In wireless communication transmission,image encryption plays a key role in protecting data privacy against unauthorized access.However,conventional encryption methods often face challenges in key space security,parti...In wireless communication transmission,image encryption plays a key role in protecting data privacy against unauthorized access.However,conventional encryption methods often face challenges in key space security,particularly when relying on chaotic sequences,which may exhibit vulnerabilities to brute-force and predictability-based attacks.To address the limitations,this paper presents a robust and efficient encryption scheme that combines iterative hyper-chaotic systems and Convolutional Neural Networks(CNNs).Firstly,a novel two-dimensional iterative hyper-chaotic system is proposed because of its complex dynamic behavior and expanded parameter space,which can enhance the key space complexity and randomness,ensuring resistance against cryptanalysis.Secondly,an innovative CNN architecture is introduced for generating the key stream for the cryptographic system.CNN architecture exhibits excellent nonlinearity and can further optimize the key generation process.To rigorously evaluate the encryption performance,extensive simulation analyses were conducted,including visualization,statistical histogram,information entropy,correlation,differential attack,and resistance.The method has shown a high NPCR(Number of Pixel Change Rate)of 99.642%and a UACI(Unified Average Changing Intensity)value of 33.465%,exhibiting powerful resistance to differential attacks.A series of comprehensive experimental tests have illustrated that the proposed scheme exhibits superior distribution characteristics,which underscores the robustness and efficacy of the image encryption,and helps for communication security.展开更多
Remote sensing images carry crucial ground information,often involving the spatial distribution and spatiotemporal changes of surface elements.To safeguard this sensitive data,image encryption technology is essential....Remote sensing images carry crucial ground information,often involving the spatial distribution and spatiotemporal changes of surface elements.To safeguard this sensitive data,image encryption technology is essential.In this paper,a novel Fibonacci sine exponential map is designed,the hyperchaotic performance of which is particularly suitable for image encryption algorithms.An encryption algorithm tailored for handling the multi-band attributes of remote sensing images is proposed.The algorithm combines a three-dimensional synchronized scrambled diffusion operation with chaos to efficiently encrypt multiple images.Moreover,the keys are processed using an elliptic curve cryptosystem,eliminating the need for an additional channel to transmit the keys,thus enhancing security.Experimental results and algorithm analysis demonstrate that the algorithm offers strong security and high efficiency,making it suitable for remote sensing image encryption tasks.展开更多
基金supported in part by the National Key Research and Development Program of China(No.2021YFB3101500)the Fundamental Research Funds for the Central Universities(No.2023RC69).
文摘In wireless communication transmission,image encryption plays a key role in protecting data privacy against unauthorized access.However,conventional encryption methods often face challenges in key space security,particularly when relying on chaotic sequences,which may exhibit vulnerabilities to brute-force and predictability-based attacks.To address the limitations,this paper presents a robust and efficient encryption scheme that combines iterative hyper-chaotic systems and Convolutional Neural Networks(CNNs).Firstly,a novel two-dimensional iterative hyper-chaotic system is proposed because of its complex dynamic behavior and expanded parameter space,which can enhance the key space complexity and randomness,ensuring resistance against cryptanalysis.Secondly,an innovative CNN architecture is introduced for generating the key stream for the cryptographic system.CNN architecture exhibits excellent nonlinearity and can further optimize the key generation process.To rigorously evaluate the encryption performance,extensive simulation analyses were conducted,including visualization,statistical histogram,information entropy,correlation,differential attack,and resistance.The method has shown a high NPCR(Number of Pixel Change Rate)of 99.642%and a UACI(Unified Average Changing Intensity)value of 33.465%,exhibiting powerful resistance to differential attacks.A series of comprehensive experimental tests have illustrated that the proposed scheme exhibits superior distribution characteristics,which underscores the robustness and efficacy of the image encryption,and helps for communication security.
基金supported by the National Natural Science Foundation of China(Grant No.91948303)。
文摘Remote sensing images carry crucial ground information,often involving the spatial distribution and spatiotemporal changes of surface elements.To safeguard this sensitive data,image encryption technology is essential.In this paper,a novel Fibonacci sine exponential map is designed,the hyperchaotic performance of which is particularly suitable for image encryption algorithms.An encryption algorithm tailored for handling the multi-band attributes of remote sensing images is proposed.The algorithm combines a three-dimensional synchronized scrambled diffusion operation with chaos to efficiently encrypt multiple images.Moreover,the keys are processed using an elliptic curve cryptosystem,eliminating the need for an additional channel to transmit the keys,thus enhancing security.Experimental results and algorithm analysis demonstrate that the algorithm offers strong security and high efficiency,making it suitable for remote sensing image encryption tasks.
