Lightweight IoT Malware Detection Solution Using CNN Classification

10/13/2020
by   Ahmad M. N. Zaza, et al.
0

Internet of Things (IoT) is becoming more frequently used in more applications as the number of connected devices is in a rapid increase. More connected devices result in bigger challenges in terms of scalability, maintainability and most importantly security especially when it comes to 5G networks. The security aspect of IoT devices is an infant field, which is why it is our focus in this paper. Multiple IoT device manufacturers do not consider securing the devices they produce for different reasons like cost reduction or to avoid using energy-harvesting components. Such potentially malicious devices might be exploited by the adversary to do multiple harmful attacks. Therefore, we developed a system that can recognize malicious behavior of a specific IoT node on the network. Through convolutional neural network and monitoring, we were able to provide malware detection for IoT using a central node that can be installed within the network. The achievement shows how such models can be generalized and applied easily to any network while clearing out any stigma regarding deep learning techniques.

READ FULL TEXT
POST COMMENT

Comments

There are no comments yet.

Authors

page 3

02/11/2018

Lightweight Classification of IoT Malware based on Image Recognition

The Internet of Things (IoT) is an extension of the traditional Internet...
11/03/2021

A Survey of Machine Learning Algorithms for Detecting Malware in IoT Firmware

This work explores the use of machine learning techniques on an Internet...
05/22/2020

Hermes: Enabling Energy-efficient IoT Networks with Generalized Deduplication

With the advent of the Internet of Things (IoT), the ever growing number...
05/05/2021

Current State of IPv6 Security in IoT

This report presents the current state of security in IPv6 for IoT devic...
08/05/2019

On the security of ballot marking devices

A recent debate among election experts has considered whether electronic...
10/24/2020

Safeguarding the IoT from Malware Epidemics: A Percolation Theory Approach

The upcoming Internet of things (IoT) is foreseen to encompass massive n...
09/08/2021

Malware Squid: A Novel IoT Malware Traffic Analysis Framework using Convolutional Neural Network and Binary Visualisation

Internet of Things devices have seen a rapid growth and popularity in re...
This week in AI

Get the week's most popular data science and artificial intelligence research sent straight to your inbox every Saturday.