Matches in SemOpenAlex for { <https://semopenalex.org/work/W4285145763> ?p ?o ?g. }
Showing items 1 to 89 of
89
with 100 items per page.
- W4285145763 endingPage "10" @default.
- W4285145763 startingPage "1" @default.
- W4285145763 abstract "Internet of Things (IoTs) is envisaged to widely capture the realm of logistics and transportation services in future. The applications of ubiquitous IoTs have been extended to Maritime Transportation Systems (MTS) that spawned increasing security threats; posing serious fiscal concerns to stakeholders involved. Among these threats, Distributed Denial of Service Attack (DDoS) is ranked very high that can wreak havoc on IoT artifacts of the MTS networks. Timely and effective detection of such attacks is imperative for necessary mitigation. Conventional approaches exploit entropy of attributes in network traffic for detecting DDoS attacks. However, the majority of these approaches are static in nature and consider only a few network traffic parameters, limiting the number of DDoS attack detection to a few types and intensities. In current research, a novel framework named “Dual Stack Machine Learning (S2ML)” has been proposed to calculate distinct entropy-based varying 10-Tuple (T) features from network traffic features, three window sizes and associated Rate of Exponent Separation (RES). These features have been exploited for developing an intelligent model over MTS-IoT datasets to successfully detect multiple types of DDoS attacks in MTS. S2ML is an efficient framework that overcomes the shortcomings of prevalent DDoS detection approaches, as evident from the comparison with Multi-layer Perceptron (MLP), Alternating Decision Tree (ADT) and Simple Logistic Regression (SLR) over different evaluation metrics (Confusion metrics, ROCs). The proposed S2ML technique outperforms prevalent ones with 1.5% better results compared to asserted approaches on distribution of normal/attack traffic. We look forward to enhancing the model performance through dynamic windowing, measuring packet drop rates and infrastructure of Software Defined Networks (SDNs)." @default.
- W4285145763 created "2022-07-14" @default.
- W4285145763 creator A5042109913 @default.
- W4285145763 creator A5047199689 @default.
- W4285145763 creator A5052391962 @default.
- W4285145763 creator A5061357625 @default.
- W4285145763 creator A5074431197 @default.
- W4285145763 creator A5077752961 @default.
- W4285145763 date "2022-01-01" @default.
- W4285145763 modified "2023-10-16" @default.
- W4285145763 title "Securing IoT Based Maritime Transportation System Through Entropy-Based Dual-Stack Machine Learning Framework" @default.
- W4285145763 cites W1484917059 @default.
- W4285145763 cites W1965343849 @default.
- W4285145763 cites W2049710565 @default.
- W4285145763 cites W2079262584 @default.
- W4285145763 cites W2153334513 @default.
- W4285145763 cites W2290966079 @default.
- W4285145763 cites W2626509862 @default.
- W4285145763 cites W2769202530 @default.
- W4285145763 cites W2798388460 @default.
- W4285145763 cites W2854846946 @default.
- W4285145763 cites W2892485325 @default.
- W4285145763 cites W2892556724 @default.
- W4285145763 cites W2964948631 @default.
- W4285145763 cites W3007757402 @default.
- W4285145763 cites W3042259242 @default.
- W4285145763 cites W3105750153 @default.
- W4285145763 cites W3138598418 @default.
- W4285145763 cites W4253521989 @default.
- W4285145763 doi "https://doi.org/10.1109/tits.2022.3177772" @default.
- W4285145763 hasPublicationYear "2022" @default.
- W4285145763 type Work @default.
- W4285145763 citedByCount "2" @default.
- W4285145763 countsByYear W42851457632023 @default.
- W4285145763 crossrefType "journal-article" @default.
- W4285145763 hasAuthorship W4285145763A5042109913 @default.
- W4285145763 hasAuthorship W4285145763A5047199689 @default.
- W4285145763 hasAuthorship W4285145763A5052391962 @default.
- W4285145763 hasAuthorship W4285145763A5061357625 @default.
- W4285145763 hasAuthorship W4285145763A5074431197 @default.
- W4285145763 hasAuthorship W4285145763A5077752961 @default.
- W4285145763 hasBestOaLocation W42851457632 @default.
- W4285145763 hasConcept C106301342 @default.
- W4285145763 hasConcept C110875604 @default.
- W4285145763 hasConcept C119857082 @default.
- W4285145763 hasConcept C121332964 @default.
- W4285145763 hasConcept C136764020 @default.
- W4285145763 hasConcept C154945302 @default.
- W4285145763 hasConcept C165696696 @default.
- W4285145763 hasConcept C31258907 @default.
- W4285145763 hasConcept C38652104 @default.
- W4285145763 hasConcept C38822068 @default.
- W4285145763 hasConcept C41008148 @default.
- W4285145763 hasConcept C50644808 @default.
- W4285145763 hasConcept C60908668 @default.
- W4285145763 hasConcept C62520636 @default.
- W4285145763 hasConceptScore W4285145763C106301342 @default.
- W4285145763 hasConceptScore W4285145763C110875604 @default.
- W4285145763 hasConceptScore W4285145763C119857082 @default.
- W4285145763 hasConceptScore W4285145763C121332964 @default.
- W4285145763 hasConceptScore W4285145763C136764020 @default.
- W4285145763 hasConceptScore W4285145763C154945302 @default.
- W4285145763 hasConceptScore W4285145763C165696696 @default.
- W4285145763 hasConceptScore W4285145763C31258907 @default.
- W4285145763 hasConceptScore W4285145763C38652104 @default.
- W4285145763 hasConceptScore W4285145763C38822068 @default.
- W4285145763 hasConceptScore W4285145763C41008148 @default.
- W4285145763 hasConceptScore W4285145763C50644808 @default.
- W4285145763 hasConceptScore W4285145763C60908668 @default.
- W4285145763 hasConceptScore W4285145763C62520636 @default.
- W4285145763 hasLocation W42851457631 @default.
- W4285145763 hasLocation W42851457632 @default.
- W4285145763 hasOpenAccess W4285145763 @default.
- W4285145763 hasPrimaryLocation W42851457631 @default.
- W4285145763 hasRelatedWork W1496222301 @default.
- W4285145763 hasRelatedWork W1590307681 @default.
- W4285145763 hasRelatedWork W2296488620 @default.
- W4285145763 hasRelatedWork W2353836703 @default.
- W4285145763 hasRelatedWork W2358353312 @default.
- W4285145763 hasRelatedWork W3207760230 @default.
- W4285145763 hasRelatedWork W41015297 @default.
- W4285145763 hasRelatedWork W4280645561 @default.
- W4285145763 hasRelatedWork W4285370786 @default.
- W4285145763 hasRelatedWork W4312814274 @default.
- W4285145763 isParatext "false" @default.
- W4285145763 isRetracted "false" @default.
- W4285145763 workType "article" @default.