Results 41 to 50 of about 24,885,017 (322)
Applied SciencesIndustrial control systems (ICSs) are critical components automating the processes and operations of electromechanical systems. These systems are vulnerable to cyberattacks and can be the targets of malicious activities.
Hayriye Tanyıldız +2 more
doaj +1 more source
GANG-MAM: GAN based enGine for Modifying Android Malware
SoftwareX, 2022 Malware detectors based on machine learning are vulnerable to adversarial attacks. Generative Adversarial Networks (GAN) are architectures based on Neural Networks that may be used to produce successful adversarial samples.
Renjith G. +4 more
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Adversarial Systems and Adversarial Mindsets: Do We Need Either? [PDF]
Bond Law Review, 2003 extract] The styles of teaching and studying law in civilian and common law jurisdictions are very different. In the context of a desire to make civil procedure in common law jurisdictions less adversarial, the greater emphasis on case based learning in the common law world is striking.
openaire +3 more sources
A System-Driven Taxonomy of Attacks and Defenses in Adversarial Machine Learning
IEEE Transactions on Emerging Topics in Computational Intelligence, 2020 Machine Learning (ML) algorithms, specifically supervised learning, are widely used in modern real-world applications, which utilize Computational Intelligence (CI) as their core technology, such as autonomous vehicles, assistive robots, and biometric ...
Koosha Sadeghi +2 more
semanticscholar +1 more source
Physical Adversarial Attacks Against End-to-End Autoencoder Communication Systems
, 2019 We show that end-to-end learning of communication systems through deep neural network (DNN) autoencoders can be extremely vulnerable to physical adversarial attacks.
Larsson, Erik G., Sadeghi, Meysam
core +1 more source
Defending Against Adversarial Attacks On Medical Imaging Ai System, Classification Or Detection? [PDF]
IEEE International Symposium on Biomedical Imaging, 2020 Medical imaging AI systems such as disease classification and segmentation are increasingly inspired and transformed from computer vision based AI systems. Although an array of defense techniques have been developed and proved to be effective in computer
X. Li, Deng Pan, D. Zhu
semanticscholar +1 more source
Exploring Diverse Feature Extractions for Adversarial Audio Detection
IEEE Access, 2023 Although deep learning models have exhibited excellent performance in various domains, recent studies have discovered that they are highly vulnerable to adversarial attacks.
Yujin Choi +3 more
doaj +1 more source
Adversarial Learning for Neural Dialogue Generation
, 2017 In this paper, drawing intuition from the Turing test, we propose using adversarial training for open-domain dialogue generation: the system is trained to produce sequences that are indistinguishable from human-generated dialogue utterances.
Jean, Sébastien +5 more
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ECGadv: Generating Adversarial Electrocardiogram to Misguide Arrhythmia Classification System
, 2020 Deep neural networks (DNNs)-powered Electrocardiogram (ECG) diagnosis systems recently achieve promising progress to take over tedious examinations by cardiologists.
Chen, Huangxun +4 more
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Using LIP to Gloss Over Faces in Single-Stage Face Detection Networks
, 2018 This work shows that it is possible to fool/attack recent state-of-the-art face detectors which are based on the single-stage networks. Successfully attacking face detectors could be a serious malware vulnerability when deploying a smart surveillance ...
D Chen +5 more
core +1 more source