Cyber Defense Through Engineering and Analytics
Cyber Defense Through Engineering and Analytics
I specialize in cybersecurity defense using a systems engineering and data-driven approach. I design and secure virtual environments, analyze real attack behavior through logs and network traffic, and build detection capabilities that improve security resilience. My work spans SIEM alerting, PCAP forensics, and incident reporting aligned to national cybersecurity standards — all focused on protecting critical systems from real-world threats.
Ryan Beavers
Cybersecurity & Systems Engineer
Threat Detection | Network Defense | Secure System Design
I build and secure virtual environments, analyze logs and network traffic to expose attacker behavior, and deploy SIEM detections that strengthen defense in real time.
Email:
Location:
Huntsville, Alabama
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Core Capabilities:
– SIEM + PCAP Forensics (Splunk | Wireshark)
– Linux | Network Security​
– Incident Detection & Reporting
– Statistical Modeling & Anomaly Detection
– Former Intel Software/Telemetry Engineer
– Security+ Exam (Scheduled 11/19/25)
– U.S. Citizen | Clearance Eligible
EXPERIENCE
2024-Present
Independant Study
Cybersecurity-SOC Lab Projects
II built a virtual SOC using Kali, Ubuntu servers, and Splunk to simulate real attacker behavior. I executed SSH brute-force attempts, port scans, and web exploits to generate logs and alerts. Using Splunk dashboards and Wireshark PCAPs, I identified malicious activity and documented recommended responses aligned with NIST practices.
2021-2022
Portland State University
Teaching & Technical Communication
I helped students communicate complex analytical concepts clearly and accurately, improving documentation and structured reasoning—skills directly applicable to cybersecurity reporting and collaboration.
2008-2010
Software Engineer
Intel Corporation
I engineered real-time telemetry and system simulation tools that accelerated performance feedback and reliability insights for new hardware. I collaborated with cross-functional teams to optimize system efficiency and earned multiple recognition awards for my contributions.
Doctor of Engineering
Beginning January 2026
The George Washington University
Cybersecurity Analytics
2024-2025
Master of Science
UNIVERSITY of Oklahoma
Applied Statistics
2025
Certificate
Fullstack Academy
Cybersecurity
2019-2021
Master of Arts
Johns Hopkins University
Liberal Arts
2004-2008
Bachelor of Science
Arizona State University
Computational Mathematics
PROJECTS
ETHICS & CRITICAL ANALYSIS
This essay examines how generative AI tools shape our understanding of human values — and what happens when ethical context is missing. By analyzing AI-generated definitions of leadership, I explore the risks of “bias by omission,” the illusion of neutrality in algorithmic systems, and the responsibility humans retain for moral judgment in technological environments.
Automated hiring promises efficiency — but without ethical safeguards, it can quietly reinforce discrimination instead of eliminating it. This analysis examines Amazon’s failed AI recruiting tool and shows how biased training data, opaque decision logic, and misplaced trust in automation can harm real people seeking real jobs. It calls for transparency, fairness auditing, and human accountability in the use of machine-learning systems that influence life-changing opportunities.
Every analyst has a go-to way of making sense of the world. For me, data behaves like language—full of structure, rhythm, and meaning beneath the surface. This narrative explores how my background in the humanities and applied statistics shaped a unique analytical mindset: treating logs as stories, anomalies as “glitches,” and cybersecurity as a communication problem between humans and machines. It also reflects critically on the limits of any single method—and the importance of expanding the toolbelt.