[HTML][HTML] The cybersecurity mesh: A comprehensive survey of involved artificial intelligence methods, cryptographic protocols and challenges for future research

B Ramos-Cruz, J Andreu-Perez, L Martínez - Neurocomputing, 2024 - Elsevier
In today's world, it is vital to have strong cybersecurity measures in place. To combat the
ever-evolving threats, adopting advanced models like cybersecurity mesh is necessary to …

A Systematic Literature Review on Cyber Attack Detection in Software-Define Networking (SDN)

DS Ahmed, AA Abdulhameed… - Mesopotamian …, 2024 - journals.mesopotamian.press
The increasing complexity and sophistication of cyberattacks pose significant challenges to
traditional network security tools. Software-defined networking (SDN) has emerged as a …

Augmenting cybersecurity through attention based stacked autoencoder with optimization algorithm for detection and mitigation of attacks on IoT assisted networks

KS Prasad, EL Lydia, MV Rajesh, K Radhika… - Scientific Reports, 2024 - nature.com
Abstract The Internet of Things (IoT) network is a fast-growing technology, which is efficiently
used in various applications. In an IoT network, the massive amount of connecting nodes is …

Collaborative Federated Learning-Based Model for Alert Correlation and Attack Scenario Recognition

HK Alkhpor, FM Alserhani - Electronics, 2023 - mdpi.com
Planned and targeted attacks, such as the advanced persistent threat (APT), are highly
sophisticated forms of attack. They involve numerous steps and are intended to remain …

On the Fence: Anomaly Detection in IoT Networks

P Russell, MA Elsayed, B Nandy… - NOMS 2023-2023 …, 2023 - ieeexplore.ieee.org
The Internet of Things (IoT) is increasingly impacting every aspect of life, with deployment in
various societal applications. This paper explores anomaly detection via novelty and outlier …

A Federated Learning Approach for Multi-stage Threat Analysis in Advanced Persistent Threat Campaigns

F Nelles, A Yazdinejad, A Dehghantanha… - arXiv preprint arXiv …, 2024 - arxiv.org
Multi-stage threats like advanced persistent threats (APT) pose severe risks by stealing data
and destroying infrastructure, with detection being challenging. APTs use novel attack …

P3GNN: A Privacy-Preserving Provenance Graph-Based Model for APT Detection in Software Defined Networking

H Nazari, A Yazdinejad, A Dehghantanha… - arXiv preprint arXiv …, 2024 - arxiv.org
Software Defined Networking (SDN) has brought significant advancements in network
management and programmability. However, this evolution has also heightened …

Rapid APT detection in resource-constrained IoT devices using global vision federated learning (GV-FL)

H Zhu, H Wang, CT Lam, L Hu, BK Ng… - … Conference on Neural …, 2023 - Springer
Security and privacy are critical concerns in cyberspace due to the inherent vulnerability of
Internet of Things (IoT) systems. In particular, Advanced Persistent Threat (APT) has become …

XFedHunter: An Explainable Federated Learning Framework for Advanced Persistent Threat Detection in SDN

HT Thi, NDH Son, PT Duy, NH Khoa… - arXiv preprint arXiv …, 2023 - arxiv.org
Advanced Persistent Threat (APT) attacks are highly sophisticated and employ a multitude of
advanced methods and techniques to target organizations and steal sensitive and …

Anomaly Detection for IoT Networks: Empirical Study

MA Elsayed, P Russell, B Nandy… - 2023 IEEE Canadian …, 2023 - ieeexplore.ieee.org
The Internet of Things (IoT) actively transforms physical objects, including portable,
wearable, and implantable sensors, into an information ecosystem that enriches the …