ELIDS: Ensemble Feature Selection for Lightweight IDS against DDoS Attacks in Resource-Constrained IoT Environment
Abstract Distributed Denial of Service (DDoS) attacks are increasingly prevalent in today's
digital era, particularly due to the growth of unprotected Internet of Things (IoT) devices. This …
digital era, particularly due to the growth of unprotected Internet of Things (IoT) devices. This …
Establishment of critical non-depositing velocity prediction model for sediment in drip irrigation laterals based on PSO-SVM
C Wang, D Bai, Y Li, Q Zhang, X Ma, D Tian… - Journal of Cleaner …, 2024 - Elsevier
Accurately determining the critical non-depositing velocity for sediment (CNDVS) in drip
irrigation laterals is essential to address issues of sediment deposition and clogging in drip …
irrigation laterals is essential to address issues of sediment deposition and clogging in drip …
[HTML][HTML] Machine learning-enabled hybrid intrusion detection system with host data transformation and an advanced two-stage classifier
Abstract Network Intrusion Detection Systems (NIDS) have been extensively investigated by
monitoring real network traffic and analyzing suspicious activities. However, there are …
monitoring real network traffic and analyzing suspicious activities. However, there are …
Performance comparison analysis of classification methodologies for effective detection of intrusions
Intrusion detection systems (IDS) are critical in many applications, including cloud
environments. The intrusion poses a security threat and extracts privacy data and …
environments. The intrusion poses a security threat and extracts privacy data and …
A Machine Learning-Based Framework with Enhanced Feature Selection and Resampling for Improved Intrusion Detection
F Malik, Q Waqas Khan, A Rizwan, R Alnashwan… - Mathematics, 2024 - mdpi.com
Intrusion Detection Systems (IDSs) play a crucial role in safeguarding network
infrastructures from cyber threats and ensuring the integrity of highly sensitive data …
infrastructures from cyber threats and ensuring the integrity of highly sensitive data …
Privacy-Preserving Attribute-Based Access Control Scheme with Intrusion Detection and Policy Hiding for Data Sharing in VANET
Vehicle Ad-hoc Network (VANET) plays an important role in improving traffic management
and driving safety. Data sharing in VANET can be achieved using such communications as …
and driving safety. Data sharing in VANET can be achieved using such communications as …
Research on Dung Beetle Optimization Based Stacked Sparse Autoencoder for Network Situation Element Extraction
Y Yang, P Zhao - IEEE Access, 2024 - ieeexplore.ieee.org
Network security situation awareness enables networks to actively and effectively defend
against network attacks, relying on the extraction of network situation elements as an initial …
against network attacks, relying on the extraction of network situation elements as an initial …
HybridRobustNet: enhancing detection of hybrid attacks in IoT networks through advanced learning approach
The proliferation of Internet of Things (IoT) devices has revolutionized various domains, but it
has also brought forth numerous security challenges. One of the most concerning threats is …
has also brought forth numerous security challenges. One of the most concerning threats is …
[HTML][HTML] IDS-Anta: An open-source code with a defense mechanism to detect adversarial attacks for intrusion detection system
K Barik, S Misra - Software Impacts, 2024 - Elsevier
An intrusion detection system (IDS) is critical in protecting organizations from cyber threats.
The susceptibility of Machine Learning and Deep Learning-based IDSs against adversarial …
The susceptibility of Machine Learning and Deep Learning-based IDSs against adversarial …
An Efficient Anomaly Detection System in IoT Edge using Chi Square-Improved Particle Swarm Optimization Feature Selection with Ensemble classifiers
J Manokaran, V Gurusamy, O Khalaf… - … of Computing and …, 2024 - journal.uob.edu.bh
Anomaly detection using machine learning (ML) algorithms is the key research theme in the
modern digital era. Though the recent ML-based anomaly detection models have better …
modern digital era. Though the recent ML-based anomaly detection models have better …