A modified grey wolf optimization algorithm for an intrusion detection system
Cyber-attacks and unauthorized application usage have increased due to the extensive use
of Internet services and applications over computer networks, posing a threat to the service's …
of Internet services and applications over computer networks, posing a threat to the service's …
A novel fully convolutional neural network approach for detection and classification of attacks on industrial IoT devices in smart manufacturing systems
Abstract Recently, Internet of things (IoT) devices have been widely implemented and
technologically advanced in manufacturing settings to monitor, collect, exchange, analyze …
technologically advanced in manufacturing settings to monitor, collect, exchange, analyze …
Chameleon: Optimized feature selection using particle swarm optimization and ensemble methods for network anomaly detection
In this paper, we propose an optimization approach by leveraging swarm intelligence and
ensemble methods to solve the non-deterministic feature selection problem. The proposed …
ensemble methods to solve the non-deterministic feature selection problem. The proposed …
An edge based hybrid intrusion detection framework for mobile edge computing
Abstract The Mobile Edge Computing (MEC) model attracts more users to its services due to
its characteristics and rapid delivery approach. This network architecture capability enables …
its characteristics and rapid delivery approach. This network architecture capability enables …
An efficient framework for detection and classification of iot botnet traffic
Abstract The Internet of Things (IoT) has become an integral requirement to equip common
life. According to IDC, the number of IoT devices may increase exponentially up to a trillion …
life. According to IDC, the number of IoT devices may increase exponentially up to a trillion …
Lbdmids: LSTM based deep learning model for intrusion detection systems for IOT networks
In the recent years, we have witnessed a huge growth in the number of Internet of Things
(loT) and edge devices being used in our everyday activities. This demands the security of …
(loT) and edge devices being used in our everyday activities. This demands the security of …
Privacy-preserving big data analytics for cyber-physical systems
Cyber-physical systems (CPS) generate big data collected from combining physical and
digital entities, but the challenge of CPS privacy-preservation demands further research to …
digital entities, but the challenge of CPS privacy-preservation demands further research to …
A comparative study on the impact of adversarial machine learning attacks on contemporary intrusion detection datasets
Adversarial attack techniques have taken a firm stand against the capabilities of deep neural
networks, rendering them less efficient in performing their functions. Various kind of attacks …
networks, rendering them less efficient in performing their functions. Various kind of attacks …
Optimization of intrusion detection systems determined by ameliorated HNADAM-SGD algorithm
Information security is of pivotal concern for consistently streaming information over the
widespread internetwork. The bottleneck flow of incoming and outgoing data traffic …
widespread internetwork. The bottleneck flow of incoming and outgoing data traffic …
An abnormal traffic detection model combined biindrnn with global attention
H Li, H Ge, H Yang, J Yan, Y Sang - IEEE access, 2022 - ieeexplore.ieee.org
As time series data with internal correlation, networks traffic data can be used for abnormal
detection using Recurrent Neural Network (RNN) and its variants, but existing models are …
detection using Recurrent Neural Network (RNN) and its variants, but existing models are …