Because of its on-demand servicing and scalability features in cloud computing,security and confidentiality have converted to key concerns.Maintaining transaction information on thirdparty servers carries significant ...Because of its on-demand servicing and scalability features in cloud computing,security and confidentiality have converted to key concerns.Maintaining transaction information on thirdparty servers carries significant dangers so that malicious individuals trying for illegal access to information data security architecture.This research proposes a security-aware information transfer in the cloud-based on the blowfish algorithm(BFA)to address the issue.The user is verified initially with the identification and separate the imported data using pattern matching technique.Further,BFA is utilised to encrypt and save the data in cloud.This can safeguard the data and streamline the proof so that client cannot retrieve the information without identification which makes the environment secure.The suggested approach’s performance is evaluated using several metrics,including encryption time,decryption time,memory utilisation,and runtime.Compared to the existing methodology,the investigational findings clearly show that the method takes the least time to data encryption.展开更多
Encrypted communication using artificial intelligence is a new challenging research direction.GoogleBrain first proposed the generation of encrypted communication based on Generative Adversarial Networks,resulting in ...Encrypted communication using artificial intelligence is a new challenging research direction.GoogleBrain first proposed the generation of encrypted communication based on Generative Adversarial Networks,resulting in related discussions and research.In the encrypted communication model,when part of the plaintext is leaked to the attacker,it will cause slow decryption or even being unable to decrypt the communication party,and the high success rate of the attacker decryption,making the encrypted communication no longer secure.In the case of 16-bit plaintext symmetrical encrypted communication,the neural network model used in the original encrypted communicationwas optimized.The optimized communication party can complete the decryption within 1000 steps,and the error rate of the attacker is increased to more than 0.9 without affecting the decryption of the communicator,which reduces the loss rate of the entire communication to less than 0.05.The optimized neural network can ensure secure encrypted communication of information.展开更多
基金This work is supported by the National Natural Science Foundation of China （No. 69874038）, the National High-Tech Research and Development Plan of China （No. 2001AA115300） and the Natural Science Foundation of Liaoning Province of China （No. 20031018）.
文摘Because of its on-demand servicing and scalability features in cloud computing,security and confidentiality have converted to key concerns.Maintaining transaction information on thirdparty servers carries significant dangers so that malicious individuals trying for illegal access to information data security architecture.This research proposes a security-aware information transfer in the cloud-based on the blowfish algorithm(BFA)to address the issue.The user is verified initially with the identification and separate the imported data using pattern matching technique.Further,BFA is utilised to encrypt and save the data in cloud.This can safeguard the data and streamline the proof so that client cannot retrieve the information without identification which makes the environment secure.The suggested approach’s performance is evaluated using several metrics,including encryption time,decryption time,memory utilisation,and runtime.Compared to the existing methodology,the investigational findings clearly show that the method takes the least time to data encryption.
基金The National Natural Science Foundation of China(No.61572521)Engineering University of PAP Innovation Team Science Foundation(No.KYTD201805)Natural Science Basic Research Plan in Shaanxi Province of China(2021JM252).
文摘Encrypted communication using artificial intelligence is a new challenging research direction.GoogleBrain first proposed the generation of encrypted communication based on Generative Adversarial Networks,resulting in related discussions and research.In the encrypted communication model,when part of the plaintext is leaked to the attacker,it will cause slow decryption or even being unable to decrypt the communication party,and the high success rate of the attacker decryption,making the encrypted communication no longer secure.In the case of 16-bit plaintext symmetrical encrypted communication,the neural network model used in the original encrypted communicationwas optimized.The optimized communication party can complete the decryption within 1000 steps,and the error rate of the attacker is increased to more than 0.9 without affecting the decryption of the communicator,which reduces the loss rate of the entire communication to less than 0.05.The optimized neural network can ensure secure encrypted communication of information.
