Chaos theory has been widely utilized in password design, resulting in an encryption algorithm that exhibits strong security and high efficiency. However, rapid advancements in cryptanalysis technology have rendered single system generated sequences susceptible to tracking and simulation, compromising encryption algorithm security. To address this issue, we propose an image encryption algorithm based on hybrid heterogeneous time-delay chaotic systems. Our algorithm utilizes a collection of sequences generated by multiple heterogeneous time-delay chaotic systems, rather than sequences from a single chaotic system. Specifically, three sequences are randomly assigned to image pixel scrambling and diffusion operations. Furthermore, the time-delay chaotic system comprises multiple hyperchaotic systems with positive Lyapunov exponents, exhibiting a more complex dynamic behavior than non-delay chaotic systems. Our encryption algorithm is developed by a plurality of time-delay chaotic systems, thereby increasing the key space, enhancing security, and making the encrypted image more difficult to crack. Simulation experiment results verify that our algorithm exhibits superior encryption efficiency and security compared to other encryption algorithms.

In response to the critical challenges of securing multi-image transmissions in cloud and 5G/6G networks, this paper proposes an innovative encryption algorithm that synergistically combines hybrid chaotic maps with computer-generated holography (CGH). The authors introduce three groundbreaking contributions: (1) A novel integrated chaotic system (NICS) fusing logistic, sinus, and tent mappings through modular arithmetic to achieve full-range chaos with a ${10}^{84}$ key space and 40% higher Lyapunov exponents; (2) An enhanced Gerchberg Saxton algorithm incorporating adaptive feedback to accelerate convergence by 35% while enabling parallel encryption of eight $512\times 512$ images; (3) A dynamic secure hash algorithm 256 (SHA-256) bits based key binding mechanism that resists chosen plaintext attacks. Extensive experiments validate the exceptional performance metrics: Information entropy approaching the theoretical maximum (7.992±0.005), near-zero adjacent pixel correlation (< 0.004), and robust resistance to noise (20%) and cropping attacks (60% recovery at 60% loss). The algorithm's practical superiority is demonstrated through 2.3× faster processing speeds compared with conventional methods, along with successful deployments in medical imaging and military communication systems, establishing a new benchmark for secure multi-image transmission in next-generation networks.

Understanding the dynamics of the propagation of computer viruses is crucial for the development of effective cybersecurity strategies. This paper proposes a novel compartmental model based on the traditional SIR framework, which incorporats the Beddington-DeAngelis functional response to capture the inhibitory effects of the modern operating systems' built-in security mechanisms. We rigorously establish the well-posedness of the model by proving the non-negativity and boundedness of solutions. The existence and stability of equilibrium points are thoroughly analyzed using the Hurwitz criterion, Lyapunov functions, and Dulac criterion. Numerical simulations validate our theoretical findings and demonstrate the significant role of the system self-protection parameters in controlling virus spread. Unlike previous models, our approach provides explicit connections between the model parameters and real-world cybersecurity metrics, thus offering practical insights for network defense strategies. The model's ability to maintain a persistent infected state aligns with the observed behaviors of modern malware, thus providing a more realistic representation of the dynamics of computer viruses. The study employs advanced visualization techniques, including three-dimensional surface plots to elucidate the complex interactions between protection parameters, thus providing actionable insights for the design and implementation of cybersecurity policies.