A comprehensive survey on DDoS defense systems: New trends and challenges
In the past ten years, the source of DDoS has migrated to botnets composed of IoT devices.
The scale of DDoS attacks increases dramatically with the number of IoT devices. New …
The scale of DDoS attacks increases dramatically with the number of IoT devices. New …
Analysis of machine learning classifiers for early detection of DDoS attacks on IoT devices
Distributed denial-of-service attacks are still difficult to handle as per current scenarios. The
attack aim is a menace to network security and exhausting the target networks with …
attack aim is a menace to network security and exhausting the target networks with …
Chronos: Ddos attack detection using time-based autoencoder
Cognitive network management is becoming quintessential to realize autonomic networking.
However, the wide spread adoption of the Internet of Things (IoT) devices, increases the risk …
However, the wide spread adoption of the Internet of Things (IoT) devices, increases the risk …
Detection and characterization of ddos attacks using time-based features
J Halladay, D Cullen, N Briner, J Warren, K Fye… - IEEE …, 2022 - ieeexplore.ieee.org
In today's evolving cybersecurity landscape, distributed denial-of-service (DDoS) attacks
have become one of the most prolific and costly threats. Their capability to incapacitate …
have become one of the most prolific and costly threats. Their capability to incapacitate …
A novel unbalanced weighted KNN based on SVM method for pipeline defect detection using eddy current measurements
S Lu, Y Yue, X Liu, J Wu, Y Wang - Measurement Science and …, 2022 - iopscience.iop.org
Pipeline safety inspections are particularly important because they are the most common
means of energy transportation. In order to avoid pipe leakage, eddy current inspection is …
means of energy transportation. In order to avoid pipe leakage, eddy current inspection is …
STEAMCODER: Spatial and temporal adaptive dynamic convolution autoencoder for anomaly detection
P Xu, H Gan, H Fu, Z Zhang - Knowledge-Based Systems, 2023 - Elsevier
The anomaly detection algorithm greatly improves the reliability of equipment operation.
Traditional anomaly detection algorithms are mostly designed for large data sets, making it …
Traditional anomaly detection algorithms are mostly designed for large data sets, making it …
Comparative analysis of machine learning models for anomaly detection in manufacturing
A Kharitonov, A Nahhas, M Pohl, K Turowski - Procedia Computer Science, 2022 - Elsevier
The introduction of various technologies in the context of Industry 4.0 allowed collecting
monitoring data for various fields in manufacturing. Shop-floor and production data can be …
monitoring data for various fields in manufacturing. Shop-floor and production data can be …
Multifractal detrended fluctuation analysis based detection for SYN flooding attack
The TCP SYN flooding (half-open connection) attack is a type of DDoS attack, which denies
the services by consuming the server resources. This attack prevents legitimate users from …
the services by consuming the server resources. This attack prevents legitimate users from …
A Hybrid Mutual Authentication Approach for Artificial Intelligence of Medical Things
Artificial Intelligence of Medical Things (AIoMT) is a hybrid of the Internet of Medical Things
(IoMT) and artificial intelligence to materialize the acquisition of real-time data via the smart …
(IoMT) and artificial intelligence to materialize the acquisition of real-time data via the smart …
Spotting anomalies at the edge: Outlier exposure-based cross-silo federated learning for ddos detection
Distributed Denial-of-Service (DDoS) attacks are expected to continue plaguing service
availability in emerging networks which rely on distributed edge clouds to offer critical …
availability in emerging networks which rely on distributed edge clouds to offer critical …