2019 Program

(the schedule is now available)

Keynotes:

Protecting Users: When Security and Privacy Collide by Aleatha Parker-Wood

On Evaluating Adversarial Robustness by Nicholas Carlini

Tutorials:

Accelerating The Alert Triage Scenario (AT-ATs): InfoSec Data Science with RAPIDS

Talks:

Trying to Make Meterpreter into an Adversarial Example

Scalable Infrastructure for Malware Labeling and Analysis

TweetSeeker: Extracting Adversary Methods from the Twitterverse

Applying Deep Graph Representation Learning to the Malware Graph

CNN-Based Malware Visualization and Explainability

Describing Malware via Tagging

Mitigating Adversarial Attacks against Machine Learning for Static Analysis

ProblemChild: Discovering Anomalous Patterns based on Parent-Child Process Relationships

What is the Shape of an Executable?

Using Lexical Features for Malicious URL Detection- A Machine Learning Approach

An Information Security Approach to Feature Engineering

Next Generation Process Emulation with Binee

EMBER Improvements

Exploring Backdoor Poisoning Attacks Against Malware Classifiers

Applications of Graph Integration to Function Comparison and Malware Classification

Learning to Rank Relevant Malware Strings Using Weak Supervision

Towards a Trustworthy and Resilient Machine Learning Classifier - a Case Study of Ransomware Behavior Detector

Posters:

Privacy-preserving Surveillance Methods using Homomorphic Encryption

Supervised/unsupervised cross-over method for autonomous anomaly classification

Detecting Unexpected Network Flows with Streaming Graph Clustering

On the OTHER Application of Graph Analytics for Insider Threat Detection

Cyber-Adversary Behavior Extraction and Comparisons Using IDS Alert Logs

Magicwand: A Learning-Based Approach for Automatic Low-Volume DDoS Mitigation

Predicting Exploitability: Forecasts for Vulnerability Management

The Secret Life of Pwns: Understanding the Risks and Benefits of Exploit Code Disclosure

Serverless Machine Learning for Phishing

Adversarial Attacks against Malware N-gram Machine Learning Classifiers

Towards A Public Dataset/Benchmark for ML-Sec

Phish Language Processing (PhishLP)

Linking Exploits from the Dark Web to Known Vulnerabilities for Proactive Cyber Threat Intelligence: An Attention-Based Deep Structured Semantic Model Approach

Evaluating the Potential Threat of Generative Adversarial Models to Intrusion Detection Systems