Biologically Inspired Smart Contract: A Blockchain-Based DDoS Detection System

Han, X; Zhang, R; Liu, X; Jiang, F

Biologically Inspired Smart Contract: A Blockchain-Based DDoS Detection System

Han, X Zhang, R Liu, X Jiang, F

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Publisher:: IEEE
Publication Type:: Conference Proceeding
Citation:: 2020 IEEE International Conference on Networking, Sensing and Control (ICNSC), 2020, 00, pp. 1-6
Issue Date:: 2020-11-04

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Field	Value	Language
dc.contributor.author	Han, X
dc.contributor.author	Zhang, R
dc.contributor.author	Liu, X
dc.contributor.author	Jiang, F https://orcid.org/0000-0003-3765-561X
dc.date	2020-10-30
dc.date.accessioned	2021-05-25T02:16:42Z
dc.date.available	2021-05-25T02:16:42Z
dc.date.issued	2020-11-04
dc.identifier.citation	2020 IEEE International Conference on Networking, Sensing and Control (ICNSC), 2020, 00, pp. 1-6
dc.identifier.isbn	9781728168531
dc.identifier.uri	http://hdl.handle.net/10453/149192
dc.description.abstract	With the increase of Internet usage, the identification and recovery from cyber-attacks become the major concerns for cyber industries. Therefore, the harm caused by network attacks has caused widespread concern. Distributed Denial of Service (DDoS) attack is a very common destructive cyber attack. This is a network attack that destroys the network and can cause multiple computers to be attacked at the same time, failing to perform services properly. Therefore, based on the understanding of blockchain structure and DDoS characteristics, a blockchain-based DDoS detection model framework is proposed to form a blockchain-based collaborative detection system. We use the blockchain consortium chain structure to treat all participants as part of the private chain in the system. Each participating organization has its own channel, and other organizations cannot access its information, thus fully protecting the privacy of each participant. Our experimental results show that smart contracts can detect DDoS data and generate anomalous chains on each node. The time required to generate an exception chain and information sharing is very short, which indicates that the system can protect the privacy of user data. While sharing data in time, good results can be obtained as a collaborative detection system.
dc.language	en
dc.publisher	IEEE
dc.relation.ispartof	2020 IEEE International Conference on Networking, Sensing and Control (ICNSC)
dc.relation.ispartof	2020 IEEE International Conference on Networking, Sensing and Control
dc.relation.isbasedon	10.1109/icnsc48988.2020.9238104
dc.rights	info:eu-repo/semantics/closedAccess
dc.title	Biologically Inspired Smart Contract: A Blockchain-Based DDoS Detection System
dc.type	Conference Proceeding
utslib.citation.volume	00
utslib.location.activity	Nanjing, China
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Provost
pubs.organisational-group	/University of Technology Sydney/Provost/Jumbunna
utslib.copyright.status	closed_access	*
dc.date.updated	2021-05-25T02:16:41Z
pubs.finish-date	2020-11-02
pubs.publication-status	Published
pubs.start-date	2020-10-30
pubs.volume	00

Abstract:

With the increase of Internet usage, the identification and recovery from cyber-attacks become the major concerns for cyber industries. Therefore, the harm caused by network attacks has caused widespread concern. Distributed Denial of Service (DDoS) attack is a very common destructive cyber attack. This is a network attack that destroys the network and can cause multiple computers to be attacked at the same time, failing to perform services properly. Therefore, based on the understanding of blockchain structure and DDoS characteristics, a blockchain-based DDoS detection model framework is proposed to form a blockchain-based collaborative detection system. We use the blockchain consortium chain structure to treat all participants as part of the private chain in the system. Each participating organization has its own channel, and other organizations cannot access its information, thus fully protecting the privacy of each participant. Our experimental results show that smart contracts can detect DDoS data and generate anomalous chains on each node. The time required to generate an exception chain and information sharing is very short, which indicates that the system can protect the privacy of user data. While sharing data in time, good results can be obtained as a collaborative detection system.

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http://hdl.handle.net/10453/149192