## 1 Introduction
Unlike conventional encryption-based security methods, chaos-based communication systems rely on simple analog chaos oscillators, making them well-suited for energy-efficient and lightweight implementations. These systems enable secure transmission from low-power sensors to larger network nodes without the need for complex operations, addressing key challenges in resource-constrained IoT environments [10]. Chaotic systems such as the Lorenz and Chua circuits have been effectively utilized in chaos-based communication systems to secure data transmissions [15; 16; 17]. These systems generate chaotic waveforms characterized by high sensitivity to initial conditions and noise-like waveforms, making them ideal for encoding sensitive information. In such implementations, the transmitter and receiver must achieve precise synchronization to decode the transmitted data, providing an additional layer of security. Any disruption in synchronization renders the intercepted signal unreadable, significantly complicating unauthorized access [18; 19]. Chaos-based modulation techniques, such as differential chaos shift keying (DCSK), further enhance PLS by resisting eavesdropping. These methods utilize chaotic signals' wideband and nonperiodic nature, making them particularly suited for IoT environments where low-power, high-security solutions are required. Unlike traditional key-based approaches, chaos-based systems inherently ensure difficult-to-intercept without needing pre-shared keys, reducing overhead and simplifying implementation [14; 19]. Recent research has further expanded the applicability of chaos-based communication systems, particularly in multi-carrier and MIMO configurations, to enhance security and spectral efficiency. Multi-carrier implementations of chaos shift keying (CSK) and its derivatives improve signal robustness while maintaining the inherent unpredictabilityof chaotic waveforms, making them resistant to eavesdropping and interference [20]. Additionally, synchronization stability remains a critical aspect, as efficient drive-response synchronization enables accurate data recovery even in noisy environments. Studies on breaking time correlation among state variables have demonstrated enhanced security by minimizing the predictability of transmitted signals, further reinforcing chaos-based methods as viable solutions for secure IoT communication [21]. Researchers are developing advanced chaotic models to overcome limitations in existing systems, such as lower complexity and improved sensitivity and resilience to noise. Innovations like the Exponential Chaotic Model have introduced robust chaos, ensuring reliability even in noisy channels and offering new possibilities for secure communication [22; 23]. Beyond communication, chaos has found applications in multimedia security and random number generation. Advanced image encryption algorithms based on dynamic chaotic systems provide robustness against statistical and differential attacks and ensure data integrity in IoT environments [24; 25; 26; 27]. While the integration of chaos into PLS represents a significant leap forward, challenges remain. Active research areas include synchronization under varying channel conditions, efficient implementation in resource-limited devices, and the potential vulnerabilities of chaotic systems. Despite these constraints, chaos-based PLS offers a compelling pathway for IoT security, blending innovation with practicality to address the unique challenges of modern networks [28; 29]. Synchronization is a crucial part of chaos-based communication systems, which allows them to safely send and receive data in IoT and wireless sensor networks. At its core, chaotic synchronization ensures that the state variables of a receiver's chaotic oscillator replicate those of the transmitter's oscillator, enabling precise signal decoding. Techniques like the Pecora-Carroll method [30] and adaptive control [31; 32] are commonly used to achieve synchronization by coupling specific state variables between drive and response oscillators.