FloCon 2019 Presentions
These presentations were given at FloCon 2018, an annual event where attendees discuss the analysis of large volumes of traffic and showcase the next generation of flow-based analysis techniques.
Publisher:
Software Engineering Institute
Subjects
This collection of presentations were given at FloCon 2019, an annual event where attendees discuss the analysis of large volumes of traffic and showcase the next generation of flow-based analysis techniques.
Improved Hunt Seeding with Specfic Anomaly Scoring
January 2019
In this presentation, the attendees were presented with a flexible, open source tool for non-parametrically modeling multivariate densities of network logs.
Using Triangulation to Evaluate Machine Learning Models
January 2019
In this presentation, Dr. Andrew Fast presents a series of questions and data queries that can be used to determine the parameters of effectiveness for a machine learning model.
Cybersecurity Data Science: Best Practices from the Field
January 2019
In this presentation, the author seeks to take a step back from methodological insights and case studies to ask larger questions concerning the status of cybersecurity data science as an emerging profession.
Four Machine Learning Techniques that Tackle Scale - And Not Just By Increasing Accuracy
January 2019
In this presentation the author presents an overview of the ways in which recent machine learning techniques can provide ancillary value—value beyond accurate predictions—that helps with the problems of scaling real-world implementations.
The Power of Cyber Threat Intelligence
January 2019
In this presentation, the author discusses how to anticipate the right questions and convey the right information to executives through case studies that highlight the power of what cyber threat intelligence can do to drive executive decision making.
The Generation and Use of TLS Fingerprints
January 2019
In this presentation, the authors describe a TLS fingerprinting system and discusses the common pitfalls when using this type of information and analyzes techniques that make effective use of our newly open-sourced TLS fingerprint database.
Monitoring Massive Network Traffic using Bayesian Inference
January 2019
In this presentation, the author discusses methods for performing large scale Bayesian inference on DNS logs aggregated into count data, representing the number of requests from tens of millions of stub IPs made to hundreds of millions of domains.
Using Generative Adversarial Networks to Improve Phishing Domain Classifiers
January 2019
In this presentation, the authors discuss the use of generative adversarial networks (GANs) to construct synthetic phishing domains as potential evasion attacks, and test the value of including these domains in a machine learning classifier.
Harvesting Logs for Enhanced Investigations
January 2019
In this talk, the author discusses the type of information that should be continuously collected and kept on-hand for investigative value in the case of a network compromise, and he addresses the value of such artifacts in an investigation.
Network Telescopes Revisited: From Loads of Unwanted Traffic to Threat Intelligence
January 2019
This presentation introduces a comprehensive system developed to analyze malicious traffic on a large scale and produce actionable results in close to real time.
Time-Based Correlation of Malicious Events and Their Connections
January 2019
In this presentation, the authors discuss how to automate the use of statistics to help link events and connections in a timeline during an incident or forensic investigation.
IMPACT: Information Marketplace for Policy and Analysis of Cyber-risk & Trust
January 2019
In this presentation, Jeff Schmidt introduces a U.S. Department of Homeland Security (DHS) program called Information Marketplace for Policy and Analysis of Cyber-risk & Trust (IMPACT).
InSight2: IRNC Advanced Measurements and Instrumentation (AMI)
January 2019
In this presentation, the authors discuss InSight2, an open platform, intended to monitor and facilitate the development of network analytics for these large-scale networks.
Detecting Automatic Flows
January 2019
In this presentation, Jeffrey Dean, PhD., discusses specific Netflow-derived features that can be used to discriminate between flows generated by user actions and those generated automatically by applications or systems.
Quantum Approach to Inverse Malware Eradication
January 2019
The goal of this presentation is to inform people that using a 'pass only known good' methodolgy through a quantum approach simplifies the solution and the future of information security will benefit from an inverted approach to security.