LogEvent2vec : LogEvent-to-vector based anomaly detection for large-scale logs in internet of things
| dc.contributor.author | Wang, Jin | |
| dc.contributor.author | Tang, Yangning | |
| dc.contributor.author | He, Shiming | |
| dc.contributor.author | Zhao, Changqing | |
| dc.contributor.author | Sharma, Pradip Kumar | |
| dc.contributor.author | Alfarraj, Osama | |
| dc.contributor.author | Tolba, Amr | |
| dc.contributor.institution | University of Aberdeen.Computing Science | en |
| dc.contributor.institution | University of Aberdeen.Cybersecurity and Privacy | en |
| dc.date.accessioned | 2020-07-08T10:25:01Z | |
| dc.date.available | 2020-07-08T10:25:01Z | |
| dc.date.issued | 2020-05 | |
| dc.description | Funding: This work was funded by the National Natural Science Foundation of China (Nos. 61802030), the Research Foundation of Education Bureau of Hunan Province, China (No. 19B005), and the International Cooperative Project for “Double First-Class”, CSUST (No. 2018IC24), the open research fund of Key Lab of Broadband Wireless Communication and Sensor Network Technology (Nanjing University of Posts and Telecommunications), Ministry of Education (No. JZNY201905), the Open Research Fund of the Hunan Provincial Key Laboratory of Network Investigational Technology (No. 2018WLZC003). This work was funded by the Researchers Supporting Project No. (RSP-2019/102) King Saud University, Riyadh, Saudi Arabia. Acknowledgments: We thank Researchers Supporting Project No. (RSP-2019/102) King Saud University, Riyadh, Saudi Arabia, for funding this research. We thank Francesco Cauteruccio for proofreading this paper. | en |
| dc.description.status | Peer reviewed | en |
| dc.format.extent | 19 | |
| dc.format.extent | 1043977 | |
| dc.identifier | 171373082 | |
| dc.identifier | ba2d5267-8daf-4613-a839-e778b24cc9a6 | |
| dc.identifier | 85084058085 | |
| dc.identifier | 32357404 | |
| dc.identifier | 000537106200015 | |
| dc.identifier.citation | Wang, J, Tang, Y, He, S, Zhao, C, Sharma, P K, Alfarraj, O & Tolba, A 2020, 'LogEvent2vec : LogEvent-to-vector based anomaly detection for large-scale logs in internet of things', Sensors (Switzerland), vol. 20, no. 9, 2451. https://doi.org/10.3390/s20092451 | en |
| dc.identifier.doi | 10.3390/s20092451 | |
| dc.identifier.iss | 9 | en |
| dc.identifier.issn | 1424-8220 | |
| dc.identifier.other | ORCID: /0000-0001-6620-9083/work/76976513 | |
| dc.identifier.uri | https://hdl.handle.net/2164/14671 | |
| dc.identifier.url | http://www.scopus.com/inward/record.url?scp=85084058085&partnerID=8YFLogxK | en |
| dc.identifier.vol | 20 | en |
| dc.language.iso | eng | |
| dc.relation.ispartof | Sensors (Switzerland) | en |
| dc.subject | Device management | en |
| dc.subject | IoT | en |
| dc.subject | Log anomaly detection | en |
| dc.subject | Log event | en |
| dc.subject | Log template | en |
| dc.subject | Word2vec | en |
| dc.subject | log anomaly detection | en |
| dc.subject | log template | en |
| dc.subject | log event | en |
| dc.subject | word2vec | en |
| dc.subject | device management | en |
| dc.subject | QA75 Electronic computers. Computer science | en |
| dc.subject | Analytical Chemistry | en |
| dc.subject | Instrumentation | en |
| dc.subject | Atomic and Molecular Physics, and Optics | en |
| dc.subject | Electrical and Electronic Engineering | en |
| dc.subject | Biochemistry | en |
| dc.subject.lcc | QA75 | en |
| dc.title | LogEvent2vec : LogEvent-to-vector based anomaly detection for large-scale logs in internet of things | en |
| dc.type | Journal article | en |
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