Skip to search form
Skip to main content
Skip to account menu
Semantic Scholar
Semantic Scholar's Logo
Search 228,254,428 papers from all fields of science
Search
Sign In
Create Free Account
Adversarial machine learning
Adversarial machine learning is a research field that lies at the intersection of machine learning and computer security. It aims to enable the safe…
Expand
Wikipedia
(opens in a new tab)
Create Alert
Alert
Related topics
Related topics
6 relations
Biometrics
International Conference on Machine Learning
Journal of Machine Learning Research
TensorFlow
Broader (2)
Computer security
Machine learning
Papers overview
Semantic Scholar uses AI to extract papers important to this topic.
Review
2020
Review
2020
Adversarial Machine Learning for Text
Daniel Lee
,
Rakesh M. Verma
IWSPA@CODASPY
2020
Corpus ID: 212675630
In this tutorial, we investigate the history, evolution and latest research topics in the area of adversarial machine learning…
Expand
2019
2019
Adversarial Machine Learning with Double Oracle
Kai Wang
International Joint Conference on Artificial…
2019
Corpus ID: 199465990
We aim to improve the general adversarial machine learning solution by introducing the double oracle idea from game theory, which…
Expand
2018
2018
A Compact Reconfigurable Multi-mode Resonator-based Multi-band Band Pass Filter for Intelligent Transportation Systems Applications
Shivesh Triapthi
,
N. Pathak
,
M. Parida
Defence Science Journal
2018
Corpus ID: 53632184
A compact wide band reconfigurable bandpass filter (BPF) which utilises a hemi-circular flower shaped multimode resonator (MMR…
Expand
2018
2018
Adversarial Evasion-Resilient Hardware Malware Detectors
Khaled N. Khasawneh
,
N. Abu-Ghazaleh
,
D. Ponomarev
,
Lei Yu
IEEE/ACM International Conference on Computer…
2018
Corpus ID: 53062033
Machine learning offers tantalizing possibilities in computing and autonomous systems: data driven components and systems are…
Expand
2018
2018
Towards Adversarial Configurations for Software Product Lines
Paul Temple
,
M. Acher
,
B. Biggio
,
J. Jézéquel
,
F. Roli
arXiv.org
2018
Corpus ID: 44137785
Ensuring that all supposedly valid configurations of a software product line (SPL) lead to well-formed and acceptable products is…
Expand
2017
2017
Deep encrypted text categorization
R. Vinayakumar
,
K. Soman
,
P. Poornachandran
International Conference on Advances in Computing…
2017
Corpus ID: 562681
Long short-term memory (LSTM) is a significant approach to capture the long-range temporal context in sequences of arbitrary…
Expand
Review
2017
Review
2017
An Introduction to Adversarial Machine Learning
Atul Kumar
,
S. Mehta
,
Deepak Vijaykeerthy
Journées Bases de Données Avancées
2017
Corpus ID: 5362737
Machine learning based system are increasingly being used for sensitive tasks such as security surveillance, guiding autonomous…
Expand
2017
2017
Attacking Machine Learning models as part of a cyber kill chain
Tam n. Nguyen
arXiv.org
2017
Corpus ID: 4705410
Machine learning is gaining popularity in the network security domain as many more network-enabled devices get connected, as…
Expand
2017
2017
An Adversarial Machine Learning Model Against Android Malware Evasion Attacks
Lingwei Chen
,
Shifu Hou
,
Yanfang Ye
,
Lifei Chen
APWeb/WAIM Workshops
2017
Corpus ID: 206711689
With explosive growth of Android malware and due to its damage to smart phone users, the detection of Android malware is one of…
Expand
2007
2007
Foundations of Adversarial Machine Learning
Daniel Lowd
,
Christopher Meek
,
Pedro M. Domingos
2007
Corpus ID: 18644620
As classifiers are deployed to detect malicious behavior ran ging from spam to terrorism, adversaries modify their behaviors to…
Expand
By clicking accept or continuing to use the site, you agree to the terms outlined in our
Privacy Policy
(opens in a new tab)
,
Terms of Service
(opens in a new tab)
, and
Dataset License
(opens in a new tab)
ACCEPT & CONTINUE