A Deep Learning-based Penetration Testing Framework for Vulnerability Identification in Internet of Things Environments

Author:

Koroniotis Nickolaos1,Moustafa Nour1,Turnbull Benjamin1,Schiliro Francesco1,Gauravaram Praveen1,Janicke Helge1

Affiliation:

1. Cyber Security Cooperative Research Centre (CSCRC),Perth,WA,Australia,6027

Publisher

IEEE

Reference22 articles.

1. A study on penetration testing process and tools

2. Internal Network Penetration Testing Using Free/Open Source Tools: Network and System Administration Approach

3. Creating novel features to anomaly network detection using darpa-2009 data set;moustaf;Proceedings of the 14th European Conference on Cyber Warfare and Security Academic Conferences Limited,0

4. FGMC-HADS: Fuzzy Gaussian mixture-based correntropy models for detecting zero-day attacks from linux systems

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2. Optimal Deep-Learning-Based Cyberattack Detection in a Blockchain-Assisted IoT Environment;Mathematics;2023-09-26

3. Review on Penetration Testing Techniques in Cyber security;2023 Second International Conference on Augmented Intelligence and Sustainable Systems (ICAISS);2023-08-23

4. A Comprehensive Literature Review of Artificial Intelligent Practices in the Field of Penetration Testing;Lecture Notes in Electrical Engineering;2023

5. Understanding the Penetration Test Workflow: a security test with Tramonto in an e-Government application;2022 IEEE International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom);2022-12

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