DeepAI AI Chat
Log In Sign Up

Intrusion detection in computer systems by using artificial neural networks with Deep Learning approaches

by   Sergio Hidalgo-Espinoza, et al.

Intrusion detection into computer networks has become one of the most important issues in cybersecurity. Attackers keep on researching and coding to discover new vulnerabilities to penetrate information security system. In consequence computer systems must be daily upgraded using up-to-date techniques to keep hackers at bay. This paper focuses on the design and implementation of an intrusion detection system based on Deep Learning architectures. As a first step, a shallow network is trained with labelled log-in [into a computer network] data taken from the Dataset CICIDS2017. The internal behaviour of this network is carefully tracked and tuned by using plotting and exploring codes until it reaches a functional peak in intrusion prediction accuracy. As a second step, an autoencoder, trained with big unlabelled data, is used as a middle processor which feeds compressed information and abstract representation to the original shallow network. It is proven that the resultant deep architecture has a better performance than any version of the shallow network alone. The resultant functional code scripts, written in MATLAB, represent a re-trainable system which has been proved using real data, producing good precision and fast response.


page 1

page 2

page 3

page 4


Deep learning for cyber security intrusion detection: Approaches, datasets, and comparative study

n this paper, we present a survey of deep learning approaches for cyber ...

A Compendium on Network and Host based Intrusion Detection Systems

The techniques of deep learning have become the state of the art methodo...

Network Intrusion Detection with Limited Labeled Data

With the increasing dependency of daily life over computer networks, the...

Mimic Learning to Generate a Shareable Network Intrusion Detection Model

Purveyors of malicious network attacks continue to increase the complexi...

Two-stage Deep Stacked Autoencoder with Shallow Learning for Network Intrusion Detection System

Sparse events, such as malign attacks in real-time network traffic, have...

Comparison of System Call Representations for Intrusion Detection

Over the years, artificial neural networks have been applied successfull...