Anomaly detection in Internet of medical Things with Blockchain from the perspective of deep neural network

J Wang, H Jin, J Chen, J Tan, K Zhong - Information Sciences, 2022 - Elsevier
IoMT technology has many advantages in healthcare system, such as optimizing the
medical service model, improving the efficiency of hospital operation and management, and …

Anomaly traffic detection in IoT security using graph neural networks

M Gao, L Wu, Q Li, W Chen - Journal of Information Security and …, 2023 - Elsevier
The number of Internet of Things (IoT) devices is expanding quickly as IoT gradually spreads
to all aspects of life. At the same time, IoT devices have emerged as a new attack medium for …

Detecting anomalous IoT traffic flow with locality sensitive hashes

B Charyyev, MH Gunes - GLOBECOM 2020-2020 IEEE Global …, 2020 - ieeexplore.ieee.org
Widespread adoption of Internet of Things (IoT) devices increased the variety of devices
connected to a network. These devices have become a primary target of cyber-attacks as …

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 …

Deep-IFS: Intrusion detection approach for industrial internet of things traffic in fog environment

M Abdel-Basset, V Chang, H Hawash… - IEEE Transactions …, 2020 - ieeexplore.ieee.org
The extensive propagation of industrial Internet of Things (IIoT) technologies has
encouraged intruders to initiate a variety of attacks that need to be identified to maintain the …

Anomaly detection framework for Internet of things traffic using vector convolutional deep learning approach in fog environment

BA NG, S Selvakumar - Future Generation Computer Systems, 2020 - Elsevier
The proliferation of Internet of things (IoT) devices has lured hackers to launch attacks.
Therefore, anomalies in IoT traffic must be detected to mitigate these attacks and protect …

DOC-IDS: a deep learning-based method for feature extraction and anomaly detection in network traffic

N Yoshimura, H Kuzuno, Y Shiraishi, M Morii - Sensors, 2022 - mdpi.com
With the growing diversity of cyberattacks in recent years, anomaly-based intrusion detection
systems that can detect unknown attacks have attracted significant attention. Furthermore, a …

Intrusion detection using network traffic profiling and machine learning for IoT

JR Rose, M Swann, G Bendiab… - 2021 IEEE 7th …, 2021 - ieeexplore.ieee.org
The rapid increase in the use of IoT devices brings many benefits to the digital society,
ranging from improved efficiency to higher productivity. However, the limited resources and …

Fast model update for iot traffic anomaly detection with machine unlearning

J Fan, K Wu, Y Zhou, Z Zhao… - IEEE Internet of Things …, 2022 - ieeexplore.ieee.org
It is often needed to update deep learning-based detection models in traffic anomaly
detection systems for the Internet of Things (IoT) because of mislabeled samples or device …

MS‐ADS: multistage spectrogram image‐based anomaly detection system for IoT security

Z Ahmad, AS Khan, K Zen… - Transactions on Emerging …, 2023 - Wiley Online Library
The innovative computing idea of Internet‐of‐Things (IoT) architecture has gained
tremendous popularity over the last decade, resulting in an exponential increase in the …