Results 31 to 40 of about 94,861 (274)
Multi-Targeted Adversarial Example in Evasion Attack on Deep Neural Network
IEEE Access, 2018 Deep neural networks (DNNs) are widely used for image recognition, speech recognition, pattern analysis, and intrusion detection. Recently, the adversarial example attack, in which the input data are only slightly modified, although not an issue for ...
Hyun Kwon +4 more
doaj +1 more source
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
doaj +1 more source
Gotta Catch 'Em All: Using Honeypots to Catch Adversarial Attacks on Neural Networks
, 2020 Deep neural networks (DNN) are known to be vulnerable to adversarial attacks. Numerous efforts either try to patch weaknesses in trained models, or try to make it difficult or costly to compute adversarial examples that exploit them.
Li, Bo +5 more
core +1 more source
Adversarial Examples Are Not Easily Detected
Proceedings of the 10th ACM Workshop on Artificial Intelligence and Security, 2017 Neural networks are known to be vulnerable to adversarial examples: inputs that are close to natural inputs but classified incorrectly. In order to better understand the space of adversarial examples, we survey ten recent proposals that are designed for detection and compare their efficacy.
Carlini, Nicholas, Wagner, David
openaire +2 more sources
Detecting Overfitting via Adversarial Examples
, 2019 17 ...
Werpachowski, Roman +2 more
openaire +2 more sources
Defense Architecture for Adversarial Examples of Ensemble Model Traffic Based on FeatureDifference Selection [PDF]
Jisuanji kexueCurrently,anomaly traffic detection models that leverage deep learning technologies are increasingly vulnerable to adversarial example attacks.Adversarial training has emerged as a potent defense mechanism against these adversarial attacks.By ...
HE Yuankang, MA Hailong, HU Tao, JIANG Yiming
doaj +1 more source
Scale-Adaptive Adversarial Patch Attack for Remote Sensing Image Aircraft Detection
Remote Sensing, 2021 With the adversarial attack of convolutional neural networks (CNNs), we are able to generate adversarial patches to make an aircraft undetectable by object detectors instead of covering the aircraft with large camouflage nets. However, aircraft in remote
Mingming Lu, Qi Li, Li Chen, Haifeng Li
doaj +1 more source
Feature-Guided Black-Box Safety Testing of Deep Neural Networks
, 2018 Despite the improved accuracy of deep neural networks, the discovery of adversarial examples has raised serious safety concerns. Most existing approaches for crafting adversarial examples necessitate some knowledge (architecture, parameters, etc.) of the
B Biggio +8 more
core +1 more source
Adversarial Attacks to Manipulate Target Localization of Object Detector
IEEE AccessAdversarial attack has gradually become an important branch in the field of artificial intelligence security, where the potential threat brought by adversarial example attack is more not to be ignored.
Kai Xu +7 more
doaj +1 more source
Network error correction with unequal link capacities
, 2010 This paper studies the capacity of single-source single-sink noiseless networks under adversarial or arbitrary errors on no more than z edges. Unlike prior papers, which assume equal capacities on all links, arbitrary link capacities are considered ...
Avestimehr, Amir Salman +3 more
core +2 more sources