DeepAI AI Chat
Log In Sign Up

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

by   Nickolaos Koroniotis, et al.

The Internet of Things (IoT) paradigm has displayed tremendous growth in recent years, resulting in innovations like Industry 4.0 and smart environments that provide improvements to efficiency, management of assets and facilitate intelligent decision making. However, these benefits are offset by considerable cybersecurity concerns that arise due to inherent vulnerabilities, which hinder IoT-based systems' Confidentiality, Integrity, and Availability. Security vulnerabilities can be detected through the application of penetration testing, and specifically, a subset of the information-gathering stage, known as vulnerability identification. Yet, existing penetration testing solutions can not discover zero-day vulnerabilities from IoT environments, due to the diversity of generated data, hardware constraints, and environmental complexity. Thus, it is imperative to develop effective penetration testing solutions for the detection of vulnerabilities in smart IoT environments. In this paper, we propose a deep learning-based penetration testing framework, namely Long Short-Term Memory Recurrent Neural Network-Enabled Vulnerability Identification (LSTM-EVI). We utilize this framework through a novel cybersecurity-oriented testbed, which is a smart airport-based testbed comprised of both physical and virtual elements. The framework was evaluated using this testbed and on real-time data sources. Our results revealed that the proposed framework achieves about 99 outperforming other four peer techniques.


page 4

page 5


PatrIoT: IoT Automated Interoperability and Integration Testing Framework

With the rapid growth of the contemporary Internet of Things (IoT) marke...

Towards a Cybersecurity Testbed for Agricultural Vehicles and Environments

In today's modern farm, an increasing number of agricultural systems and...

Automated Security Assessment for the Internet of Things

Internet of Things (IoT) based applications face an increasing number of...

Physical Layer Security based Key Management for LoRaWAN

Within this the work applicability of Physical LayerSecurity (PHYSEC) ba...

Ethical Hacking for IoT Security: A First Look into Bug Bounty Programs and Responsible Disclosure

The security of the Internet of Things (IoT) has attracted much attentio...

Autosploit: A Fully Automated Framework for Evaluating the Exploitability of Security Vulnerabilities

The existence of a security vulnerability in a system does not necessari...