Day 11: Kernel Anomaly Scoring Validation & Interpretation

// Context

By the end of Day 10, Sentinel Sandbox successfully produced stable anomaly scores using a temporally bucketed syscall representation and a CPU-only Dynamic Weightless Network (DWN).

Day 11 focused on validation and interpretation, rather than adding new architecture.
The goal was to confirm that the observed anomaly scores were:

structurally sound
repeatable
meaningful in the context of kernel behavior

// What Was Done

Re-ran training and scoring pipelines on live ptrace syscall traces
Verified preprocessing guarantees:
- Fixed input dimensionality (43,008 bits)
- No shape drift across windows
- No histogram expansion from unknown syscalls
Scored syscall windows generated from:
- Normal interactive shell sessions
- Abnormal / syscall-noisy executions

// Observed Behavior

Normal Discriminator

Produces consistently positive mean responses
Indicates effective memorization of benign kernel behavior patterns

Attack Discriminator

Produces suppressed or negative responses
Expected outcome due to normal-only training

Anomaly Score (Normal − Attack)

Strongly positive mean for benign traces
High variance, expected at prototype scale
Distribution shift observed between normal and abnormal executions

// Interpretation

The system currently behaves as a statistical anomaly detector, not a binary classifier.

No decision threshold is enforced
Scores must be interpreted as relative deviations from learned benign behavior
This aligns with classical intrusion detection system (IDS) design

// Key Insight

Anomaly detection systems should be evaluated by score distributions, not accuracy metrics.

At this stage:

Distribution separation matters more than precision/recall
Stability and interpretability take priority over classification performance

// What Was Intentionally Not Done

No threshold calibration
No ROC or false-positive tuning
No claims of production readiness

These steps are deferred to preserve scientific correctness.

// Outcome

Sentinel Sandbox now demonstrates:

End-to-end kernel-level anomaly scoring
Representation-stable preprocessing
Interpretable discriminator behavior

The system is ready for the next phase: threshold calibration and false-positive analysis.

// Status

Completed