FloCon 2020 Presentations
• Collection
Publisher
Software Engineering Institute
Topic or Tag
Abstract
These presentations were given at FloCon 2020, an annual conference that focuses on data-driven network security. Speakers from industry, government, and academia presented talks on how to apply "big data" analysis techniques to solve difficult security problems.
Collection Items
![presentation-thumbnail-1](/media/images/Presentation_Thumbnail_1.max-150x150.format-webp.webp)
AI is Not Magic: Machine Learning for Network Security
• Presentation
By Lena Pons, Eliezer Kanal
This presentation introduces foundational data science concepts and prepares attendees to scope new Artificial Intelligence and Machine Learning projects.
Learn More![presentation-thumbnail-1](/media/images/Presentation_Thumbnail_1.max-150x150.format-webp.webp)
SysFlow: Scalable System Telemetry for Improved Security Analytics
• Presentation
By Federico Araujo (IBM Research), Teryl Taylor (IBM Research)
This presentation introduces SysFlow as a new data representation for system behavior introspection for scalable security, compliance, and performance analytics.
Learn More![presentation-thumbnail-1](/media/images/Presentation_Thumbnail_1.max-150x150.format-webp.webp)
Data Driven Security Challenges
• Presentation
By Timothy J. Shimeall
This presentation discusses data driven security challenges in network security.
Learn More![presentation-thumbnail-1](/media/images/Presentation_Thumbnail_1.max-150x150.format-webp.webp)
Bayes at 10+ Gbps: Identifying Malicious and Vulnerable Processes from Passive Traffic Fingerprinting
• Presentation
By David McGrew (Cisco Systems, Inc.)
This presentation describes an inferencing system and its implementation, results in applying it to real-world traffic, and open issues in this technology area.
Learn More![presentation-thumbnail-1](/media/images/Presentation_Thumbnail_1.max-150x150.format-webp.webp)
Less is More with Intelligent Packet Capture
• Presentation
By Randy Caldejon (CounterFlow AI)
Attendees learned to build and deploy a cost-effective network forensics solution with open source tools like Argus and Dragonfly Machine Learning Engine.
Learn More![presentation-thumbnail-1](/media/images/Presentation_Thumbnail_1.max-150x150.format-webp.webp)
Alchemy: Stochastic Data Augmentation for Malicious Network Traffic Detection
• Presentation
By Bo Hu (NTT Group)
This presentation introduces a stochastic method called Alchemy that regenerates a set of feature vectors by randomly resampling the raw traffic data of each bag into several subsets.
Learn More![presentation-thumbnail-1](/media/images/Presentation_Thumbnail_1.max-150x150.format-webp.webp)
Comcast Security Analytics Platform
• Presentation
By Gary Gabriel (Comcast), Mason Cheng (Comcast)
This presentation showed practical ways to process large-scale security-related data and analyze it using cloud based infrastructure.
Learn More![presentation-thumbnail-1](/media/images/Presentation_Thumbnail_1.max-150x150.format-webp.webp)
The Long & Winding Road to Production-Worthy
• Presentation
By Emily Heath (Mitre)
In this presentation, attendees learned valuable skills for how to test their analytics from different perspectives. From an operational perspective, the presenter discussed how to evaluate analytics for coverage of …
Learn More![presentation-thumbnail-1](/media/images/Presentation_Thumbnail_1.max-150x150.format-webp.webp)
A Structural Approach to Modeling Encrypted Connections
• Presentation
By Anthony Kasza (Corelight)
This presentation discusses how the concept of SOL can be applied to model encrypted protocols, including the SSH, SSL, and RDP protocols.
Learn More![presentation-thumbnail-1](/media/images/Presentation_Thumbnail_1.max-150x150.format-webp.webp)
Automating Reasoning with ATT&CK?
• Presentation
By Jonathan Spring
This presentation discusses limitations in MITRE's ATT&CK framework and proposes ways to restructure it to be more useful.
Learn MoreThis content was created for a conference series or symposium and does not necessarily reflect the positions and views of the Software Engineering Institute.