Muna Al-Hawawreh

Orcid: 0000-0003-4690-2256

Affiliations:
  • Deakin University, Victoria, Australia


According to our database1, Muna Al-Hawawreh authored at least 27 papers between 2016 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
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Online presence:

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Bibliography

2024
Securing the Industrial Internet of Things against ransomware attacks: A comprehensive analysis of the emerging threat landscape and detection mechanisms.
J. Netw. Comput. Appl., March, 2024

Explainable deep learning for attack intelligence and combating cyber-physical attacks.
Ad Hoc Networks, February, 2024

A threat intelligence framework for protecting smart satellite-based healthcare networks.
Neural Comput. Appl., January, 2024

Hierarchical Classification for Intrusion Detection System: Effective Design and Empirical Analysis.
CoRR, 2024

A Dual-Tier Adaptive One-Class Classification IDS for Emerging Cyberthreats.
CoRR, 2024

usfAD Based Effective Unknown Attack Detection Focused IDS Framework.
CoRR, 2024

2023
Chatgpt for cybersecurity: practical applications, challenges, and future directions.
Clust. Comput., December, 2023

A privacy-aware framework for detecting cyber attacks on internet of medical things systems using data fusion and quantum deep learning.
Inf. Fusion, November, 2023

An explainable ensemble of multi-view deep learning model for fake review detection.
J. King Saud Univ. Comput. Inf. Sci., September, 2023

Edge Learning for 6G-Enabled Internet of Things: A Comprehensive Survey of Vulnerabilities, Datasets, and Defenses.
IEEE Commun. Surv. Tutorials, 2023

Generative AI for Cyber Threat-Hunting in 6G-enabled IoT Networks.
Proceedings of the 23rd IEEE/ACM International Symposium on Cluster, 2023

WiP: Towards Zero Trust Authentication in Critical Industrial Infrastructures with PRISM.
Proceedings of the Applied Cryptography and Network Security Workshops, 2023

2022
X-IIoTID: A Connectivity- and Device-agnostic Intrusion Dataset for Industrial Internet of Things.
Dataset, May, 2022

X-IIoTID: A Connectivity-Agnostic and Device-Agnostic Intrusion Data Set for Industrial Internet of Things.
IEEE Internet Things J., 2022

Ultra Light-weight Encryption for Securing D2D Communication of ESP8266 IoT devices in Wireless Mesh Networks.
Proceedings of the International Symposium on Networks, Computers and Communications, 2022

2021
Deep Learning-Enabled Threat Intelligence Scheme in the Internet of Things Networks.
IEEE Trans. Netw. Sci. Eng., 2021

Developing a Security Testbed for Industrial Internet of Things.
IEEE Internet Things J., 2021

Fake or Genuine? Contextualised Text Representation for Fake Review Detection.
CoRR, 2021

Asynchronous Peer-to-Peer Federated Capability-Based Targeted Ransomware Detection Model for Industrial IoT.
IEEE Access, 2021

2019
An Efficient Approach for Representing and Sending Data in Wireless Sensor Networks.
J. Commun., 2019

Targeted Ransomware: A New Cyber Threat to Edge System of Brownfield Industrial Internet of Things.
IEEE Internet Things J., 2019

Leveraging Deep Learning Models for Ransomware Detection in the Industrial Internet of Things Environment.
Proceedings of the 2019 Military Communications and Information Systems Conference, 2019

An Efficient Intrusion Detection Model for Edge System in Brownfield Industrial Internet of Things.
Proceedings of the 3rd International Conference on Big Data and Internet of Things, 2019

Industrial Internet of Things Based Ransomware Detection using Stacked Variational Neural Network.
Proceedings of the 3rd International Conference on Big Data and Internet of Things, 2019

2018
Identification of malicious activities in industrial internet of things based on deep learning models.
J. Inf. Secur. Appl., 2018

An anomaly-based approach for DDoS attack detection in cloud environment.
Int. J. Comput. Appl. Technol., 2018

2016
Present Status and Challenges in Cloud Monitoring Framework: A Survey.
Proceedings of the 2016 European Intelligence and Security Informatics Conference, 2016


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