Identify Selective Forwarding Attacks Using Danger Model: Promote the Detection Accuracy in Wireless Sensor Networks
Author:
Affiliation:
1. School of Optoelectronic Science and Engineering, University of Electronic Science and Technology of China, Chengdu, China
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Electrical and Electronic Engineering,Instrumentation
Link
http://xplorestaging.ieee.org/ielx7/7361/9774386/09755128.pdf?arnumber=9755128
Reference27 articles.
1. Secure IoT routing: Selective forwarding attacks and trust-based defenses in RPL network;jiang;arXiv 2201 06937,2022
2. A reputation‐based RPL protocol to detect selective forwarding attack in Internet of Things
3. Securing Wireless Sensor Networks Against Denial‐of‐Sleep Attacks Using RSA Cryptography Algorithm and Interlock Protocol
4. The Receptor Density Algorithm
5. Host-based intrusion detection systems adapted from agent-based artificial immune systems
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1. A Federated Learning Mechanism for Mitigating Selective Forwarding Attacks in RPL-Based Internet of Things;2024 IEEE International Conference on Communications Workshops (ICC Workshops);2024-06-09
2. DSAT-IDS: Dissimilarity and Adaptive Threshold-based Intrusion Detection system to mitigate selective forwarding attack in the RPL-based 6LoWPAN;Cluster Computing;2024-06-07
3. Enhancing Energy Efficiency in Intrusion Detection Systems for Wireless Sensor Networks Through Zigbee Protocol;Advances in IT Standards and Standardization Research;2024-05-31
4. Probabilistic models for evaluating network edge's resistance against scan and foothold attack;IET Communications;2024-04-23
5. GD3N: Adaptive clustering-based detection of selective forwarding attacks in WSNs under variable harsh environments;Information Sciences;2024-04
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