Results 21 to 30 of about 1,143,792 (206)
Adversarial Machine Learning Attacks and Defense Methods in the Cyber Security Domain
ACM Computing Surveys, 2021 In recent years, machine learning algorithms, and more specifically deep learning algorithms, have been widely used in many fields, including cyber security.
Ishai Rosenberg +3 more
semanticscholar +1 more source
Adversarial Machine Learning Attacks Against Video Anomaly Detection Systems [PDF]
2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), 2022 Anomaly detection in videos is an important computer vision problem with various applications including auto-mated video surveillance. Although adversarial attacks on image understanding models have been heavily investigated, there is not much work on ...
Furkan Mumcu, Keval Doshi, Yasin Yılmaz
semanticscholar +1 more source
Adversarial Attacks and Defense Technologies on Autonomous Vehicles: A Review
Applied Computer Systems, 2021 In recent years, various domains have been influenced by the rapid growth of machine learning. Autonomous driving is an area that has tremendously developed in parallel with the advancement of machine learning.
Mahima K. T. Y. +2 more
doaj +1 more source
Adversarial Machine Learning in Image Classification: A Survey Toward the Defender’s Perspective [PDF]
ACM Computing Surveys, 2020 Deep Learning algorithms have achieved state-of-the-art performance for Image Classification. For this reason, they have been used even in security-critical applications, such as biometric recognition systems and self-driving cars.
G. R. Machado +2 more
semanticscholar +1 more source
Adversarial Machine Learning for 5G Communications Security [PDF]
Game Theory and Machine Learning for Cyber Security, 2021 Machine learning provides automated means to capture complex dynamics of wireless spectrum and support better understanding of spectrum resources and their efficient utilization.
Y. Sagduyu, T. Erpek, Yi Shi
semanticscholar +1 more source
EIFDAA: Evaluation of an IDS with function-discarding adversarial attacks in the IIoT
Heliyon, 2023 The complexity of the Industrial Internet of Things (IIoT) presents higher requirements for intrusion detection systems (IDSs). An adversarial attack is a threat to the security of machine learning-based IDSs.
Shiming Li +4 more
doaj +1 more source
Security and Artificial Intelligence, 2019 In this paper (expanded from an invited talk at AISEC 2010), we discuss an emerging field of study: adversarial machine learning---the study of effective machine learning techniques against an adversarial opponent.
Ling Huang +4 more
semanticscholar +1 more source
Adversarial Machine Learning in Wireless Communications Using RF Data: A Review [PDF]
IEEE Communications Surveys and Tutorials, 2020 Machine learning (ML) provides effective means to learn from spectrum data and solve complex tasks involved in wireless communications. Supported by recent advances in computational resources and algorithmic designs, deep learning (DL) has found success ...
D. Adesina +3 more
semanticscholar +1 more source
Impact of adversarial examples on deep learning models for biomedical image segmentation [PDF]
, 2019 Deep learning models, which are increasingly being used in the field of medical image analysis, come with a major security risk, namely, their vulnerability to adversarial examples.
C Pena-Betancor +3 more
core +4 more sources
Adversarial Machine Learning Security Problems for 6G: mmWave Beam Prediction Use-Case [PDF]
International Black Sea Conference on Communications and Networking, 2021 6G is the next generation for the communication systems. In recent years, machine learning algorithms have been applied widely in various fields such as health, transportation, and the autonomous car. The predictive algorithms will be used in 6G problems.
Evren Çatak +2 more
semanticscholar +1 more source