Zero-day attack detection: a systematic literature review

R Ahmad, I Alsmadi, W Alhamdani… - Artificial Intelligence …, 2023 - Springer
With the continuous increase in cyberattacks over the past few decades, the quest to
develop a comprehensive, robust, and effective intrusion detection system (IDS) in the …

A dynamic ensemble algorithm for anomaly detection in IoT imbalanced data streams

J Jiang, F Liu, Y Liu, Q Tang, B Wang, G Zhong… - Computer …, 2022 - Elsevier
With the rapid development of ambient intelligence (AmI) in the Internet of Things (IoT),
many data streams are generated from sensing devices in intelligent scenarios. Due to the …

Causality-Guided Counterfactual Debiasing for Anomaly Detection of Cyber-Physical Systems

W Tang, J Liu, Y Zhou, Z Ding - IEEE Transactions on Industrial …, 2023 - ieeexplore.ieee.org
Machine learning has become a promising technology for anomaly detection of cyber-
physical systems (CPSs). However, the trained anomaly detection models always suffer from …

Mean-Shift and Local Outlier Factor-Based Ensemble Machine Learning Approach for Anomaly Detection in IoT Devices

AK Gulhare, A Badholia… - … Conference on Inventive …, 2022 - ieeexplore.ieee.org
IoT devices are rapidly being used in everyday life. However, many of these devices are
susceptible as a result of insecure design, implementation, and setup. As a consequence …

Machine Learning-based Oddity Detection of Smoke and Gas Sensor Data in a Large Gated Community

DS Harsha, B Suresh… - 2022 IEEE International …, 2022 - ieeexplore.ieee.org
Oddity detection identifies strange events or observations that are statistically distinct from
the rest of the data and can cause concern. The paper proposes a method to find oddities …

Fault Estimation for Operational Systems

T Ozkent, EG Soyak - 2022 Innovations in Intelligent Systems …, 2022 - ieeexplore.ieee.org
Operational systems are crucial for corporations. A majority of the business processes flow
through these systems and even minor downtimes on these systems may cause serious …

The Hierarchical Ensemble Model for Network Intrusion Detection in the Real-world Dataset

L Chen, SE Weng, CJ Peng, YC Li… - … on Circuits and …, 2022 - ieeexplore.ieee.org
Network intrusion detection is an indispensable defense in the critical era fulling of
cyberattacks. However, it faces a severe class imbalanced issue, and most of the researches …

mkdnad: A network flow anomaly detection method based on multi-teacher knowledge distillation

Y Yang, D Liu - 2022 16th IEEE International Conference on …, 2022 - ieeexplore.ieee.org
Anomaly detection models for network flow based on machine learning have poor detection
performance under extremely unbalanced training data conditions, and also have slow …