System-Level Behavioral and Component-Based Analysis for Identifying Post-Quantum Cryptographic (PQC) Execution and PQC-Based Attack Attempts

Abstract This research paper provides a unified method to identify whether a system is executing post-quantum cryptographic (PQC) algorithms or classical cryptography using a combination of system-level behavioral analysis and component-level symbol tracing. By observing runtime telemetry—such as CPU utilization, memory usage, heap activity, output size, and execution time—and correlating it with dynamic function-level tracing, the system generates a runtime cryptographic fingerprint. This fingerprint enables real-time detection of PQC-based attack attempts, fallback/downgrade behavior, and unauthorized cryptographic operations. This research paper operates across smartcards, Hardware security Module (HSMs), host systems, cloud environments, and CI/CD pipelines, providing future-proof security monitoring against quantum-capable adversaries.

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-12-17
DOI
https://doi.org/10.5281/zenodo.17935732
Primary Topic
Cryptographic Implementations and Security
Type
article
Field-Weighted Citation Impact
0.00
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article

System-Level Behavioral and Component-Based Analysis for Identifying Post-Quantum Cryptographic (PQC) Execution and PQC-Based Attack Attempts

Zenodo (CERN European Organization for Nuclear Research)
Cryptographic Implementations and Security
article

System-Level Behavioral and Component-Based Analysis for Identifying Post-Quantum Cryptographic (PQC) Execution and PQC-Based Attack Attempts

article en

Abstract

Abstract This research paper provides a unified method to identify whether a system is executing post-quantum cryptographic (PQC) algorithms or classical cryptography using a combination of system-level behavioral analysis and component-level symbol tracing. By observing runtime telemetry—such as CPU utilization, memory usage, heap activity, output size, and execution time—and correlating it with dynamic function-level tracing, the system generates a runtime cryptographic fingerprint. This fingerprint enables real-time detection of PQC-based attack attempts, fallback/downgrade behavior, and unauthorized cryptographic operations. This research paper operates across smartcards, Hardware security Module (HSMs), host systems, cloud environments, and CI/CD pipelines, providing future-proof security monitoring against quantum-capable adversaries.

Zenodo (CERN European Organization for Nuclear Research)
Openalex Percentile: Top 19%
Cryptographic Implementations and Security
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