Results 51 to 60 of about 804,777 (293)
Big Data and Cognitive Computing, 2020 In this work, we propose a novel defense system against adversarial examples leveraging the unique power of Generative Adversarial Networks (GANs) to generate new adversarial examples for model retraining. To do so, we develop an automated pipeline using
Shayan Taheri +3 more
doaj +1 more source
Leveraging linear mapping for model-agnostic adversarial defense
Frontiers in Computer Science, 2023 In the ever-evolving landscape of deep learning, novel designs of neural network architectures have been thought to drive progress by enhancing embedded representations.
Huma Jamil +5 more
doaj +1 more source
GUARD: Graph Universal Adversarial Defense [PDF]
, 2023 Graph convolutional networks (GCNs) have been shown to be vulnerable to small adversarial perturbations, which becomes a severe threat and largely limits their applications in security-critical scenarios.
Wu, Ruofan +7 more
core +1 more source
Remote Sensing, 2023 Deep neural networks (DNNs) have been widely utilized in automatic visual navigation and recognition on modern unmanned aerial vehicles (UAVs), achieving state-of-the-art performances.
Zihao Lu, Hao Sun, Yanjie Xu
doaj +1 more source
Defending Against Adversarial Attacks with Camera Image Pipelines
, 2023 Existing neural networks for computer vision tasks are vulnerable to adversarial attacks: adding imperceptible perturbations to the input images can fool these models into making a false prediction on an image that was correctly predicted without the ...
Zhang, Yuxuan
core
Guided Adversarial Attack for Evaluating and Enhancing Adversarial Defenses
CoRR, 2020 Advances in the development of adversarial attacks have been fundamental to the progress of adversarial defense research. Efficient and effective attacks are crucial for reliable evaluation of defenses, and also for developing robust models. Adversarial attacks are often generated by maximizing standard losses such as the cross-entropy loss or maximum ...
Gaurang Sriramanan +3 more
openaire +3 more sources
Multi-Line Defense Against Windows Adversarial Malware by Using Windows PE Information
IEEE AccessDeep learning has recently been in the spotlight among malware detection researchers in the sense that its training-based robust decision process can lead to efficient and effective malware detection.
Hannah Ho, Jun-Won Ho, Sungjin Ho
doaj +1 more source
Information Transmission Strategies for Self‐Organized Robotic Aggregation
Advanced Robotics Research, EarlyView.In this review, we discuss how information transmission influences the neighbor‐based self‐organized aggregation of swarm robots. We focus specifically on local interactions regarding information transfer and categorize previous studies based on the functions of the information exchanged.
Shu Leng +5 more
wiley +1 more source
An Empirical Review of Adversarial Defenses
CoRR, 2020 19 pages, 8 Figures, Report Reviewed by Vivek ...
openaire +3 more sources
Advanced Science, EarlyView.This review comprehensively summarizes the atomic defects in TMDs for their applications in sustainable energy storage devices, along with the latest progress in ML methodologies for high‐throughput TEM data analysis, offering insights on how ML‐empowered microscopy facilitates bridging structure–property correlation and inspires knowledge for precise ...
Zheng Luo +6 more
wiley +1 more source