The decay diagrams of radioactive nuclei are the obvious indication of the main properties shown by the nuclei at low states of excitement and of the basic aspects of nuclear physics.They are extensively applied in in...The decay diagrams of radioactive nuclei are the obvious indication of the main properties shown by the nuclei at low states of excitement and of the basic aspects of nuclear physics.They are extensively applied in industry’,agriculture,energy,national defense,medical science,the environment,and metrology,as well as in astronomy,archaeology,geology,biology,chemistry and other basic sciences.Therefore,they are always focuses of interest.展开更多
Deep neural networks(DNNs)are widely adopted in daily life and the security problems of DNNs have drawn attention from both scientific researchers and industrial engineers.Many related works show that DNNs are vulnera...Deep neural networks(DNNs)are widely adopted in daily life and the security problems of DNNs have drawn attention from both scientific researchers and industrial engineers.Many related works show that DNNs are vulnerable to adversarial examples that are generated with subtle perturbation to original images in both digital domain and physical domain.As a most common application of DNNs,face recognition systems are likely to cause serious consequences if they are attacked by the adversarial examples.In this paper,we implement an adversarial attack system for face recognition in both digital domain that generates adversarial face images to fool the recognition system,and physical domain that generates customized glasses to fool the system when a person wears the glasses.Experiments show that our system attacks face recognition systems effectively.Furthermore,our system could misguide the recognition system to identify a person wearing the customized glasses as a certain target.We hope this research could help raise the attention of artificial intelligence security and promote building robust recognition systems.展开更多
文摘The decay diagrams of radioactive nuclei are the obvious indication of the main properties shown by the nuclei at low states of excitement and of the basic aspects of nuclear physics.They are extensively applied in industry’,agriculture,energy,national defense,medical science,the environment,and metrology,as well as in astronomy,archaeology,geology,biology,chemistry and other basic sciences.Therefore,they are always focuses of interest.
基金This work is supported in part by the National Natural Science Foundation of China under Grant 61902082,U1636215the Guangdong Province Key research and Development Plan under Grant 2019B010136003.
文摘Deep neural networks(DNNs)are widely adopted in daily life and the security problems of DNNs have drawn attention from both scientific researchers and industrial engineers.Many related works show that DNNs are vulnerable to adversarial examples that are generated with subtle perturbation to original images in both digital domain and physical domain.As a most common application of DNNs,face recognition systems are likely to cause serious consequences if they are attacked by the adversarial examples.In this paper,we implement an adversarial attack system for face recognition in both digital domain that generates adversarial face images to fool the recognition system,and physical domain that generates customized glasses to fool the system when a person wears the glasses.Experiments show that our system attacks face recognition systems effectively.Furthermore,our system could misguide the recognition system to identify a person wearing the customized glasses as a certain target.We hope this research could help raise the attention of artificial intelligence security and promote building robust recognition systems.
