Joshua Neil
Precision threat detection - Alpha Level
- Role
- Co-founder at Alpha Level
- Location
- Redmond, WA, US
- LinkedIn followers
- 500 followers
About Joshua Neil
After more than 25 years of experience working on data driven solutions to USG and Industry enterprise security problems, I\'m convinced of certain things:1. Attackers are going to penetrate perimeter defenses. Yet, only the most mature security operations have visibility and understand their normal enterprise behavior, let alone those of an attacker.2. Statistical methods are under-utilized for attack detection. There is huge promise in identifying attack-consistent events that are also rare with respect to a historic, predictive model. A good understanding of the underlying model assumptions, combined with security domain knowledge, is critical to the proper application of statistical or machine learning approaches.3. Attacks do not happen in isolation on a single endpoint. Instead, they are exhibited across multiple endpoints, and in the communications between these endpoints. This leads to questions about local, connected subgraphs, within the larger network graph.4. Networks create rare events continuously! As such, I focus on not only quantifying rarity, but security-relevant rarity.5. Context is everything. Telling the forensic story to the analyst, as much as possible with the data available, is the difference between rapid detection of only true breaches and foundering in a sea of false positives.
Experience
Co-founder
Aug 2023 — Present
Education
UC Irvine
BS, Mathematics
1998 — 2000
University of Southern California
MS, Electrical Engineering
2004 — 2006
The University of New Mexico
MS, Statistics
2007 — 2011
The University of New Mexico
Ph.D., Statistics
2007 — 2011
Skills
- Information Security
- Simulation
- Matlab
- Linux
- Simulations
- Network Security
- Monte Carlo Simulation
- Modeling
- Mathematics
- Data Mining
- High Performance Computing
- Science
- Algorithms
- Machine Learning
- Scientific Computing
- Statistical Computing
- Statistics
- C++
- Research
- Theory
- Analytics
- C
- Programming
- Optimization
- Statistical Modeling
- Parallel Computing
- Program Development
- Analysis
- Perl
- Data Science
- Python
- Technical Writing
- Latex
- Parallel Programming
- Numerical Analysis
- Applied Mathematics
- R&D
- Security
- Bayesian Statistics
- Data Analysis
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