Surveying trust-based collaborative intrusion detection: state-of-the-art, challenges and future directions

W Li, W Meng, LF Kwok - IEEE Communications Surveys & …, 2021 - ieeexplore.ieee.org
Owing to the swift growth in cyber attacks, intrusion detection systems (IDSs) have become a
necessity to help safeguard personal and organizational assets. However, with the …

Enhancing the security of blockchain-based software defined networking through trust-based traffic fusion and filtration

W Meng, W Li, J Zhou - Information Fusion, 2021 - Elsevier
With the rapid development of Internet-of-Things (IoT), more smart devices can be
connected to the Internet, resulting in a dramatic increase of data transmission and …

Ensemble classification for intrusion detection via feature extraction based on deep Learning

M Yousefnezhad, J Hamidzadeh, M Aliannejadi - Soft Computing, 2021 - Springer
An intrusion detection system is a security system that aims to detect sabotage and
intrusions on networks to inform experts of the attack and abuse of the network. Different …

Machine learning empowered trust evaluation method for IoT devices

W Ma, X Wang, M Hu, Q Zhou - IEEE access, 2021 - ieeexplore.ieee.org
With the rapid development of the Internet of Things (IoT), malicious or affected IoT devices
have imposed enormous threats on the IoT environment. To address this issue, trust has …

A detection framework against CPMA attack based on trust evaluation and machine learning in IoT network

L Liu, X Xu, Y Liu, Z Ma, J Peng - IEEE Internet of Things …, 2021 - ieeexplore.ieee.org
Internet of Things (IoT) network is vulnerable to various cyberattacks, especially insider
attacks. Most existing studies mainly detect nontargeted insider attackers, who manipulate …

[HTML][HTML] Challenge-based collaborative intrusion detection in software-defined networking: An evaluation

W Li, Y Wang, Z Jin, K Yu, J Li, Y Xiang - Digital Communications and …, 2021 - Elsevier
Abstract Software-Defined Networking (SDN) is an emerging architecture that enables a
computer network to be intelligently and centrally controlled via software applications. It can …

Insider threat detection using deep autoencoder and variational autoencoder neural networks

E Pantelidis, G Bendiab, S Shiaeles… - … Conference on Cyber …, 2021 - ieeexplore.ieee.org
Internal attacks are one of the biggest cybersecurity issues to companies and businesses.
Despite the implemented perimeter security systems, the risk of adversely affecting the …

Collaborative intrusion detection in the era of IoT: Recent advances and challenges

W Li, W Meng - Security and Privacy in the Internet of Things …, 2021 - Wiley Online Library
Summary Internet of Things (IoT) is currently transferring the conventional networks by
allowing various devices to connect with each other, and the continued growth of IoT …

Using homomorphic encryption for privacy-preserving clustering of intrusion detection alerts

G Spathoulas, G Theodoridis, GP Damiris - International Journal of …, 2021 - Springer
Cyber-security attacks are becoming more frequent and more severe day by day. To detect
the execution of such attacks, organizations install intrusion detection systems. It would be …

A collaborative intrusion detection system using deep blockchain framework for securing cloud networks

O Alkadi, N Moustafa, B Turnbull - Intelligent Systems and Applications …, 2021 - Springer
Security solutions, especially intrusion detection and blockchain, have been individually
employed in the cloud for detecting cyber threats and preserving private data. Both solutions …