Post-Quantum Overhead Summary: Latency and Performance Metrics

PQ-CZTA, a post-quantum cognitive zero-trust architecture, achieved F1-scores from 0.972 to 1.000 across six intrusion detection datasets. The framework, authored by Hashim Hussain and last updated in May 2026, incurs a 3.1–4.4 second latency for a full post-quantum handshake. This 5.5 KB Excel file summarizes performance overheads for securing resource-constrained healthcare IoT systems.

Use Cases

• Benchmarking post-quantum cryptographic latency for IoT systems based on the reported 3.1–4.4 second handshake overhead.
• Evaluating machine learning-based intrusion detection performance using the F1-scores (0.972-1.000) reported across multiple datasets.
• Assessing the impact of SMOTE oversampling on model performance for imbalanced IoT traffic data.
• Designing adaptive zero-trust policy engines based on the described dynamic trust scoring and policy decisions (ALLOW, MONITOR, DENY, QUARANTINE).

Strengths

• Performance metrics are derived from six diverse intrusion detection datasets, including NSL-KDD, CIC-IDS2017, and MedBIoT.
• Reports specific, quantified results: F1-scores ranging from 0.972 to 1.000 and a latency of 3.1–4.4 seconds.
• Includes an ablation study quantifying component contributions, such as SMOTE improving F1-score by 5–20% on imbalanced data.

Limitations

• Row count is unknown, which may limit suitability assessment.
• Column-level documentation is absent; field semantics must be inferred after download.
• The dataset is very small at 5.5 KB, indicating limited scope, likely a summary of results rather than raw data.

Provenance

Source

Hashim Hussain via figshare.

Collection Method

Results summarized from evaluating the proposed Post-Quantum Cognitive Zero-Trust Architecture (PQ-CZTA).

Freshness

Last updated 2026-05-28 17:42:41; freshness should be verified.