CAMLIS 2019: CONFERENCE ON APPLIED MACHINE LEARNING FOR INFORMATION SECURITY

This page contains an index consisting of author-provided keywords.

A
adversarial attacks	Mitigating Adversarial Attacks against Machine Learning for Static Analysis
adversarial example	Trying to Make Meterpreter into an Adversarial Example
Adversarial Machine Learning	Exploring Backdoor Poisoning Attacks Against Malware Classifiers Towards a Trustworthy and Resilient Machine Learning Classifier - a Case Study of Ransomware Behavior Detector
Automated Malware Detection	CNN-Based Malware Visualization and Explainability
B
Backdoor Attacks	Exploring Backdoor Poisoning Attacks Against Malware Classifiers
behavior analysis	Towards a Trustworthy and Resilient Machine Learning Classifier - a Case Study of Ransomware Behavior Detector
Behavioral analysis	ProblemChild: Discovering Anomalous Patterns based on Parent-Child Process Relationships
benchmark	EMBER Improvements
binary emulation	Next Generation Process Emulation with Binee
C
Classification	An Information Security Approach to Feature Engineering
cloud	Scalable Infrastructure for Malware Labeling and Analysis
computer security	Mitigating Adversarial Attacks against Machine Learning for Static Analysis
D
data augmentation	Towards a Trustworthy and Resilient Machine Learning Classifier - a Case Study of Ransomware Behavior Detector
data processing	Accelerating The Alert Triage Scenario (AT-ATs): InfoSec Data Science with RAPIDS
dataset	EMBER Improvements
decompilation	Applications of Graph Integration to Function Comparison and Malware Classification
Deep Learning	An Information Security Approach to Feature Engineering What is the Shape of an Executable?
deep learning explanation	Towards a Trustworthy and Resilient Machine Learning Classifier - a Case Study of Ransomware Behavior Detector
Deep neural networks	Describing Malware via Tagging
E
early detection	Towards a Trustworthy and Resilient Machine Learning Classifier - a Case Study of Ransomware Behavior Detector
Email Security	Using Lexical Features for Malicious URL Detection- A Machine Learning Approach
Embeddings	Applying Deep Graph Representation Learning to the Malware Graph
Executable	What is the Shape of an Executable?
Explainable ML for Infosec	CNN-Based Malware Visualization and Explainability
F
feature engineering	An Information Security Approach to Feature Engineering EMBER Improvements
Feature Hashing	An Information Security Approach to Feature Engineering
G
gpu	Accelerating The Alert Triage Scenario (AT-ATs): InfoSec Data Science with RAPIDS
Graph Analytics	TweetSeeker: Extracting Adversary Methods from the Twitterverse
Graph deep learning	Applying Deep Graph Representation Learning to the Malware Graph
Graph representation learning	Applying Deep Graph Representation Learning to the Malware Graph
Graph-based algorithms	ProblemChild: Discovering Anomalous Patterns based on Parent-Child Process Relationships
H
hybrid analysis	Next Generation Process Emulation with Binee
I
infrastructure	Scalable Infrastructure for Malware Labeling and Analysis
Intelligence Collection	TweetSeeker: Extracting Adversary Methods from the Twitterverse
Interpretable ML	TweetSeeker: Extracting Adversary Methods from the Twitterverse
IOC	An Information Security Approach to Feature Engineering
L
labeling	Scalable Infrastructure for Malware Labeling and Analysis
learning to rank	Learning to Rank Relevant Malware Strings Using Weak Supervision
Learning-based approaches for automating security tasks/workflows	ProblemChild: Discovering Anomalous Patterns based on Parent-Child Process Relationships
M
machine learning	Trying to Make Meterpreter into an Adversarial Example PowerShell Malware Detection using AMSI Scalable Infrastructure for Malware Labeling and Analysis What is the Shape of an Executable? Using Lexical Features for Malicious URL Detection- A Machine Learning Approach Mitigating Adversarial Attacks against Machine Learning for Static Analysis
Malicious URL Detection	Using Lexical Features for Malicious URL Detection- A Machine Learning Approach
malware	Trying to Make Meterpreter into an Adversarial Example Scalable Infrastructure for Malware Labeling and Analysis What is the Shape of an Executable? Mitigating Adversarial Attacks against Machine Learning for Static Analysis
malware analysis	Learning to Rank Relevant Malware Strings Using Weak Supervision
Malware Classification	Exploring Backdoor Poisoning Attacks Against Malware Classifiers
Malware description	Describing Malware via Tagging
malware detection	Next Generation Process Emulation with Binee
Malware embeddings	Describing Malware via Tagging
Malware Reverse Engineering	CNN-Based Malware Visualization and Explainability
markov	Applications of Graph Integration to Function Comparison and Malware Classification
N
Natural Language Processing	TweetSeeker: Extracting Adversary Methods from the Twitterverse
NET	Applications of Graph Integration to Function Comparison and Malware Classification
Neural Networks	What is the Shape of an Executable? Mitigating Adversarial Attacks against Machine Learning for Static Analysis
O
One-hot encoding	An Information Security Approach to Feature Engineering
open-source	EMBER Improvements
P
pagerank	Applications of Graph Integration to Function Comparison and Malware Classification
pe file	Mitigating Adversarial Attacks against Machine Learning for Static Analysis
Poisoning Attacks	Exploring Backdoor Poisoning Attacks Against Malware Classifiers
powershell	PowerShell Malware Detection using AMSI
R
ransomware detector	Towards a Trustworthy and Resilient Machine Learning Classifier - a Case Study of Ransomware Behavior Detector
reproducibility study	Trying to Make Meterpreter into an Adversarial Example
S
script	PowerShell Malware Detection using AMSI
Security	An Information Security Approach to Feature Engineering
simulated malware	Towards a Trustworthy and Resilient Machine Learning Classifier - a Case Study of Ransomware Behavior Detector
Social Media Analysis	TweetSeeker: Extracting Adversary Methods from the Twitterverse
static analysis	Mitigating Adversarial Attacks against Machine Learning for Static Analysis
static classifier	EMBER Improvements
T
Tagging	Describing Malware via Tagging
Topology	What is the Shape of an Executable?
tutorial	Accelerating The Alert Triage Scenario (AT-ATs): InfoSec Data Science with RAPIDS
U
Unsupervised Learning	TweetSeeker: Extracting Adversary Methods from the Twitterverse
V
Vectorization	What is the Shape of an Executable?
W
weak supervision	Learning to Rank Relevant Malware Strings Using Weak Supervision

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