Microservice security: a systematic literature review

D Berardi, S Giallorenzo, J Mauro, A Melis… - PeerJ Computer …, 2022 - peerj.com
Microservices is an emerging paradigm for developing distributed systems. With their
widespread adoption, more and more work investigated the relation between microservices …

A comparative study of attribute selection algorithms on intrusion detection system in UAVs: A case study of UKM-IDS20 dataset

AB Mohammed, L Chaari Fourati… - … Conference on Risks …, 2022 - Springer
Security issues of unmanned aerial vehicles (UAVs) have received great attention. A new
dataset named UKM-IDS20 has been recently developed for intrusion detection in UAVs to …

SecDOAR: A Software Reference Architecture for Security Data Orchestration, Analysis and Reporting

MA Chauhan, MA Babar, F Rabhi - arXiv preprint arXiv:2408.12904, 2024 - arxiv.org
A Software Reference Architecture (SRA) is a useful tool for standardising existing
architectures in a specific domain and facilitating concrete architecture design, development …

An efficient privacy preserving and public auditing data integrity verification protocol for cloud-based online learning environments

LJ Deborah, SM Ganesh… - Secure Data Management …, 2023 - taylorfrancis.com
Ever since the onset of COVID-19, governments and educational organizations have
understood the significance of e-learning education systems for continuing education during …

Effect machine learning techniques for analyzing and filtering spam Mails problems

T Abed Mohammed, S Khamees Jwair - The 7th International …, 2021 - dl.acm.org
The increase in spam and unwanted emails and messages has increased dramatically over
the few past years to overcome this problem the need to develop more reliable and more …

Security enhancements and flaws of emerging communication technologies

D Berardi - 2022 - amsdottorato.unibo.it
The multi-faced evolution of network technologies ranges from big data centers to
specialized network infrastructures and protocols for mission-critical operations. For …

Predicting Big data Drug Interactions and associated side effects by Using Artificial Neural Networks (ANN) over Traditional Graph Convolutional Networks (GCNs)

AA IBRAHIM, TA Mohammed, ON DARA - 2024 - researchsquare.com
Rapid advances in machine learning have enabled the prediction of complex drug-drug
interactions (DDIs) and associated harmful effects. This study aims to develop a neural …

An Improved Convolutional Neural Network-Based Spam Recognition Model

J Liu - 2024 2nd International Conference on Image …, 2024 - atlantis-press.com
Spam is one of the significant threats to cyber security by not only sending unwanted
messages but also by potentially carrying viruses. Conventional spam detection methods …

[引用][C] Predicting Big data Drug Interactions and associated side effects by Using Artificial Neural Networks (ANN) over Traditional Graph Convolutional Networks …

T Abed Mohammed… - International Journal of …, 2024 - University of Bahrain