow tables
botnet
command and control systems
computer network security
Data Streaming
expert system rule set
expert systems
flow connection concept
generated metadata
Human Factors
Indexes
Internet of Things
Intrusion Detection Systems
invasive software
IoT devices
IP networks
malicious behaviours
malicious network threats
malware
malware detection
meta data
multipeered ZeuS botnet
multiple 5 tuple communications
multituple indexing
network analytics tools
Network Behavioural detection
network traffic analysis
network traffic behaviour
Next generation firewall
next generation firewalls
packet content
peer based tracking
Peer-to-peer computing
privacy
Protocols
pubcrawl
Scalability
single tuple flow types
standard IDS systems
standards
TCP/IP fields
telecommunication traffic
traditional firewalls
transport protocols
video streaming
Zeus botnet
biblio
Deep in the Dark - Deep Learning-Based Malware Traffic Detection Without Expert Knowledge
Submitted by
grigby1
on Thu, 01/02/2020 - 2:41pm
Analytical models
classification
computer architecture
computer network security
Data models
deep learning
deep learning models
deep learning-based malware traffic detection
expert handcrafted features
expert systems
feature extraction
Human Factors
invasive software
learning (artificial intelligence)
machine learning-based systems
malware
malware detection
malware network traffic
network security applications
network traffic
networking attacks
pattern classification
privacy
pubcrawl
Raw Measurements
raw-traffic feature representations
robust network security systems
Scalability
telecommunication traffic
Training
biblio
Phishing E-Mail Detection by Using Deep Learning Algorithms
Submitted by
grigby1
on Tue, 11/26/2019 - 3:48pm
classification
deep learning
Human behavior
human factor
machine learning
malware detection
Phishing
pubcrawl
supervised learning
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