Please use this identifier to cite or link to this item:
https://hdl.handle.net/2440/135551
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Full metadata record
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dc.contributor.author | Zhou, Y. | - |
dc.contributor.author | Shi, Z. | - |
dc.contributor.author | Sun, R. | - |
dc.date.issued | 2022 | - |
dc.identifier.citation | Proceedings of the ACM International Conference Proceeding Series (ACSW), 2022, pp.84-90 | - |
dc.identifier.isbn | 9781450396066 | - |
dc.identifier.uri | https://hdl.handle.net/2440/135551 | - |
dc.description.abstract | This project proposes a sensor-based visual agricultural monitoring system. Distinguished from traditional agricultural monitoring systems, this system further analyzes basic agricultural data, prevents attacks such as Jamming, Flooding, and Exhaustion, and monitors common wireless network attacks such as Selective Forwarding, Black Hole Attacks, Sinkhole Attacks, Flooding Attacks and Misdirection Attacks. Experimental verification and evaluation of the attack prevention and monitoring are also conducted. | - |
dc.description.statementofresponsibility | Yifan Zhou, Zhendong Shi, Ruoxi Sun | - |
dc.language.iso | en | - |
dc.publisher | Association for Computing Machinery | - |
dc.rights | © 2022 Association for Computing Machinery. Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from permissions@acm.org. | - |
dc.source.uri | https://www.acm.org/ | - |
dc.title | Visualization and Attack Prevention for a Sensor-Based Agricultural Monitoring System | - |
dc.type | Conference paper | - |
dc.contributor.conference | Australasian Computer Science Week (ACSW) (14 Feb 2022 - 17 Feb 2022 : Virtual Online) | - |
dc.identifier.doi | 10.1145/3511616.3513102 | - |
pubs.publication-status | Published | - |
dc.identifier.orcid | Sun, R. [0000-0001-5404-8550] | - |
Appears in Collections: | Computer Science publications |
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File | Description | Size | Format | |
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hdl_135551.pdf | Submitted version | 1.23 MB | Adobe PDF | View/Open |
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