article · IEEE Internet of Things Journal
Chaotic systems are widely used in cryptography and pseudorandom number generation because they produce pseudo-random signals. Introducing a nonlinear memristor to a Cubic map creates a discrete mapping known as the two-dimensional memristive Cubic map (2D-MCM). This system exhibits complex dynamical behaviour, a wide parameter space, and boosting bifurcation behaviour. As control parameters rise, the map produces an expanded range of values, enabling the generation of a greater volume of pseudo-random sequences. Physical capture of the system attractors was confirmed through a dedicated hardware platform. Additionally, a video encryption algorithm built on this map was developed to selectively encrypt specific areas within video streams. In testing, the encrypted video achieved near-zero correlation coefficients across horizontal, vertical, and diagonal directions, demonstrating strong suitability for video encryption tasks.
Digital video communication requires robust cryptographic techniques to protect sensitive visual data from interception and unauthorised access. By enhancing the randomness and complexity of chaotic signals through memristive components, secure systems can generate stronger encryption keys. This research demonstrates that such mathematical models can be realised in physical hardware and effectively protect targeted sections of video content with minimal statistical correlation.
The approach targets applications in secure video transmission, digital surveillance, and selective media encryption where specific regions of interest require protection. Potential users include developers of secure communications hardware and video protection software. The technology appears to be at an applied and tested stage, having progressed from theoretical mathematical modelling to physical hardware attractor capture and experimental video encryption simulations.
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Chaos systems find extensive applications in cryptography and pseudorandom number generation due to their ability to generate pseudo-random signals. This paper focuses on enhancing the complexity of chaotic systems by introducing the memristor, a nonlinear component. We propose a novel map called the 2D memristive Cubic map (2D-MCM), which integrates the memristor with the Cubic map to create a discrete mapping. The 2D-MCM exhibits rich dynamical behavior and a broad parameter space. Notably, the 2D-MCM displays boosting bifurcation behavior. As the control parameters increase, the 2D-MCM demonstrates an expanded range of values, indicating its ability to generate a larger number of pseudo-random sequences. To validate its performance, we establish a hardware platform to physically capture the attractors of the 2D-MCM. To verify the performance of the 2D-MCM in generating pseudorandom sequences, we designed a video encryption algorithm based on the 2D-MCM. This algorithm selectively encrypts specific areas within the video, with correlation coefficients of the encrypted video in the horizontal, vertical, and diagonal directions being 0.0002, -0.0005, and 0.0004, respectively. Through simulation experiments and security analysis, we demonstrate that the 2D-MCM performs well in video encryption tasks.
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DOI: 10.1109/jiot.2024.3376572
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