Healthcare data continues to grow in size and complexity. Hence, there's a rising need for more scalable and accurate prediction models. This study presents a framework that combines big data processing with advan...
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Vision transformers (ViTs) perform exceptionally well in various computer vision tasks but remain vulnerable to adversarial attacks. Recent studies have shown that the transferability of adversarial examples exists fo...
Vision transformers (ViTs) perform exceptionally well in various computer vision tasks but remain vulnerable to adversarial attacks. Recent studies have shown that the transferability of adversarial examples exists for CNNs, and the same holds true for ViTs. However, existing ViT attacks aggressively regularize the largest token gradients to exact zero within each layer of the surrogate model, overlooking the interactions between layers, which limits their transferability in attacking black-box models. Therefore, in this paper, we focus on boosting the transferability of adversarial attacks on ViTs through adaptive token tuning (ATT). Specifically, we propose three optimization strategies: an adaptive gradient re-scaling strategy to reduce the overall variance of token gradients, a self-paced patch out strategy to enhance the diversity of input tokens, and a hybrid token gradient truncation strategy to weaken the effectiveness of attention mechanism. We demonstrate that scaling correction of gradient changes using gradient variance across different layers can produce highly transferable adversarial examples. In addition, introducing attentional truncation can mitigate the overfitting over complex interactions between tokens in deep ViT layers to further improve the transferability. On the other hand, using feature importance as a guidance to discard a subset of perturbation patches in each iteration, along with combining self-paced learning and progressively more sampled attacks, significantly enhances the transferability over attacks that use all perturbation patches. Extensive experiments conducted on ViTs, undefended CNNs, and defended CNNs validate the superiority of our proposed ATT attack method. On average, our approach improves the attack performance by 10.1% compared to state-of-the-art transfer-based attacks. Notably, we achieve the best attack performance with an average of 58.3% on three defended CNNs. Code is available at https://***/MisterRpeng/
Distributed self-adaptive system is a multi-component collaborative system that automatically adjusts its behavior and structure through adaptive mechanisms to maintain system performance and stability in dynamic envi...
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The Internet of Things (IoT) is a constantly expanding system connecting countless devices for seamless data collection and exchange. This has transformed decision-making with data-driven insights across different dom...
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Diabetic Retinopathy (DR) and Diabetic Macular Edema (DME) are major causes of vision loss in diabetic patients. Early detection is crucial for preventing permanent vision impairment. This research paper proposes a no...
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Under the wave of digital transformation, remote collaboration has become the new normal in the daily operation of enterprises. But at the same time, the risk of sensitive data leakage and the insufficiency of protect...
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Healthcare providers and researchers that work with patients who have cervical cancer face a significant challenge because it is one of the world's most common causes of death. Worldwide, cervical cancer is one of...
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Essay are considered as the most prominent way in assessing the student performance. Manual grading of the essay are considered to be a hectic tasks for both students and instructors due to various reasons such as tim...
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Lithium-ion batteries are integral to various systems, including electric vehicles and warehouses, where estimating their operational lifespan is critical. This lifespan, known as Remaining Useful Life (RUL), helps in...
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Object tracking has proven to be an essential in a wide range of applications and unmanned aerial vehicles (UAVs) provide advantages to this field in accurately observing and tracking moving targets in challenging env...
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