Intrusion detection mechanism for large scale networks using CNN-LSTM

L Karanam, KK Pattanaik… - 2020 13th International …, 2020 - ieeexplore.ieee.org
In today's world, Network and System Security are of paramount importance in the digital
communication environment. To avoid breaches, it is badly needed for a security …

Advanced intrusion detection using deep learning-LSTM network on cloud environment

P Jisna, T Jarin, PN Praveen - 2021 Fourth International …, 2021 - ieeexplore.ieee.org
Cloud Computing is a favored choice of any IT organization in the current context since that
provides flexibility and pay-per-use service to the users. Moreover, due to its open and …

Efficient deep CNN-BiLSTM model for network intrusion detection

J Sinha, M Manollas - Proceedings of the 2020 3rd International …, 2020 - dl.acm.org
The need for Network Intrusion Detection systems has risen since usage of cloud
technologies has become mainstream. With the ever growing network traffic, Network …

A scalable network intrusion detection system using bi-lstm and cnn

SS Kanumalli, K Lavanya, A Rajeswari… - … and Smart Energy …, 2023 - ieeexplore.ieee.org
As cloud technologies are used more frequently, network intrusion detection systems are
becoming increasingly well-liked. Due to ever-increasing network traffic and the regular …

Combining CNNs and Bi-LSTMs for Enhanced Network Intrusion Detection: A Deep Learning Approach

SP Praveen, S Sindhura, PN Srinivasu… - 2023 3rd International …, 2023 - ieeexplore.ieee.org
Network Intrusion Detection Systems have become more popular as cloud technologies
have become more widely adopted. This paper presents a network intrusion detection …

NIDS-CNNLSTM: Network intrusion detection classification model based on deep learning

J Du, K Yang, Y Hu, L Jiang - IEEE Access, 2023 - ieeexplore.ieee.org
Intrusion detection is the core topic of network security, and the intrusion detection algorithm
based on deep learning has become a research hotspot in network security. In this paper, a …

DeepInsight-convolutional neural network for intrusion detection systems

TP Tran, VC Nguyen, L Vu… - 2021 8th NAFOSTED …, 2021 - ieeexplore.ieee.org
Intrusion detection systems (IDSs) play a critical role in many computer networks to combat
attacks from external environments. However, due to the rapid spread of various new …

Deep IDS: A deep learning approach for Intrusion detection based on IDS 2018

A Dey - 2020 2nd International Conference on Sustainable …, 2020 - ieeexplore.ieee.org
Intrusion Detection is one of the fields network security important for industry 4.0. Applying
deep learning models opened a new scope in this field. But availability of latest data set and …

A hypertuned lightweight and scalable LSTM model for hybrid network intrusion detection

A Bibi, GA Sampedro, A Almadhor, AR Javed, T Kim - Technologies, 2023 - mdpi.com
Given the increasing frequency of network attacks, there is an urgent need for more effective
network security measures. While traditional approaches such as firewalls and data …

A novel intrusion detector based on deep learning hybrid methods

S Wang, C Xia, T Wang - 2019 IEEE 5th Intl Conference on Big …, 2019 - ieeexplore.ieee.org
Intrusion detection system plays an important role in network security defense. It analyzes
network traffic and connection characteristics to identify various types of network attacks …