Results 21 to 30 of about 504,342 (225)
, 2017 Deep neural networks (DNNs) are one of the most prominent technologies of our time, as they achieve state-of-the-art performance in many machine learning tasks, including but not limited to image classification, text mining, and speech processing ...
Chen, Pin-Yu +4 more
core +1 more source
Cube Attacks on Tweakable Black Box Polynomials [PDF]
, 2009 Almost any cryptographic scheme can be described by tweakable polynomials over GF (2), which contain both secret variables (e.g., key bits) and public variables (e.g., plaintext bits or IV bits). The cryptanalyst is allowed to tweak the polynomials by choosing arbitrary values for the public variables, and his goal is to solve the resultant system of ...
Itai Dinur, Adi Shamir
openaire +2 more sources
Generic Black-Box End-to-End Attack Against State of the Art API Call Based Malware Classifiers
, 2018 In this paper, we present a black-box attack against API call based machine learning malware classifiers, focusing on generating adversarial sequences combining API calls and static features (e.g., printable strings) that will be misclassified by the ...
G Tandon +4 more
core +1 more source
Black-box Adversarial Attacks with Bayesian Optimization
CoRR, 2019 We focus on the problem of black-box adversarial attacks, where the aim is to generate adversarial examples using information limited to loss function evaluations of input-output pairs. We use Bayesian optimization~(BO) to specifically cater to scenarios involving low query budgets to develop query efficient adversarial attacks. We alleviate the issues
Satya Narayan Shukla +3 more
openaire +2 more sources
Efficient Decision-based Black-box Adversarial Attacks on Face Recognition
, 2019 Face recognition has obtained remarkable progress in recent years due to the great improvement of deep convolutional neural networks (CNNs). However, deep CNNs are vulnerable to adversarial examples, which can cause fateful consequences in real-world ...
Dong, Yinpeng +6 more
core +1 more source
Art-Attack: Black-Box Adversarial Attack via Evolutionary Art
CoRR, 2022 Deep neural networks (DNNs) have achieved state-of-the-art performance in many tasks but have shown extreme vulnerabilities to attacks generated by adversarial examples. Many works go with a white-box attack that assumes total access to the targeted model including its architecture and gradients.
Phoenix Neale Williams, Ke Li 0001
openaire +2 more sources
AAA+ protein unfoldases—the Moirai of the proteome
FEBS Letters, EarlyView.AAA+ unfoldases are essential molecular motors that power protein degradation and disaggregation. This review integrates recent cryo‐electron microscopy (cryo‐EM) structures and single‐molecule biophysical data to reconcile competing models of substrate translocation.
Stavros Azinas, Marta Carroni
wiley +1 more source
FEBS Letters, EarlyView.The pyruvate generator, which causes activation of respiration by extra‐mitochondrial Ca2+, is also present and functional in rat brainstem mitochondria, as it is in other brain regions. This finding is confirmed by experiments with a fully reconstituted malate–aspartate shuttle (MAS).
Grazyna Debska‐Vielhaber +7 more
wiley +1 more source
Query-limited Black-box Attacks to Classifiers
CoRR, 2017 5 Pages, 2017 NIPS workshop on machine learning and computer security (12/08/2017-12/09/2017)
Fnu Suya +3 more
openaire +2 more sources
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