Hybrid DFA-Chaos Cryptosystem for Secure IoT Data Transmission on Resource-Constrained Devices

The rapid proliferation of Internet of Things (IoT) devices in resource-limited environments poses significant security challenges, as traditional cryptographic methods are often too slow and resource-intensive for systems with limited power and memory. This study addresses these issues through the development of a novel hybrid cryptosystem that combines Deterministic Finite Automata (DFA)-based hashing with Lorenz attractor-driven encryption for secure IoT data transmission. The approach is twofold: first, hash values are generated from fixed sensor data sources; second, the Lorenz chaotic system uses this data as initial conditions to generate unpredictable encryption keys. The system employs lightweight XOR-based encryption, making it well suited for microcontrollers. A working prototype was developed and implemented on Arduino platforms using the Wokwi simulation environment and tested with real sensor inputs (temperature and photoresistor). Experimental results show excellent performance: zero hash collisions for 1,000 input values ranging from 0 to 1023, total key unpredictability even with minimal input changes, and encryption time under 120 ms on Arduino Uno. The system achieves robust security and 100% accuracy in tampering detection, while consuming less than 20% of the available memory on the microcontroller. Its successful implementation demonstrates the feasibility of hybrid DFA-chaos cryptography in embedded IoT environments.

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Publication Details

Journal
International Journal of Innovative Research and Scientific Studies
Published
2025-09-19
DOI
https://doi.org/10.53894/ijirss.v8i6.10076
Primary Topic
Chaos-based Image/Signal Encryption
Type
article
Field-Weighted Citation Impact
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article

Hybrid DFA-Chaos Cryptosystem for Secure IoT Data Transmission on Resource-Constrained Devices

Akbota Kulzhanova, Talgat Mazakov, Sholpan Jomartova, Vadim Zhmud et al.
International Journal of Innovative Research and Scientific Studies
Chaos-based Image/Signal Encryption
article

Hybrid DFA-Chaos Cryptosystem for Secure IoT Data Transmission on Resource-Constrained Devices

Akbota Kulzhanova, Talgat Mazakov, Sholpan Jomartova, Vadim Zhmud, Aigerim Mazakova
article en

Abstract

The rapid proliferation of Internet of Things (IoT) devices in resource-limited environments poses significant security challenges, as traditional cryptographic methods are often too slow and resource-intensive for systems with limited power and memory. This study addresses these issues through the development of a novel hybrid cryptosystem that combines Deterministic Finite Automata (DFA)-based hashing with Lorenz attractor-driven encryption for secure IoT data transmission. The approach is twofold: first, hash values are generated from fixed sensor data sources; second, the Lorenz chaotic system uses this data as initial conditions to generate unpredictable encryption keys. The system employs lightweight XOR-based encryption, making it well suited for microcontrollers. A working prototype was developed and implemented on Arduino platforms using the Wokwi simulation environment and tested with real sensor inputs (temperature and photoresistor). Experimental results show excellent performance: zero hash collisions for 1,000 input values ranging from 0 to 1023, total key unpredictability even with minimal input changes, and encryption time under 120 ms on Arduino Uno. The system achieves robust security and 100% accuracy in tampering detection, while consuming less than 20% of the available memory on the microcontroller. Its successful implementation demonstrates the feasibility of hybrid DFA-chaos cryptography in embedded IoT environments.

International Journal of Innovative Research and Scientific StudiesVol. 8(6)
Al-Farabi Kazakh National University (KZ), Institute of Laser Physics (RU)
Openalex Percentile: Top 75%
Chaos-based Image/Signal Encryption
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Hybrid DFA-Chaos Cryptosystem for Secure IoT Data Transmission on Resource-Constrained Devices — Akbota Kulzhanova, Talgat Mazakov, et al. · International Journal of Innovative Research and Scientific Studies (2025) | TGRS Research Map | TGRS