This repository contains the complete research prototype for Carbon-Aware Cybersecurity Scheduling (CACS) — a novel framework that reduces the carbon footprint of security operations by intelligently deferring non-critical tasks to time windows when the electricity grid has lower carbon intensity.
Key Finding: Carbon-aware scheduling achieves a 28.8% reduction in CO₂ emissions from security operations with only 3.8 hours average additional vulnerability exposure for deferrable tasks.
📊 Results Summary
Strategy
CO₂ (kg)
Reduction
Avg Exposure (h)
Max Exposure (h)
Fixed (Baseline)
98.52
—
0.0
0
Carbon-Aware
70.10
28.8%
3.8
162
Hybrid (α=0.6)
78.77
20.0%
1.1
22
Night-Shift
81.65
17.1%
1.6
18
Statistical robustness: 29.5% ± 1.2% mean reduction (95% CI: 27.1–31.8%) over 10 independent trials.
1# Install dependencies2pip install numpy pandas matplotlib
34# Run the full experiment5python experiment.py
67# For real UK carbon intensity data (requires internet):8# Edit experiment.py: set use_real_data=True
📐 Problem Formulation
Given a set of security tasks T = {t₁, t₂, ..., tₙ}, each with energy consumption eᵢ, generation time gᵢ, deadline dᵢ, and deferrability flag δᵢ, minimize:
min Σ eᵢ · c(sᵢ)
Subject to:
sᵢ = gᵢ if δᵢ = 0 (non-deferrable)
gᵢ ≤ sᵢ ≤ gᵢ + dᵢ if δᵢ = 1 (deferrable)
Where c(h) is the carbon intensity (gCO₂/kWh) at hour h.
🔬 Scheduling Strategies
Carbon-Aware Greedy — Defer each task to the lowest-carbon hour within its deadline
