An Overview of Backdoor Attacks Against Deep Neural Networks and Possible Defences

Understand

Together with impressive advances touching every aspect of our society, AI technology based on Deep Neural Networks (DNN) is bringing increasing security concerns.

• While attacks operating at test time have monopolised the initial attention of researchers, backdoor attacks, exploiting the possibility of corrupting DNN models by interfering with the training process, represents a further serious threat undermining the dependability of AI techniques.
• In a backdoor attack, the attacker corrupts the training data so to induce an erroneous behaviour at test time.
• Test time errors, however, are activated only in the presence of a triggering event corresponding to a properly crafted input sample.