Achievements

Scientific Contributions

Over the past few years, the group has produced an extensive body of peer-reviewed, Scopus- and Web of Science–indexed publications, covering:

Advanced chaotic map integrations for digital image, audio, and text encryption.
Efficient cryptographic algorithms ensuring high entropy, resistance to differential attacks, and fast computational performance.
Innovative techniques combining the Collatz conjecture, matrix algebra, and logistic–H´enon chaotic maps to generate ultra-secure keys.
Development of encryption frameworks that integrate machine learning and deep feature extraction for intelligent data security systems.

These contributions have been disseminated through IEEE Access, Journal of Cybersecurity and Privacy, Cryptography, Symmetry, Treatment du Signal, and Applied Mathematics & Information Sciences, among others.

Leading Software and Tool Solutions

The group has successfully designed and implemented several research-grade tools and software frameworks that extend the boundaries of applied cryptography:

ChaosCrypt Suite – A modular cryptographic framework for image, text, and audio data, integrating multiple chaotic systems (Logistic, H´enon, and Collatz-based models). Supports key expansion, multi-round substitution, and real-time encryption visualization. Developed in C++/Python, optimized for GPU-enabled HPC environments.
CASDC Framework (Cryptographically Secure Data System using Dual Private Keys) – Introduced in IEEE Access (2022), this tool implements dual-image key generation and parallelized encryption, offering both strong security and high throughput for multimedia protection.
Chaotic Key Generator (CKG) – A lightweight and portable utility for producing cryptographically strong keys based on logistic and H´enon chaotic maps, ensuring enhanced randomness and unpredictability.
SecureAudio Lab – Developed from the group’s ACR’25 publication, it provides speech encryption and segmentation-based chaotic key integration for secure transmission of voice data in IoT and cloud systems.
CryptoML Analyzer – A hybrid AI–cryptography evaluation platform used to assess encryption robustness using entropy measures, correlation coefficients, NPCR/UACI metrics, and adversarial testing.

Recognized Publications and Impact

The group’s publications have collectively advanced the field of chaos-based cryptography and post-quantum resilience. Notable examples include:

Chaotic H´enon–Logistic Map Integration (Journal of Cybersecurity and Privacy, 2025): Proposed a powerful dual-map encryption method achieving superior randomness distribution in pixel and key-space analysis.
Collatz Conjecture–Driven Key Generation (IEEE Access, 2024): A first-of-its-kind framework linking number theory to chaos-based encryption.
CASDC: Dual Private Key Image Cryptosystem (IEEE Access, 2022): Pioneered multi-key dynamic encryption resistant to brute-force and differential attacks.
Complex Matrix Private Key Method (Symmetry, 2022): Enhanced classical chaotic encryption using structured matrix transformations.
Hybrid Parallel Cryptography Framework (AMIS, 2022): Improved efficiency and scalability of median filters and encryption models through two-stage window generation.

Trending

Test trending

Achievements