English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

Adversarial examples generated from surrogate models often possess theability to deceive other black-box models, a property known as transferability.Recent research has focused on enhancing adversarial transferability, withinput transformation being one of the most effective approaches. However,existing input transformation methods suffer from two issues. Firstly, certainmethods, such as the Scale-Invariant Method, employ exponentially decreasingscale invariant parameters that decrease the adaptability in generatingeffective adversarial examples across multiple scales. Secondly, most mixupmethods only linearly combine candidate images with the source image, leadingto reduced features blending effectiveness. To address these challenges, wepropose a framework called Uniform Scale and Mix Mask Method (US-MM) foradversarial example generation. The Uniform Scale approach explores the upperand lower boundaries of perturbation with a linear factor, minimizing thenegative impact of scale copies. The Mix Mask method introduces masks into themixing process in a nonlinear manner, significantly improving the effectivenessof mixing strategies. Ablation experiments are conducted to validate theeffectiveness of each component in US-MM and explore the effect ofhyper-parameters. Empirical evaluations on standard ImageNet datasetsdemonstrate that US-MM achieves an average of 7% better transfer attack successrate compared to state-of-the-art methods.

Boost Adversarial Transferability by Uniform Scale and Mix Mask Method