A comprehensive survey on poisoning attacks and countermeasures in machine learning
The prosperity of machine learning has been accompanied by increasing attacks on the
training process. Among them, poisoning attacks have become an emerging threat during …
training process. Among them, poisoning attacks have become an emerging threat during …
Machine learning in IoT security: Current solutions and future challenges
The future Internet of Things (IoT) will have a deep economical, commercial and social
impact on our lives. The participating nodes in IoT networks are usually resource …
impact on our lives. The participating nodes in IoT networks are usually resource …
Back to the drawing board: A critical evaluation of poisoning attacks on production federated learning
V Shejwalkar, A Houmansadr… - … IEEE Symposium on …, 2022 - ieeexplore.ieee.org
While recent works have indicated that federated learning (FL) may be vulnerable to
poisoning attacks by compromised clients, their real impact on production FL systems is not …
poisoning attacks by compromised clients, their real impact on production FL systems is not …
Hidden trigger backdoor attacks
With the success of deep learning algorithms in various domains, studying adversarial
attacks to secure deep models in real world applications has become an important research …
attacks to secure deep models in real world applications has become an important research …
Privacy and security issues in deep learning: A survey
Deep Learning (DL) algorithms based on artificial neural networks have achieved
remarkable success and are being extensively applied in a variety of application domains …
remarkable success and are being extensively applied in a variety of application domains …
Dataset security for machine learning: Data poisoning, backdoor attacks, and defenses
As machine learning systems grow in scale, so do their training data requirements, forcing
practitioners to automate and outsource the curation of training data in order to achieve state …
practitioners to automate and outsource the curation of training data in order to achieve state …
Witches' brew: Industrial scale data poisoning via gradient matching
Data Poisoning attacks modify training data to maliciously control a model trained on such
data. In this work, we focus on targeted poisoning attacks which cause a reclassification of …
data. In this work, we focus on targeted poisoning attacks which cause a reclassification of …
Cyber security intrusion detection for agriculture 4.0: Machine learning-based solutions, datasets, and future directions
In this paper, we review and analyze intrusion detection systems for Agriculture 4.0 cyber
security. Specifically, we present cyber security threats and evaluation metrics used in the …
security. Specifically, we present cyber security threats and evaluation metrics used in the …
De-pois: An attack-agnostic defense against data poisoning attacks
Machine learning techniques have been widely applied to various applications. However,
they are potentially vulnerable to data poisoning attacks, where sophisticated attackers can …
they are potentially vulnerable to data poisoning attacks, where sophisticated attackers can …
Deep reinforcement learning for partially observable data poisoning attack in crowdsensing systems
M Li, Y Sun, H Lu, S Maharjan… - IEEE Internet of Things …, 2019 - ieeexplore.ieee.org
Crowdsensing systems collect various types of data from sensors embedded on mobile
devices owned by individuals. These individuals are commonly referred to as workers that …
devices owned by individuals. These individuals are commonly referred to as workers that …