The Fractal Spectral Wave Filter: A Quantum-Resilient Cryptographic Primitive Harnessing the Aliasing Collisions

The rapid evolution of Quantum Computing poses a significant threat to the standard mathematical foundations of classical cryptography, prompting the global transition towards Post-Quantum Cryptography (PQC). While NIST is standardising lattice-based algorithms, chaotic cryptography continues to struggle with high-dimensional data, as traditional models require O(N^3) computational time and suffer from catastrophic memory overhead. Building upon prior optimization frameworks designed to eliminate cubic computational bottlenecks in chaotic systems [6], this paper introduces a novel cryptographic framework centered on the Fractal Spectral Wave Filter. By mapping arbitrary two-dimensional spatial data into a one-dimensional array using the Morton Z-order curve, we preserve local data relationships without dense matrix overhead. The system then utilizes the Number Theoretic Transform (NTT) over finite Galois integer rings—forming the core mathematical framework of NIST's PQC standards—for frequency-domain processing. Furthermore, by intentionally omitting standard zero-padding, the resulting unmitigated aliasing collisions act as a secure, lossless fractal scrambler, diffusing data in strict O(N log N) time. Experimental validations demonstrate perfect lossless recovery (MSE of 0.000000) and an optimal Shannon entropy of up to 7.9991 bits/symbol, establishing a new generalized paradigm for quantum-resilient data security.

Authors

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-08-28
DOI
https://doi.org/10.5281/zenodo.22146475
Primary Topic
Chaos-based Image/Signal Encryption
Type
preprint
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
preprint

The Fractal Spectral Wave Filter: A Quantum-Resilient Cryptographic Primitive Harnessing the Aliasing Collisions

Venkata Rajasekhara Reddy Lakkasani
Zenodo (CERN European Organization for Nuclear Research)
Chaos-based Image/Signal Encryption
preprint

The Fractal Spectral Wave Filter: A Quantum-Resilient Cryptographic Primitive Harnessing the Aliasing Collisions

Venkata Rajasekhara Reddy Lakkasani
preprint en

Abstract

The rapid evolution of Quantum Computing poses a significant threat to the standard mathematical foundations of classical cryptography, prompting the global transition towards Post-Quantum Cryptography (PQC). While NIST is standardising lattice-based algorithms, chaotic cryptography continues to struggle with high-dimensional data, as traditional models require O(N^3) computational time and suffer from catastrophic memory overhead. Building upon prior optimization frameworks designed to eliminate cubic computational bottlenecks in chaotic systems [6], this paper introduces a novel cryptographic framework centered on the Fractal Spectral Wave Filter. By mapping arbitrary two-dimensional spatial data into a one-dimensional array using the Morton Z-order curve, we preserve local data relationships without dense matrix overhead. The system then utilizes the Number Theoretic Transform (NTT) over finite Galois integer rings—forming the core mathematical framework of NIST's PQC standards—for frequency-domain processing. Furthermore, by intentionally omitting standard zero-padding, the resulting unmitigated aliasing collisions act as a secure, lossless fractal scrambler, diffusing data in strict O(N log N) time. Experimental validations demonstrate perfect lossless recovery (MSE of 0.000000) and an optimal Shannon entropy of up to 7.9991 bits/symbol, establishing a new generalized paradigm for quantum-resilient data security.

Zenodo (CERN European Organization for Nuclear Research)
Chaos-based Image/Signal Encryption
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.