This preprint is under consideration at Wireless Personal Communications. A preprint is a preliminary version of a manuscript that has not completed peer review at a journal. Research Square does not conduct peer review prior to posting preprints. The posting of a preprint on this server should not be interpreted as an endorsement of its validity or suitability for dissemination as established information or for guiding clinical practice.
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Research Article
Beslin Pajila
Francis Xavier Engineering College
Corresponding Author
ORCiD: https://orcid.org/0000-0002-3905-2460
License:
This work is licensed under a CC BY 4.0 License. Read Full License
Wireless sensor networks (WSN) is considering as one of the exploring technology. WSN has a large number of sensor nodes, which sense the environment and collect the data. The collected data are sending to the sink through the intermediate nodes. Since the sensors node data are exposed to the internet, there is a possibility of vulnerability in the WSN. The common attack that affects most of the sensor nodes is the DDoS attack. In this paper aims to identify the DDoS attack quickly and to recover sensors using the fuzzy logic mechanism. In the Fuzzy based DDoS attack Detection and Recovery mechanism (FBDR) method uses type 1 fuzzy-logic to detect the occurrence of DDoS attack in a node. Similarly fuzzy- type 2 is used for recovery DDoS attack. Both the type 1 fuzzy-based rule and type 2 fuzzy-based rule perform well in terms of identifying the DDoS attack and recover the DDoS attack. It also helps to reduce the energy consumption of each node and improves the lifetime of the network. The proposed FBDR scheme is compared with other related schemes. The experimental results represent that the FBDR method works better than other similar schemes.
Keywords
Wireless Sensor Networks, type 1 Fuzzy logic, type 2 fuzzy logic, DDoS (Distributed Denial of Service) attack, Network lifetime, Energy Consumption.
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This preprint is under consideration at Wireless Personal Communications. A preprint is a preliminary version of a manuscript that has not completed peer review at a journal. Research Square does not conduct peer review prior to posting preprints. The posting of a preprint on this server should not be interpreted as an endorsement of its validity or suitability for dissemination as established information or for guiding clinical practice.
Learn more about In Review
Research Article
Beslin Pajila
Francis Xavier Engineering College
Corresponding Author
ORCiD: https://orcid.org/0000-0002-3905-2460
Badges
Prescreen
This manuscript passed our Prescreen assessment
Complete author information
Appropriate declaration statements
Potential risks to human health
Prescreen
Peer Review Timeline
CURRENT STATUS: Under Review
Version 1
Posted 25 Mar, 2021
No community comments so far
Review #? received
Received 20 Mar, 2021
Editor assigned
On 16 Feb, 2021
First submitted
On 06 Feb, 2021
Metrics
Comments: 0
PDF Downloads: ...
HTML Views: ...
License:
This work is licensed under a CC BY 4.0 License. Read Full License
Wireless sensor networks (WSN) is considering as one of the exploring technology. WSN has a large number of sensor nodes, which sense the environment and collect the data. The collected data are sending to the sink through the intermediate nodes. Since the sensors node data are exposed to the internet, there is a possibility of vulnerability in the WSN. The common attack that affects most of the sensor nodes is the DDoS attack. In this paper aims to identify the DDoS attack quickly and to recover sensors using the fuzzy logic mechanism. In the Fuzzy based DDoS attack Detection and Recovery mechanism (FBDR) method uses type 1 fuzzy-logic to detect the occurrence of DDoS attack in a node. Similarly fuzzy- type 2 is used for recovery DDoS attack. Both the type 1 fuzzy-based rule and type 2 fuzzy-based rule perform well in terms of identifying the DDoS attack and recover the DDoS attack. It also helps to reduce the energy consumption of each node and improves the lifetime of the network. The proposed FBDR scheme is compared with other related schemes. The experimental results represent that the FBDR method works better than other similar schemes.
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