Results 61 to 70 of about 94,262 (290)

Attacking Adversarial Attacks as A Defense

, 2021
It is well known that adversarial attacks can fool deep neural networks with imperceptible perturbations. Although adversarial training significantly improves model robustness, failure cases of defense still broadly exist. In this work, we find that the adversarial attacks can also be vulnerable to small perturbations.
Wu, Boxi, Pan, Heng, Shen, Li, Gu, Jindong, Zhao, Shuai, Li, Zhifeng, Cai, Deng, He, Xiaofei, Liu, Wei   +8 more
openaire   +2 more sources

Urea‐Formaldehyde Resin Confined Silicon Nanodots Composites: High‐Performance and Ultralong Persistent Luminescence for Dynamic AI Information Encryption

Advanced Science, EarlyView.
Schematic illustration of SiNDs composite materials synthesis and its internal photophysical process mechanism. And an AI‐assisted dynamic information encryption process. ABSTRACT Persistent luminescence materials typically encounter an intrinsic trade‐off between high phosphorescence quantum yield (PhQY) and ultralong phosphorescence lifetime.
Yulu Liu, Lei Cao, Lele Gao, Panyong Wang, Qiannan You, Xinpei Pang, Li Li, Mingzheng Jia, Wen‐Fei Dong, Minghui Zan   +9 more
wiley   +1 more source

Review of Artificial Intelligence Adversarial Attack and Defense Technologies

Applied Sciences, 2019
In recent years, artificial intelligence technologies have been widely used in computer vision, natural language processing, automatic driving, and other fields.
Shilin Qiu, Qihe Liu, Shijie Zhou, Chunjiang Wu   +3 more
doaj   +1 more source

Functional Adversarial Attacks

, 2019
Accepted to NeurIPS ...
Laidlaw, Cassidy, Feizi, Soheil
openaire   +2 more sources

Experimental validation of the RESPONSE framework against cyberattacks on cyber‐physical process systems

AIChE Journal, EarlyView.
Abstract This work experimentally validates the RESPONSE (Resilient Process cONtrol SystEm) framework as a solution for maintaining safe, continuous operation of cyber‐physical process systems under cyberattacks. RESPONSE implements a dual‐loop architecture that runs a networked online controller in parallel with a hard‐isolated offline controller ...
Luyang Liu, Pu Du, Zaman Sajid, Benjamin Wilhite, Costas Kravaris, Faisal Khan   +5 more
wiley   +1 more source

AB-VIP: Attack Method Using Brightness Information for Visibility Improvement of Adversarial Perturbations on the NMS Algorithm

IEEE Access
As with classification models, object detection models are vulnerable to adversarial attacks. In particular, adversarial attacks on key components of object detection models such as Region Proposal Network (RPN) and Non-Maximum Suppression (NMS ...
Gwang-Nam Kim, Han-Ju Lee, Han-Jin Lee, Hyeon-Jin Jung, Seok-Hwan Choi   +4 more
doaj   +1 more source

A Two-Stage Generative Adversarial Networks With Semantic Content Constraints for Adversarial Example Generation

IEEE Access, 2020
Deep neural networks (DNNs) have achieved great success in various applications due to their strong expressive power. However, recent studies have shown that DNNs are vulnerable to adversarial examples, and these manipulated instances can mislead DNN ...
Jianyi Liu, Yu Tian, Ru Zhang, Youqiang Sun, Chan Wang   +4 more
doaj   +1 more source

A Distributed Biased Boundary Attack Method in Black-Box Attack

Applied Sciences, 2021
The adversarial samples threaten the effectiveness of machine learning (ML) models and algorithms in many applications. In particular, black-box attack methods are quite close to actual scenarios.
Fengtao Xiang, Jiahui Xu, Wanpeng Zhang, Weidong Wang   +3 more
doaj   +1 more source

SURVEY OF ADVERSARIAL ATTACKS AND DEFENSE AGAINST ADVERSARIAL ATTACKS

Darpan International Research Analysis
In recent years, the fields of Artificial Intelligence (AI) and Deep learning (DL) techniques along with Neural Networks (NNs) have shown great progress and scope for future research. Along with all the developments comes the threats and security vulnerabilities to Neural Networks and AI models. A few fabricated inputs/samples can lead to deviations in
Akshat Jain, Sanskar Agarwal, Armaan Pareek, Vanshika Singh   +3 more
openaire   +1 more source

Artificial Intelligence for Bone: Theory, Methods, and Applications

Advanced Intelligent Discovery, EarlyView.
Advances in artificial intelligence (AI) offer the potential to improve bone research. The current review explores the contributions of AI to pathological study, biomarker discovery, drug design, and clinical diagnosis and prognosis of bone diseases. We envision that AI‐driven methodologies will enable identifying novel targets for drugs discovery. The
Dongfeng Yuan, Haicang Zhang, Liping Tong, Di Chen   +3 more
wiley   +1 more source