Naeem Firdous Syed

Orcid: 0000-0003-2450-4337

Affiliations:
  • Deakin University, Centre for Cyber Security Research and Innovation, Geelong, Australia


According to our database1, Naeem Firdous Syed authored at least 22 papers between 2011 and 2024.

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

Timeline

Legend:

Book 
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PhD thesis 
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Bibliography

2024
The Role of Rule Mining in Generating Synthetic Cyber-Physical System Attack Samples.
IEEE Internet Things Mag., November, 2024

Evaluation and Analysis of a Digital Forensic Readiness Framework for the IIoT.
Proceedings of the 12th International Symposium on Digital Forensics and Security, 2024

Securing Industrial Control Systems (ICS) Through Attack Modelling and Rule-Based Learning.
Proceedings of the 16th International Conference on COMmunication Systems & NETworkS, 2024

2023
Fog-cloud based intrusion detection system using Recurrent Neural Networks and feature selection for IoT networks.
Comput. Networks, April, 2023

DoS Attacks, Human Factors, and Evidence Extraction for the Industrial Internet of Things (IIoT) Paradigm.
Proceedings of the 38th IEEE/ACM International Conference on Automated Software Engineering, ASE 2023, 2023

2022
Securing the Smart City Airspace: Drone Cyber Attack Detection through Machine Learning.
Future Internet, 2022

Traceability in supply chains: A Cyber security analysis.
Comput. Secur., 2022

Zero Trust Architecture (ZTA): A Comprehensive Survey.
IEEE Access, 2022

Unsupervised Machine Learning for Drone Forensics through Flight Path Analysis.
Proceedings of the 10th International Symposium on Digital Forensics and Security, 2022

2021
LCDA: Lightweight Continuous Device-to-Device Authentication for a Zero Trust Architecture (ZTA).
Comput. Secur., 2021

Towards a deep learning-driven intrusion detection approach for Internet of Things.
Comput. Networks, 2021

2020
Denial of service attack detection through machine learning for the IoT.
J. Inf. Telecommun., 2020

Averaged dependence estimators for DoS attack detection in IoT networks.
Future Gener. Comput. Syst., 2020

Toward a Deep Learning-Driven Intrusion Detection Approach for Internet of Things.
CoRR, 2020

Towards a Lightweight Continuous Authentication Protocol for Device-to-Device Communication.
Proceedings of the 19th IEEE International Conference on Trust, 2020

2019
Deep Learning-Based Intrusion Detection for IoT Networks.
Proceedings of the 24th IEEE Pacific Rim International Symposium on Dependable Computing, 2019

2017
Future challenges for smart cities: Cyber-security and digital forensics.
Digit. Investig., 2017

Modelling and Evaluation of Malicious Attacks against the IoT MQTT Protocol.
Proceedings of the 2017 IEEE International Conference on Internet of Things (iThings) and IEEE Green Computing and Communications (GreenCom) and IEEE Cyber, 2017

2013
Classifying malicious activities in Honeynets using entropy and volume-based thresholds.
Secur. Commun. Networks, 2013

2011
An Entropy and Volume-Based Approach for Identifying Malicious Activities in Honeynet Traffic.
Proceedings of the 2011 International Conference on Cyberworlds, 2011

Identifying network traffic features suitable for honeynet data analysis.
Proceedings of the 24th Canadian Conference on Electrical and Computer Engineering, 2011

A reliable peer-to-peer protocol for mobile Ad-Hoc wireless networks.
Proceedings of the 9th IEEE/ACS International Conference on Computer Systems and Applications, 2011


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