Research on the development of adversarial attacks based on deep learning
With the widespread application of deep learning in various fields,the issue of adversarial attacks has attracted at-tention from both academia and industry.Firstly,the background of adversarial attacks is outlined,including the definition,classifi-cation,and differences from traditional machine learning security issues.Then we discussed adversarial sample generation and at-tack strategies,as well as attack methods such as white box and black box attacks.Finally,the significance of adversarial attacks was summarized,and future research directions were looked forward to improving the security and reliability of deep learning mod-els through research and exploration.
deep learningadversarial attacksdata attacksmodel attacksdefense strategies
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