A comprehensive survey on poisoning attacks and countermeasures in machine learning

Z Tian, L Cui, J Liang, S Yu - ACM Computing Surveys, 2022 - dl.acm.org
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 …

Anonymization techniques for privacy preserving data publishing: A comprehensive survey

A Majeed, S Lee - IEEE access, 2020 - ieeexplore.ieee.org
Anonymization is a practical solution for preserving user's privacy in data publishing. Data
owners such as hospitals, banks, social network (SN) service providers, and insurance …

Privacy-preserving blockchain-based federated learning for IoT devices

Y Zhao, J Zhao, L Jiang, R Tan, D Niyato… - IEEE Internet of …, 2020 - ieeexplore.ieee.org
Home appliance manufacturers strive to obtain feedback from users to improve their
products and services to build a smart home system. To help manufacturers develop a smart …

X-IIoTID: A connectivity-agnostic and device-agnostic intrusion data set for industrial Internet of Things

M Al-Hawawreh, E Sitnikova… - IEEE Internet of Things …, 2021 - ieeexplore.ieee.org
Industrial Internet of Things (IIoT) is a high-value cyber target due to the nature of the
devices and connectivity protocols they deploy. They are easy to compromise and, as they …

Multi-access edge computing architecture, data security and privacy: A review

B Ali, MA Gregory, S Li - IEEE Access, 2021 - ieeexplore.ieee.org
Multi-Access Edge Computing (MEC) is an extension of cloud computing that aims to
provide computation, storage, and networking capabilities at the edge of the network in …

[HTML][HTML] Evolutionary privacy-preserving learning strategies for edge-based IoT data sharing schemes

Y Shen, S Shen, Q Li, H Zhou, Z Wu, Y Qu - Digital Communications and …, 2023 - Elsevier
The fast proliferation of edge devices for the Internet of Things (IoT) has led to massive
volumes of data explosion. The generated data is collected and shared using edge-based …

Distributed incentives for intelligent offloading and resource allocation in digital twin driven smart industry

K Peng, H Huang, M Bilal, X Xu - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Mobile edge computing is one of the key enabling technologies of smart industry solutions,
providing agile and ubiquitous services for mobile devices (MDs) through offloading latency …

The security and privacy of mobile edge computing: An artificial intelligence perspective

C Wang, Z Yuan, P Zhou, Z Xu, R Li… - IEEE Internet of Things …, 2023 - ieeexplore.ieee.org
Mobile-edge computing (MEC) is a new computing paradigm that enables cloud computing
and information technology (IT) services to be delivered at the network's edge. By shifting …

Link prediction adversarial attack via iterative gradient attack

J Chen, X Lin, Z Shi, Y Liu - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
Increasing deep neural networks are applied in solving graph evolved tasks, such as node
classification and link prediction. However, the vulnerability of deep models can be revealed …

Privacy preservation in online social networks using multiple-graph-properties-based clustering to ensure k-anonymity, l-diversity, and t-closeness

R Gangarde, A Sharma, A Pawar, R Joshi, S Gonge - Electronics, 2021 - mdpi.com
As per recent progress, online social network (OSN) users have grown tremendously
worldwide, especially in the wake of the COVID-19 pandemic. Today, OSNs have become a …