10.46243/jst.2023.v8.i06.pp133-139 registered
Detection Of Cyber Attack In Network Using Machine Learning Techniques
Resolves to https://www.jst.org.in/index.php/pub/article/view/742
Held by Longman Publishers (India) · prefix 10.46243 live · DOI address https://doi.org/10.46243/jst.2023.v8.i06.pp133-139
Registered 29 Sep 2026 via crossref · record version 2 · last change 29 Sep 2026, 11:59 PM · record sha256 2dc6ab7f23ae4fa1…
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What the DOI identifies
JournalArticle — an article in a journal · Digital · Visual · en
Detection Of Cyber Attack In Network Using Machine Learning Techniques (PrincipalTitle)
Published 2023-08-07
Part of Journal of Science & Technology · ISSN 2456-5660 · volume 8 · issue 7 · pages 133–139
Agents
- Annam Pranitha Annam Pranitha (author)
- Longman Publishers (publisher)
Identifiers DOI 10.46243/jst.2023.v8.i06.pp133-139
Abstract
Improvements in computer and communication technologies have produced significant developments that are standing put from the past. Utilising new technologies offers governments, associations, and people incredible benefits, but some people are opposed to them. For instance, the security of designated data stages, the availability of data, and the assurance of important information. Dependent on these problems, advanced anxiety-based abuse may be the current big problem. Computerised dread, which caused many problems for foundations and individuals, has manifested at a level where it might be used to undermine national and open security by a variety of social entities, such as criminal association, intelligent people, and skilled activists. In order to maintain a crucial distance from sophisticated attacks, intrusion detection systems (IDS) have been developed. Learning to reinforce support is now taking place with accuracy rates pf 97.80% and 69.79%, respectively, vector machine (SVM) estimations were developed independently to recognise port compass attempts based on the new CICID2017 dataset. Perhaps instead of SVM, we can present some alternative calculations like CNN, ANN, and Random Forest 99.33, and ANN 99.11. To disrupt, disable, damage, or maliciously control a computing environment or infrastructure, to compromise the integrity of data, or to steal controlled information, a cyber-attack attacks an enterprise’s usage of cyberspace’s via cyberspace. Cyberspace’s current state foretells uncertainty for the internet’s future and its rising user base. With big data obtained by gadget sensors disclosing enormous amounts of information, new paradigms because they might be exploited for targeted attacks. Cyber security is currently dealing with new difficulties as a result of the expansion of cloud services, the rise in users of web applications, and changes to the network infrastructure that links devices with different operating systems. So by detecting the cyberattacks we can solve this problem
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Each element by the standard's name (Annex B: reference elements, then administrative) and the Handbook's (in grey), read off the record above.
| Element | Value | In the record |
|---|---|---|
| DOI Name DOI name | 10.46243/jst.2023.v8.i06.pp133-139 | doi |
| Referent Type referentType | Creation | referent |
| Referent Sub-Type referentSubType | JournalArticle — an article in a journal | type |
| Referent Name(s) referentName(s) | Detection Of Cyber Attack In Network Using Machine Learning Techniques (PrincipalTitle, en) | titles |
| Basic Metadata basicMetadata | author: Annam Pranitha Annam Pranitha publisher: Longman Publishers published: 2023-08-07 part of: Journal of Science & Technology · ISSN 2456-5660 · vol. 8 · no. 7 · pp. 133–139 language: en form: Digital · Visual · Language | agents, dates, container, language, structural_type, modes, characters |
| Referent Identifier(s) alternateIdentifier(s) | none besides the DOI | identifiers, relations (IsSameAs) |
| Registration Authority registrationAuthorityCode | Crossref — issued by Crossref (member 25296); held here as a copy | record.source_agency (our code, ra_doi_name, for names issued here once appointed) |
| Created Date issueDate | 2024-02-16 | record.registered (when the DOI name was first registered) |
| relatedIdentifiers | none needed — the descriptive metadata is in this record | container, relations (only where the descriptive metadata lives at another identifier) |
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Every change to this DOI, in order, as it was recorded. Entries are only ever added, never changed or removed.
| # | When | What | By | Changes |
|---|---|---|---|---|
| 1 | 29 Sep 2026, 10:00 PM | register registered at Crossref; record read from api.crossref.org | Administrator (admin) | 91 fields set · sha256 121e704add80… |
| 2 | 29 Sep 2026, 11:59 PM | update record re-read from api.crossref.org | Administrator (admin) | container.titles.0.value: |
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