FloCon2019 2019 Jan. 7, 2019 to Jan. 7, 2019, New Orleans, USA

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Title Speakers Summary Topic Types
Introduction Angela Horneman N/A
Cutting Through the Hype: How to Effectively Apply ML to Cybersecurity Jason Kichen Current cybersecurity challenges represent a machine-scale problem and large amounts of automation are required to ...
Improved Hunt Seeding with Specific Anomaly Scoring Brenden Bishop As the practice of hunting has spread through enterprise cyber security, interest in generalized anomaly ...
Using Triangulation to Evaluate Machine Learning Models Andrew Fast There are few industries using machine learning models with more at stake than network security. ...
Keynote Jon Ramsey It not just a model it’s threat intel a Security use case driven machine learning ...
Panel: What Cybersecurity Practice Produces the Least Benefit? Ryan E. Moore , Renee Burton , Rastislav Stringer This panel will discuss the perception of benefit with cybersecurity practice. We will look at ...
Cybersecurity Data Science: Best Practices from the Field Scott Mongeau Cybersecurity data science (CDS) is a fast emerging professional discipline. The field seeks to apply ...
Four Machine Learning Techniques that Tackle Scale (And Not Just By Increasing Accuracy) Lindsey Lack Because many of the most prominent successes of machine learning have been in the area ...
The Power of Cyber Threat Intelligence and its Influence on Executive Decision Making Eboni Thamavong Executives are inundated with an abundance of cyber threat intelligence from several sources, but what ...
The Generation and Use of TLS Fingerprints Blake Anderson There are many TLS implementations in use by different applications and operating systems, each of ...
Monitoring Massive Network Traffic Using Bayesian Inference David Rodriguez Monitoring network logs from DNS requests to TCP connections is challenging because these logs are ...
Arbitrary Albatross: Neutral Naming of Vulnerabilities at Scale Leigh Metcalf Vulnerability identification is critical defensive security infrastructure. We have CVE, which is improving scope and ...
Using Generative Adversarial Networks to Harden Phishing Class Jen Heath As machine learning classifiers are increasingly deployed for defensive cybersecurity purposes, there is a growing ...
Hunting Frameworks David Gainey In this talk, I will be discussing the type of information that should be continuously ...
Keynote: Improving Relationships with Data Jason Chan Relationships between security and development teams have historically been strained - developers want to move ...
Lunchtime Table Talk: Data Science Behind the Scenes, Part 1 - The Data Science Process for Network Security Andrew Fast Data science is rapidly becoming an integral part of the network security industry. Although widespread ...
Lunchtime Table Talk: Towards Security Defect Prediction Eliezer Kanal In this study, we investigate the limits of the current state of the art AI ...
Network Telescopes Revisited: From Loads of Unwanted Traffic to Threat Intelligence Piotr Bazydlo , Adrian Pawliński Network telescope (a.k.a., darknet) is a monitored but otherwise unused IP space that should not ...
Data as Evidence: Analysis of Logs for Litigation Matthew Curtin Covering a network with sensors is the first step towards security, but the massive flood ...
Simulating Your Way to Security - One Detector at a Time Slava Nikitin Covering a network with sensors is the first step towards security, but the massive flood ...
Detecting Lateral Movement with a Compute-intense Graph Kernel Steve Reinhardt Both successful intruders and internal abusers of computer networks seek to move laterally in an ...
Time-based Correlation of Malicious Events and their Connections Steven Nicholls In the cyber security arena, many events of interest occur in conjunction with network connection ...
Quantum Approach to Inverse Malware Eradication Dan Shabat A quantum approach to malware eradication addresses the needs of organizations, which are facing a ...
Identifying Automatic Flows Jeffrey Dean One of the limitations of solely using flow metadata (e.g. Netflow) for network analysis is ...
Insight2 Angel Kodituwakku Network throughput and complexity are increasing due to the increasing number of devices and data-driven ...
IMPACT Jeff Schmidt Good and interesting research starts with good and interesting data. Jeff Schmidt will introduce a ...
Lunchtime Table Talk: Data Science Behind the Scenes, Part 2 - "Tidy" Data for Network Traffic Analysis Andrew Fast Data science is rapidly becoming an integral part of the network security industry. Although widespread ...
Lunchtime Table Talk: Graph Measures for Network Traffic Analysis Josh Shimeall This presentation describes the use of network science (graph statistics) measures analyzing a flash crowd ...
Dynamically Repurposed and Programmable Network Monitoring Michael Reed Effective NetOp and SecOp system architectures require collecting and analyzing network traffic data in real ...
Backwaters: Security Streaming Platform Chris Weber Backwaters is a project devoted to the transportation of security data for Comcast's Enterprise. This ...
Automated Cluster Testing and Optimization Brad Powell How do you know if your cluster can handle the load you want to put ...