Metaheuristics for bilevel optimization: A comprehensive review

JF Camacho-Vallejo, C Corpus, JG Villegas - Computers & Operations …, 2023 - Elsevier
A bilevel programming model represents the relationship in a specific decision process that
involves decisions within a hierarchical structure of two levels. The upper-level problem is …

A review of federated meta-learning and its application in cyberspace security

F Liu, M Li, X Liu, T Xue, J Ren, C Zhang - Electronics, 2023 - mdpi.com
In recent years, significant progress has been made in the application of federated learning
(FL) in various aspects of cyberspace security, such as intrusion detection, privacy …

SimFBO: Towards simple, flexible and communication-efficient federated bilevel learning

Y Yang, P Xiao, K Ji - Advances in Neural Information …, 2024 - proceedings.neurips.cc
Federated bilevel optimization (FBO) has shown great potential recently in machine learning
and edge computing due to the emerging nested optimization structure in meta-learning …

Extremely boosted neural network for more accurate multi-stage Cyber attack prediction in cloud computing environment

S Dalal, P Manoharan, UK Lilhore, B Seth… - Journal of Cloud …, 2023 - Springer
There is an increase in cyberattacks directed at the network behind firewalls. An all-inclusive
approach is proposed in this assessment to deal with the problem of identifying new …

HIDM: Hybrid Intrusion Detection Model for Industry 4.0 Networks Using an Optimized CNN-LSTM with Transfer Learning

UK Lilhore, P Manoharan, S Simaiya, R Alroobaea… - Sensors, 2023 - mdpi.com
Industrial automation systems are undergoing a revolutionary change with the use of
Internet-connected operating equipment and the adoption of cutting-edge advanced …

[PDF][PDF] ASMF: Ambient social media forensics chain of custody with an intelligent digital investigation process using federated learning

AA Khan, X Zhang, F Hajjej, J Yang, CS Ku, LY Por - Heliyon, 2024 - cell.com
Ambient Intelligence is a concept that relates to a new paradigm of pervasive computing and
has the objective of automating responses from the system to humans without any human …

Exploring adversarial graph autoencoders to manipulate federated learning in the internet of things

K Li, X Yuan, J Zheng, W Ni… - … and Mobile Computing …, 2023 - ieeexplore.ieee.org
Mobile edge computing (MEC) enables the Internet of Things (IoT) with seamless integration
of multiple application services. Federated learning is increasingly considered to improve …

Edge artificial intelligence for big data: a systematic review

A Hemmati, P Raoufi, AM Rahmani - Neural Computing and Applications, 2024 - Springer
Edge computing, artificial intelligence (AI), and machine learning (ML) concepts have
become increasingly prevalent in Internet of Things (IoT) applications. As the number of IoT …

[PDF][PDF] Residential Energy Consumption Forecasting Based on Federated Reinforcement Learning with Data Privacy Protection.

Y Lu, L Cui, Y Wang, J Sun, L Liu - CMES-Computer Modeling in …, 2023 - cdn.techscience.cn
Most studies have conducted experiments on predicting energy consumption by integrating
data for model training. However, the process of centralizing data can cause problems of …

The Landscape of Modern Machine Learning: A Review of Machine, Distributed and Federated Learning

O Subasi, O Bel, J Manzano, K Barker - arXiv preprint arXiv:2312.03120, 2023 - arxiv.org
With the advance of the powerful heterogeneous, parallel and distributed computing
systems and ever increasing immense amount of data, machine learning has become an …