Matches in SemOpenAlex for { <https://semopenalex.org/work/W3198620402> ?p ?o ?g. }
Showing items 1 to 59 of
59
with 100 items per page.
- W3198620402 endingPage "8235" @default.
- W3198620402 startingPage "8226" @default.
- W3198620402 abstract "For every second after digitization, enormous quantities of data are generated from different networks. The value of providing this data with protection has therefore increased. The need to automate this protection framework has become necessary as the data is really massive. Intrusion detection systems are known as a great approach for intrusion detection. The system for detecting intrusions serves as an important mechanism to detect web security attacks. A proven technique for detecting network-based attacks, the Intrusion Detection System is still inexperienced in monitoring and recognising attacks, but efficiency remains unchanged. A large number of techniques that are based on machine learning approaches have been developed.In this paper, the CIDDS-001 dataset [12] is analyzed and the observations have been marked. Two supervised machine learning techniques such as K-Nearest Neighbour and Naive Bayes are implemented on this dataset. KNN is implemented with different K – values. KNN is executed by changing the number of testing records. K – Value is also decided by making keen observations. KNN algorithm gives on an average 92.3% accuracy. Naive Bayes algorithm is also executed by changing the number of testing records. Naive Bayes algorithm gives on average 70.66% accuracy. Time complexity of NB algorithm is less than KNN. Comparison of both the methods is presented by comparing their evaluation metrics like Accuracy, Precision, Recall, Specificity and F- Measure. This paper is concluded by identifying the pros and cons of both the algorithms and by providing the future scope of this paper." @default.
- W3198620402 created "2021-09-13" @default.
- W3198620402 creator A5013075220 @default.
- W3198620402 creator A5084367559 @default.
- W3198620402 date "2021-08-12" @default.
- W3198620402 modified "2023-09-28" @default.
- W3198620402 title "Network Intrusion Detection System Using KNN and Naive Bayes Classifiers" @default.
- W3198620402 hasPublicationYear "2021" @default.
- W3198620402 type Work @default.
- W3198620402 sameAs 3198620402 @default.
- W3198620402 citedByCount "0" @default.
- W3198620402 crossrefType "journal-article" @default.
- W3198620402 hasAuthorship W3198620402A5013075220 @default.
- W3198620402 hasAuthorship W3198620402A5084367559 @default.
- W3198620402 hasConcept C119857082 @default.
- W3198620402 hasConcept C12267149 @default.
- W3198620402 hasConcept C124101348 @default.
- W3198620402 hasConcept C154945302 @default.
- W3198620402 hasConcept C35525427 @default.
- W3198620402 hasConcept C41008148 @default.
- W3198620402 hasConcept C52001869 @default.
- W3198620402 hasConceptScore W3198620402C119857082 @default.
- W3198620402 hasConceptScore W3198620402C12267149 @default.
- W3198620402 hasConceptScore W3198620402C124101348 @default.
- W3198620402 hasConceptScore W3198620402C154945302 @default.
- W3198620402 hasConceptScore W3198620402C35525427 @default.
- W3198620402 hasConceptScore W3198620402C41008148 @default.
- W3198620402 hasConceptScore W3198620402C52001869 @default.
- W3198620402 hasIssue "7" @default.
- W3198620402 hasLocation W31986204021 @default.
- W3198620402 hasOpenAccess W3198620402 @default.
- W3198620402 hasPrimaryLocation W31986204021 @default.
- W3198620402 hasRelatedWork W1539625341 @default.
- W3198620402 hasRelatedWork W1542270631 @default.
- W3198620402 hasRelatedWork W2518336821 @default.
- W3198620402 hasRelatedWork W2737727062 @default.
- W3198620402 hasRelatedWork W2789269770 @default.
- W3198620402 hasRelatedWork W2971255169 @default.
- W3198620402 hasRelatedWork W2993309345 @default.
- W3198620402 hasRelatedWork W3008913311 @default.
- W3198620402 hasRelatedWork W3042736837 @default.
- W3198620402 hasRelatedWork W3091897064 @default.
- W3198620402 hasRelatedWork W3113446920 @default.
- W3198620402 hasRelatedWork W3120409033 @default.
- W3198620402 hasRelatedWork W3127653662 @default.
- W3198620402 hasRelatedWork W3132783280 @default.
- W3198620402 hasRelatedWork W3136244248 @default.
- W3198620402 hasRelatedWork W3138539755 @default.
- W3198620402 hasRelatedWork W3153505674 @default.
- W3198620402 hasRelatedWork W3164983683 @default.
- W3198620402 hasRelatedWork W2490463991 @default.
- W3198620402 hasRelatedWork W2556439483 @default.
- W3198620402 hasVolume "12" @default.
- W3198620402 isParatext "false" @default.
- W3198620402 isRetracted "false" @default.
- W3198620402 magId "3198620402" @default.
- W3198620402 workType "article" @default.