A scalable and hybrid intrusion detection system based on the convolutional-LSTM network

MA Khan, MR Karim, Y Kim - Symmetry, 2019 - mdpi.com
With the rapid advancements of ubiquitous information and communication technologies, a
large number of trustworthy online systems and services have been deployed. However …

ChaosNet: A chaos based artificial neural network architecture for classification

HN Balakrishnan, A Kathpalia, S Saha… - … Journal of Nonlinear …, 2019 - pubs.aip.org
Inspired by chaotic firing of neurons in the brain, we propose ChaosNet—a novel chaos
based artificial neural network architecture for classification tasks. ChaosNet is built using …

A comparative analysis of deep learning approaches for network intrusion detection systems (N-IDSs): deep learning for N-IDSs

R Vinayakumar, KP Soman… - International Journal of …, 2019 - igi-global.com
Recently, due to the advance and impressive results of deep learning techniques in the
fields of image recognition, natural language processing and speech recognition for various …

Machine learning for security at the iot edge-a feasibility study

H Wang, L Barriga, A Vahidi… - 2019 IEEE 16th …, 2019 - ieeexplore.ieee.org
Benefits of edge computing include reduced latency and bandwidth savings, privacy-by-
default and by-design in compliance with new privacy regulations that encourage sharing …

Securitization of smart home network using dynamic authentication

S Sreedharan, N Rakesh - International Conference on Computer …, 2019 - Springer
Smart home networks today span from technological advances that introduced highly
networked devices of high density to applications which are more vulnerable due to its …

A Comparative Analysis of Deep Learning Approaches for Network Intrusion Detection Systems (N-IDSs): Deep Learning for N-IDSs.

P Poornachandran - International Journal of Digital Crime & …, 2019 - search.ebscohost.com
Recently, due to the advance and impressive results of deep learning techniques in the
fields of image recognition, natural language processing and speech recognition for various …

[PDF][PDF] An Efficient Bio-Inspired Algorithm Based Data Classification Model For Intrusion Detection In Mobile AdhocNetworks

S Murugan, M Jeyakarthic - The International journal of analytical …, 2019 - researchgate.net
Presently, mobile ad hoc networks (MANET) show its applicability in several domains due to
the self-configurable nature of independent mobile nodes. The nature of wireless links …

Machine Learning Approaches for Traffic Flow Forecasting

AA Rahi - 2019 - uhra.herts.ac.uk
Intelligent Transport Systems (ITS) as a field has emerged quite rapidly in the recent years. A
competitive solution coupled with big data gathered for ITS applications needs the latest AI …

Long Short Term Memory Based Detection Of Web Based Sql Injection Attacks

MC Mwaruwa - 2019 - erepository.uonbi.ac.ke
The internet has experienced considerable growth in the past decade due to increased ease
of access and growth of mobile technologies. The internet is increasingly being used for …

A new intrusion detection model based on GRU and salient feature approach

J Hou, F Liu, X Zhuang - Dependability in Sensor, Cloud, and Big Data …, 2019 - Springer
Abstract Gated Recurrent Unit (GRU) is a variant of a recurrent neural network, just like an
LSTM network. Compared with RNN, the two networks have higher accuracy in processing …