Results 51 to 60 of about 33,606 (255)
Adversarial Machine Learning Applied to Intrusion and Malware Scenarios: A Systematic Review
IEEE Access, 2020 Cyber-security is the practice of protecting computing systems and networks from digital attacks, which are a rising concern in the Information Age. With the growing pace at which new attacks are developed, conventional signature based attack detection ...
Nuno Martins +3 more
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
Journal of Information and Technology, 2023 Serangan adversarial pada citra digital merupakan ancaman serius bagi penggunaan teknologi machine learning dalam berbagai aplikasi kehidupan sehari-hari. Teknik Fast Gradient Sign Method (FGSM) telah terbukti efektif dalam melakukan serangan pada model
Putu Widiarsa Kurniawan S +2 more
doaj +1 more source
An Adversarial Learning Framework for Privacy Preserving Communications [PDF]
, 2022 We develop a machine learning-based approach that allows to achieve privacy in communications by exploiting an advantage at the physical layer. Our goal is to transmit useful data to the intended receiver while preventing sensitive data from leaking to ...
Marchioro, Thomas
core
Continual Learning for Multimodal Data Fusion of a Soft Gripper
Advanced Robotics Research, EarlyView.Models trained on a single data modality often struggle to generalize when exposed to a different modality. This work introduces a continual learning algorithm capable of incrementally learning different data modalities by leveraging both class‐incremental and domain‐incremental learning scenarios in an artificial environment where labeled data is ...
Nilay Kushawaha, Egidio Falotico
wiley +1 more source
Advanced Robotics Research, EarlyView.This work presents a state‐adaptive Koopman linear quadratic regulator framework for real‐time manipulation of a deformable swab tool in robotic environmental sampling. By combining Koopman linearization, tactile sensing, and centroid‐based force regulation, the system maintains stable contact forces and high coverage across flat and inclined surfaces.
Siavash Mahmoudi +2 more
wiley +1 more source
Enhancing adversarial robustness of quantum neural networks by adding noise layers
New Journal of Physics, 2023 The rapid advancements in machine learning and quantum computing have given rise to a new research frontier: quantum machine learning. Quantum models designed for tackling classification problems possess the potential to deliver speed enhancements and ...
Chenyi Huang, Shibin Zhang
doaj +1 more source
Adversarial Attack’s Impact on Machine Learning Model in Cyber-Physical Systems
, 2020 Deficiency of correctly implemented and robust defence leaves Internet of Things devices vulnerable to cyber threats, such as adversarial attacks. A perpetrator can utilize adversarial examples when attacking Machine Learning models used in a cloud data ...
Vähäkainu, Petri +2 more
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Particle-based adversarial local distribution regularization [PDF]
, 2022 Adversarial training defense (ATD) and virtual adversarial training (VAT) are the two most effective methods to improve model robustness against attacks and model generalization.
Nguyen, Thanh Duc Van +4 more
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Advanced Robotics Research, EarlyView.This review maps the methods to monitor robots’ health by fusing vibration, sound, control signals, vision, force, and oil information with artificial intelligence. It identifies deep learning, transfer learning, digital twins, and physics‐informed models as key methodological pathways enabling earlier diagnosis, safer human–robot collaboration, and ...
Yuting Qiao +6 more
wiley +1 more source