Master of Science in Computer Science • Cloud security pilot plan

MidWest Power Cloud-Based AI/ML DDoS Protection Pilot

A pilot plan for evaluating whether AWS managed edge services can reduce DDoS disruption without requiring application changes.

Project objective

Improve availability and customer trust by detecting and mitigating abnormal traffic before it reaches customer portals and internal-facing systems.

What I produced

  • Designed an architecture using CloudFront, Shield, WAF, CloudWatch, IAM, and a controlled test endpoint.
  • Defined functional, performance, user, and technical requirements.
  • Created performance, security, legal, and business test cases.
  • Developed a work breakdown structure, schedule, staffing plan, quality criteria, risk register, and budget.
  • Established measurable pilot acceptance criteria for detection time, mitigation rate, latency, and legitimate-traffic availability.

Key decisions

  • Run a proof of concept before any production-wide rollout.
  • Place managed protection at the edge so existing applications do not need major changes.
  • Use controlled simulated traffic and continuous monitoring to reduce test risk.
  • Treat false positives, service disruption, and cost overrun as explicit project risks.
6-week pilotPlanning through closeout
85% mitigation goalInitial simulated DDoS target
<250 msMaximum planned added latency

Validation and analysis

  • Targeted detection within about two minutes.
  • Set an initial goal of mitigating at least 85% of simulated attack traffic.
  • Required added latency below 250 milliseconds and legitimate traffic availability of at least 99%.