A review of intrusion detection systems using machine and deep learning in internet of things: Challenges, solutions and future directions

J Asharf, N Moustafa, H Khurshid, E Debie, W Haider… - Electronics, 2020 - mdpi.com
The Internet of Things (IoT) is poised to impact several aspects of our lives with its fast
proliferation in many areas such as wearable devices, smart sensors and home appliances …

Intrusion detection using deep neural network with antirectifier layer

R Lohiya, A Thakkar - … and Communication Networks: Proceedings of ACN …, 2021 - Springer
Data security is regarded to be one of the crucial challenges in this fast-growing internet
world. Data generated through internet is exposed to various types of vulnerabilities and …

Machine Learning Based Predictive Model for Intrusion Detection

S Srivastav, K Guleria, S Sharma - … International Conference on …, 2023 - ieeexplore.ieee.org
A software that examines network traffic and searches for inconsistencies is known as an
Intrusion Detection System (IDS). Network changes that seem to be abnormal or unexpected …

Enhanced IoT based Approach to provide Secured System

RMD Charaan, SA James, DA Kumar… - 2022 International …, 2022 - ieeexplore.ieee.org
The Internet of Things (IoT) is a new generation of linked technologies that makes use of a
variety of networks to give intelligent services to end users. It is based on different networks …

[HTML][HTML] A deep learning technique for intrusion detection system using a Recurrent Neural Networks based framework

SM Kasongo - Computer Communications, 2023 - Elsevier
In recent years, the spike in the amount of information transmitted through communication
infrastructures has increased due to the advances in technologies such as cloud computing …

[PDF][PDF] Optimized machine learning algorithm for intrusion detection

RAI Alhayali, M Aljanabi, AH Ali… - Indonesian Journal of …, 2021 - academia.edu
Intrusion detection is mainly achieved by using optimization algorithms. The need for
optimization algorithms for intrusion detection is necessitated by the increasing number of …

Deep learning in intrusion detection systems

G Karatas, O Demir… - … international congress on …, 2018 - ieeexplore.ieee.org
In recent years, due to the emergence of boundless communication paradigm and increased
number of networked digital devices, there is a growing concern about cybersecurity which …

Network security: threat model, attacks, and IDS using machine learning

D Kapil, N Mehra, A Gupta, S Maurya… - … conference on artificial …, 2021 - ieeexplore.ieee.org
Nowadays, computer technology has become necessary in our day-to-day life in various
aspects such as communication, entertainment, education, banking, etc. In the digital era …

Performance assessment of IDS based on CICIDS-2017 dataset

V Priyanka, T Gireesh Kumar - … (ICTCS 2020) ICT: Applications and Social …, 2022 - Springer
With the exponential growth of the internet among users worldwide, network engineers pose
a great challenge in network security to identify intrusion activities. Intrusion Detection …

A composite approach of intrusion detection systems: hybrid RNN and correlation-based feature optimization

S Gautam, A Henry, M Zuhair, M Rashid, AR Javed… - Electronics, 2022 - mdpi.com
Detection of intrusions is a system that is competent in detecting cyber-attacks and network
anomalies. A variety of strategies have been developed for IDS so far. However, there are …