Results 31 to 40 of about 3,211,731 (245)
Adversarial attacks and defenses in deep learning
网络与信息安全学报, 2020 The adversarial example is a modified image that is added imperceptible perturbations, which can make deep neural networks decide wrongly. The adversarial examples seriously threaten the availability of the system and bring great security risks to the ...
LIU Ximeng +2 more
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IEEE Access, 2020 With the rapid development of artificial intelligence, the intellectual property protection of deep learning models appeals widespread concerns of scientists and engineers.
Ying-Qian Zhang +4 more
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Black-box adversarial attacks through speech distortion for speech emotion recognition
EURASIP Journal on Audio, Speech, and Music Processing, 2022 Speech emotion recognition is a key branch of affective computing. Nowadays, it is common to detect emotional diseases through speech emotion recognition.
Jinxing Gao, Diqun Yan, Mingyu Dong
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NbuGAN: high-speed black-box attack for high-resolution adversarial image generation
Journal of Information and TelecommunicationClassification models have emerged as the primary tools for numerous automatic computer vision tasks. However, they are susceptible to adversarial attacks, that can be harmful, but can also be employed to protect private information from classification ...
Ali Osman Topal +3 more
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Adversarial attacks and adversarial robustness in computational pathology
Nature Communications, 2022 Artificial Intelligence can support diagnostic workflows in oncology, but they are vulnerable to adversarial attacks. Here, the authors show that convolutional neural networks are highly susceptible to white- and black-box adversarial attacks in ...
Narmin Ghaffari Laleh +10 more
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FEBS Letters, EarlyView.Encapsulins are protein nanocompartments that play an important role in iron storage. In the Myxococcus xanthus encapsulin system, two cargo proteins called EncB and EncC contribute to iron mineralization. Here, we show that EncB and EncC generate iron‐containing minerals with distinct chemical compositions, suggesting that the composition of stored ...
Harry B. McDowell +2 more
wiley +1 more source
Adversarial Attacks Against Binary Similarity Systems
IEEE AccessBinary analysis has become essential for software inspection and security assessment. As the number of software-driven devices grows, research is shifting towards autonomous solutions using deep learning models. In this context, a hot topic is the binary
Gianluca Capozzi +3 more
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Black-box Adversarial Attacks in Autonomous Vehicle Technology [PDF]
, 2020 Despite the high quality performance of the deep neural network in real-world applications, they are susceptible to minor perturbations of adversarial attacks. This is mostly undetectable to human vision.
K. Naveen Kumar +7 more
core +1 more source
Tumour–host interactions in Drosophila: mechanisms in the tumour micro‐ and macroenvironment
Molecular Oncology, EarlyView.This review examines how tumour–host crosstalk takes place at multiple levels of biological organisation, from local cell competition and immune crosstalk to organism‐wide metabolic and physiological collapse. Here, we integrate findings from Drosophila melanogaster studies that reveal conserved mechanisms through which tumours hijack host systems to ...
José Teles‐Reis, Tor Erik Rusten
wiley +1 more source
A Random Ensemble of Encrypted Vision Transformers for Adversarially Robust Defense
IEEE AccessDeep neural networks (DNNs) are well known to be vulnerable to adversarial examples (AEs). In previous studies, the use of models encrypted with a secret key was demonstrated to be robust against white-box attacks, but not against black-box ones. In this
Ryota Iijima +2 more
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