Results 281 to 290 of about 22,784,147 (354)

Objectivity in an adversarial system

Medico-Legal Journal, 2020
The Rt Hon Lady Justice Heather Hallet
openaire   +3 more sources

Jailbreaking GPT-4V via Self-Adversarial Attacks with System Prompts

arXiv.org, 2023
Existing work on jailbreak Multimodal Large Language Models (MLLMs) has focused primarily on adversarial examples in model inputs, with less attention to vulnerabilities, especially in model API. To fill the research gap, we carry out the following work:
Yuanwei Wu, Xiang Li, Yixin Liu, Pan Zhou, Lichao Sun   +4 more
semanticscholar   +1 more source

Adversarial Attack Mitigation Strategy for Machine Learning-Based Network Attack Detection Model in Power System

IEEE Transactions on Smart Grid, 2023
The network attack detection model based on machine learning (ML) has received extensive attention and research in PMU measurement data protection of power systems. However, well-trained ML-based detection models are vulnerable to adversarial attacks. By
Rong Huang, Yuancheng Li
semanticscholar   +1 more source

Robustness Verification for Machine-Learning-Based Power System Dynamic Security Assessment Models Under Adversarial Examples

IEEE Transactions on Control of Network Systems, 2022
Based on machine learning (ML) technique, the data-driven power system dynamic security assessment (DSA) has received significant research interest. Yet, the well-trained ML-based models with high training and testing accuracy may be vulnerable to the ...
Chao Ren, Yan Xu
semanticscholar   +1 more source

Generative-Adversarial Class-Imbalance Learning for Classifying Cyber-Attacks and Faults - A Cyber-Physical Power System

IEEE Transactions on Dependable and Secure Computing, 2022
There has been an increasing interest in the use of data-driven techniques for classifying cyber-attacks and physical faults in cyber-physical systems.
Maryam Farajzadeh-Zanjani, Ehsan Hallaji, R. Razavi-Far, M. Saif   +3 more
semanticscholar   +1 more source

Vulnerability Analysis, Robustness Verification, and Mitigation Strategy for Machine Learning-Based Power System Stability Assessment Model Under Adversarial Examples

IEEE Transactions on Smart Grid, 2022
Based on machine learning (ML) technique, the data-driven power system stability assessment has received significant research interests in recent years.
Chao Ren, Xiaoning Du, Yan Xu, Qun Song, Yang Liu, Rui Tan   +5 more
semanticscholar   +1 more source

MANDA: On Adversarial Example Detection for Network Intrusion Detection System

IEEE Conference on Computer Communications, 2021
With the rapid advancement in machine learning (ML), ML-based Intrusion Detection Systems (IDSs) are widely deployed to protect networks from various attacks.
Ning Wang, Yimin Chen, Yang Hu, Wenjing Lou, Yiwei Thomas Hou   +4 more
semanticscholar   +1 more source

AdvDoor: adversarial backdoor attack of deep learning system

International Symposium on Software Testing and Analysis, 2021
Deep Learning (DL) system has been widely used in many critical applications, such as autonomous vehicles and unmanned aerial vehicles. However, their security is threatened by backdoor attack, which is achieved by adding artificial patterns on specific ...
Quan Zhang, Yifeng Ding, Yongqiang Tian, Jianmin Guo, Min Yuan, Yu Jiang   +5 more
semanticscholar   +1 more source

The Adversary System: Cui Bono?

Annals of Internal Medicine, 1982
Excerpt The article by Richman in this issue(1) provides a dispassionate and objective review of compensation for industrial disease.
W. KEITH, C. MORGAN
openaire   +2 more sources

Adversarial-Example Attacks Toward Android Malware Detection System

IEEE Systems Journal, 2020
Recently, it was shown that the generative adversarial network (GAN) based adversarial-example attacks could thoroughly defeat the existing Android malware detection systems.
Heng Li, Shiyao Zhou, Wei Yuan, Jiahuan Li, H. Leung   +4 more
semanticscholar   +1 more source